I have been writing blog posts for well over a decade, first at Making Things Out of Nothing, and then here at allensthoughts.com on WordPress.
I moved to WordPress because I wanted more control. WordPress is open source. I can host it myself. I can DIY. I am not at the mercy of any one platform.
But, like everything, there is a tradeoff.
Running my own WordPress site means I also need to invest time and effort to keep it modern, secure, and working well. And when time is my most expensive commodity, I have to admit that Allen’s Thoughts could have been better maintained.
More importantly, I want to spend my time sharing my thoughts, not maintaining the plumbing.
In the past few years, I have been spending much of my time with researchers, professors, and deep tech founders sitting on remarkable breakthroughs and asking a difficult question:
What does it take to turn this innovation into a world-class company?
That question has become central to how I think about this chapter of my life.
This month marks the fifth anniversary of the Wattpad acquisition in 2021. That milestone naturally invites reflection. I am deeply grateful for that chapter and everything I learned from it, but I have 100% moved on.
Why?
Because I have even more fire in the belly for what comes next.
People sometimes ask me: Do I miss operating? Why am I doing this now? Why not just start another company and do it all over again?
Those questions all lead to a deeper one:
What does winning look like for me now?
For me, winning has always been about impact. Of course, many other things matter too. But without impact, I am not interested.
That has not changed.
What has changed is where I believe my experience is most useful, where I can have the highest-leverage impact, and what kind of challenge I feel most drawn to now.
I have no interest in simply repeating the last chapter. I have already co-founded and led one iconic company that reached 100 million users globally and became a cultural phenomenon. Fewer than two hundred companies in the world have achieved that 100-million-user milestone. Even fewer founders have stayed for the full marathon, from the first user all the way to a home run.
Rather than taking it easy, I want a new and even more ambitious challenge.
I have come to believe that one of the most important challenges in deep tech today is helping scientists and deep tech founders cross the very difficult bridge from scientific and engineering breakthrough to building a world-class company.
That is the work I feel most drawn to now. It is also work I feel unusually prepared for.
I started three companies. Between them, I have seen almost every major founder outcome: one VC-backed failure as CTO with tons of very stupid mistakes, one bootstrapped company as CEO with a small exit, and one VC-backed home run in Wattpad as CEO.
From the outside, Wattpad looked deceptively simple. In reality, it became an incredibly complex global business spanning consumer, enterprise, subscriptions, virtual goods, social media, frontier technology, traditional publishing, entertainment, and even geopolitics.
We were one of the pioneers in UGC and mobile, before the iPhone even existed. Over time, Wattpad also became a deep tech company. We started building our first of many proprietary machine learning models around 2013, long before most people had even heard of AI. That shaped how I think about technology disruption and how real technical innovation becomes enduring advantage.
I also lived through strategic investors, IPO preparation, multi-bidder acquisition processes, the constant need to disrupt and reinvent ourselves, moments when tech giants were clearly trying to kill us, and a few phoenix-from-the-ashes moments.
I do not say any of this to dwell on the past. I say it because seeing that many startup permutations from the inside gives you a massive toolbox of practical judgment and wisdom.
Those tools were built and tested through real-world operating experience from day one, scaling a business into a world-class company while enduring the full roller-coaster ride.
You learn them by starting a company when the market is not ready. You learn them by doing things no one has done before. You learn them by making painful mistakes. You learn them by carrying a company through long periods when it is working, but not yet obvious. You learn them by navigating the transition from prototype to product, from product to business, from business to company, and from startup to an enduring world-class venture.
That sequence matters deeply in what I do now, because very few people have lived it end to end: a breakthrough is not yet a product. A product is not yet a business. And a business is not yet an enduring, world-class company.
The bridge between those stages is turning innovation into product and then commercializing it. That is where many promising breakthroughs fail. Not because the innovation is weak, but because turning groundbreaking innovation into a world-class company requires a different set of skills and judgments: timing, technical moat, customer need, business model, smart capital, team building, endurance, and grit.
You need to understand how all of the pieces connect and work together to build a world-class company.
I now know what I did not know.
That belief sits at the center of how I now spend my time. My mission is to unleash the full potential of scientists and their innovations by helping them become entrepreneurs and build world-class companies.
That, more than anything else, is what this chapter is about for me.
That is also part of what makes TSF distinctly TSF.
We are not trying to be a generic early-stage fund. Across our whole investment team, without exception, we bring together a combination that is very rare in venture globally: deep technical chops, real-world operating experience, scar tissue from world-class company building, and a mission-driven commitment to helping scientists and technical founders build enduring, world-class companies. We are also proven full-cycle investors with the experience of backing multiple companies of exceptional scale.
To me, TSF is not simply an investment platform. It is one of the highest-leverage ways I can apply what I have learned to make the greatest impact.
Building one iconic world-class company is hard. Leveraging that experience to help build multiple world-class companies may be even harder.
That is the challenge I want.
The next chapter started four years ago when I stepped down as Wattpad CEO, and I have been building into it ever since.
I am entering this next stretch with a lot of fire in the belly and 100% commitment. For me, that is what winning looks like.
I will continue to post here for the time being. Whether you are a subscriber here or not, please take 30 seconds to subscribe to my new Substack, A Recovering CEO’s Thoughts by Allen Lau.
My last post — Stop Supplying. Start Owning. — was one of the most engaging posts I have published in recent weeks. One part of that talk that I did not go deep enough on was the banana analogy.
I have been using this framework in talks for some time now — most recently at the Engineering Deans Canada annual meeting in Winnipeg, and before that in a keynote at York University’s Schulich School of Business on a related but different topic: “Think like an owner”. I think this analogy deserves its own post.
So for this Sunday morning, something a little lighter. Just five banana lessons that I think apply whether you are a student figuring out your first job, a founder building a company, or an investor trying to understand where value actually lives.
Yes, I went bananas — but not in a way you might think. It all starts with a monkey.
The Setup
Jack Ma once said: if you put money and a banana in front of a monkey, the monkey takes the banana. It does not know that money can buy many bananas.
I love this analogy. On the surface, it is a simple observation about short-term versus long-term thinking. But the more I have sat with it — through three companies with well over a thousand employees across three companies, two exits, and now as an investor in over 60 companies — the more I think it contains an entire philosophy of value creation.
Here are the five lessons I have drawn from it.
Lesson 1 — Cash Is Better Than a Banana
Jobs are bananas.
People grab them because a steady salary and job security feel safe. And they are not wrong to. A banana feeds you. It is real. It matters.
But a banana feeds you once. Cash — real ownership, real equity, real stakes in what you are building — feeds you many times. The problem is not that people value jobs. The problem is that too many people never stop to ask whether there is something better in front of them.
Recognizing that alternatives exist is the first step toward creation and ownership. Most people never take that step — not because they lack ambition, but because nobody ever put the alternative clearly in front of them.
Lesson 2 — Some Bananas Are Better Than Others
Not all jobs are created equal.
Some opportunities teach you, compound your skills, put you inside exceptional teams, and give you proximity to how great companies are actually built. Others keep you comfortable but stuck — including, surprisingly, many high-paying jobs at large, slow-moving organizations.
The number of jobs created is not a useful measure of prosperity. The quality of those jobs — and what they teach, and what they lead to — is what matters.
When I was early in my career, I worked at Delrina, one of the most successful Canadian tech companies of the 1990s. The company grew from 20 people to 800 in four years when Eva and I worked there. We learned more in that rocketship environment than I could have anywhere else. That was not a banana. That was a greenhouse banana — rare, valuable, and 100% worth seeking out.
The lesson: be deliberate about which banana you grab. Not all of them are the same.
Lesson 3 — A World-Class Banana Tree Is Better Than a Banana
A banana feeds you once. A tree feeds you forever.
This is where the shift from employee thinking to founder thinking begins. One banana is a salary. A tree is equity, ownership, and compounding returns on something you built.
Ownership compounds. Wages do not.
The number of jobs created is still the wrong KPI. A single world-class company — owned, scaled, and defended — creates more durable economic value than a thousand comfortable jobs at organizations that will be restructured, acquired or hollowed out over time.
Do not just own the banana. Own the tree.
Lesson 4 — A Banana Farm Is Better Than a Tree
A tree is better than a banana. But a farm is better than a tree.
Dole, a company valued at just over $1 billion and one of the most recognizable fruit brands in the world, does not just grow bananas. It operates a vertically integrated business — owning farmland, managing logistics, controlling supply. It works with over 8,000 independent farmers who supply it. Those farmers are good at what they do. But they are suppliers.
Participation as a supplier is not enough. Ownership of the platform — the farm, the infrastructure, the system — is where the compounding really begins.
Even “the number of trees” is the wrong KPI. It is the farm that matters.
Lesson 5 — A Store Is Better Than a Farm
This is the one that tends to land hardest in a room.
Even Dole — a billion-dollar company, one of the most recognized brands in its category — is a tiny supplier to the giant retailers that actually own the customer relationship. Walmart. Costco. Amazon. These are the stores. They do not grow bananas. They sell them — at scale, with leverage, owning the customer from end to end.
The store owns the customer. The store sets the rules. The store captures the value that flows through the entire chain. Needless to say, many of these stores are an order of magnitude more valuable than Dole.
This is the lesson that I applied at Wattpad. We were not just a reading platform. We owned the direct relationship with five million writers and one hundred million readers, with virtually no external dependencies. That end-to-end ownership is what made us defensible.
Amazon Kindle tried to kill us — not once, but multiple times. They launched product after product specifically designed to compete with Wattpad. Not only did we win every battle, we won the war. A clean sweep. It is rare for a company our size to take on Amazon Kindle directly and come out on top. Owning the full chain — the writers, the readers, and the relationship between them — is what made that possible. I will save the full story for another post.
True prosperity means owning the whole chain — from innovation to commercialization, from suppliers to customers. The number one KPI is ownership. Jobs follow capital, innovation, and commercialization. Not the other way around.
Why This Matters Beyond Business
I have shared this framework in many different rooms — with founders, with students, with engineering deans — and it lands every time. I think it is because the banana lessons are not really about business. They apply broadly to how we think about our lives.
Yes, the framework is useful in a business context. And yes, it is useful in an investment context. But it also applies to personal decisions, career choices, relationships, and how we spend our time. Are you grabbing the banana in front of you because it is comfortable and familiar? Or are you asking what the tree looks like? What the farm looks like? Who owns the store?
The mental model you build early about what success looks like shapes every decision that follows. Most people never stop to interrogate it.
Do not just grab the banana. Ask yourself what the tree looks like. Then ask what the farm looks like. Then ask who owns the store.
That is where the real value lives — in business, in investing, and in life.
If you missed the post this is a follow-up to, you can read Stop Supplying. Start Owning. here: [Link]
Canada has a paradox that I have been talking about for a long time.
We are home to most of the world’s AI godfathers. We have Nobel Prize winners, world-class researchers, and some of the most respected engineering schools on the planet. Those institutions attract exceptional students from around the world. And in turn, Canada trains some of the best engineering talent anywhere.
Yet an increasing number of those graduates — now approaching 80% — leave after convocation.
With them go the startups they might have built, the economic value they might have created, and the wealth that could have stayed here. We all know the largest and most valuable companies are technology companies, and they are based in the United States. Many of them were co-founded or led by Canadians.
It is a story of could have been, would have been, and should have been.
I was recently invited to speak at the Deans of Engineering Conference in Winnipeg. I want to share the core of what I said, because I think this conversation matters well beyond that room.
The root cause is not what most people think
The easy explanations are talent, capital, and policy. We hear them constantly. They are not wrong, but they are not the root cause.
The root cause is a mindset.
Clearly, we do not have a shortage of ambition or ability. One fundamental issue stands out — yet very few people talk about it, let alone address it. We have collectively learned to think like suppliers, not owners.
Without the owner mindset, we unintentionally and subconsciously optimize for producing great talent for other countries, rather than building a stake in where that talent goes and what it creates.
This is the supplier mindset made visible.
Let me illustrate with a banana
I use a banana analogy in my talks because it makes the concept concrete.
If you put money and a banana in front of a monkey, the monkey takes the banana. It does not know that money can buy many bananas. That insight comes from Jack Ma, who used this analogy to compare the mindset of someone who grabs a job versus someone who builds a company.
Jobs are bananas. They are real, they matter, and they feed people. A banana feeds you once. Cash feeds you many times.
But the lessons go further.
A banana tree is better than a banana because it can feed you forever. Ownership compounds; wages do not. A banana farm is better than a tree — because participation as a supplier is not enough; ownership of the platform is the real prize. And a store is better than a farm, because the store owns the customer relationship and captures the value that flows through the entire chain.
This is the progression from employee thinking to owner thinking. From banana to store. From grabbing to owning.
Canada has been grabbing bananas
Let me make this concrete with two examples — one personal, one national.
The Wattpad calculation. When Wattpad was acquired for US$660 million, the headline was a Canadian success story. And in many ways, it was. But here is the number nobody talks about. By the time of the acquisition, roughly half of the company was owned by Canadians. When the deal closed, about US$330 million in economic value left the country — because we had raised capital from outside Canada to build it.
Wattpad’s annual payroll was roughly US$30 million. Not small. But compared to the acquisition price, it is a fraction. Ownership creates far more value than employment. Jobs matter. Entrepreneurship matters. But nothing compares to owning world-class companies.
The auto industry analogy. Many people say Canada has a strong auto industry. We do not. We have a strong auto supplier industry. That is not the same thing. Our auto suppliers — collectively — are worth a fraction of GM, Ford, or Toyota. They build the factories, employ the workers, and take on the operational risk. When the EV transition stalled, the suppliers’ brand new facilities went quiet. When the majors slowed production, the layoffs rippled through.
The supplier bears the downside. The owner captures the upside and sets the rules.
And when the Canadian government went to attract EV investment, what did we do? We signed deals to become suppliers again — subsidized by Canadian taxpayers, while the ownership, brand, and margin stayed elsewhere. We took the risk but not the profit.
This is the supplier mindset at a national scale.
The question nobody asks clearly enough
Here is the hinge question: what does winning actually look like?
The supplier mindset and the owner mindset do not just lead to different outcomes. They lead to completely different definitions of winning.
If you are a supplier, sending your best researchers to OpenAI is a win. You produced world-class talent. Mission accomplished. That belongs in the annual report.
If you are an owner, that is a loss. You invested in that person for years, and you ended up owning nothing. The outcome looks identical from the outside — a brilliant Canadian thriving on the world stage — but the two mindsets score it completely differently.
Until we agree on what winning actually means, we will keep celebrating losses as victories.
Where the mindset gets formed
Here is what I have come to believe: the supplier mindset is not learned on the job. It is learned in school.
The mental model a student builds about what success looks like — a FAANG job offer, a US grad school acceptance, a signing bonus from a company they can brag about — is set before they ever enter the workforce.
In the US, building a unicorn startup is Plan A. Getting a job at Google is Plan B. In Canada, getting a job at Google — or going to the US — is Plan A. Building a startup, let alone a unicorn, is often not even in the equation.
That quote is from a world-class Canadian AI scientist who is now at a US company. It landed hard when I first heard it, because it is accurate.
The deans are the front line
I said something direct to the room in Winnipeg that I want to say here too.
The founders of most of Canada’s future tech giants are sitting in engineering classrooms right now. The deans who lead those schools are the single most underleveraged force in Canada’s innovation economy.
Here is why this is also in the deans’ own interest. If their students build world-class companies and keep them here, those companies will forever be associated with that school. That is a legacy that compounds for decades. The next crop of students is inspired by the tech giants that exist. Right now, leading universities outside of Canada are winning that recruitment battle — not because their engineering programs are better, but because the companies their graduates built are more visible, more celebrated, and more aspirational.
Think about OpenAI. It was co-founded by a University of Toronto alumnus. Most people associate it with Silicon Valley.
That association is not fixed. It is a choice, made one graduating class at a time.
This is not only about encouraging entrepreneurship
I want to be precise here, because there is a version of this argument that deans hear all the time and that I think misses the point.
Many engineering schools already encourage entrepreneurship. Hackathons. Incubators. Pitch competitions. These are necessary. But they do not define what success looks like. And in a strange way, encouraging entrepreneurship is still a supplier mindset — we are producing entrepreneurs for the ecosystem and hoping something sticks.
The real call to action is different. It is to start and scale world-class companies here in Canada.
That is a higher bar. A different ambition. A fundamentally different culture to build. It means celebrating the founder who builds a billion-dollar Canadian company with the same institutional pride as the researcher who wins a Nobel Prize. It means changing what the school defines as a win — not only placements, publications, and patents, but also companies that stay, scale, and own their category.
The window is now
I have saved the most important point for last.
We lost Game 1. Canada invented modern AI. The most important AI companies are almost all based in the US. That window has closed.
But Game 2 is underway. Quantum computing. Robotics. Physical AI. Space. Advanced manufacturing. Smart energy. Just to name a few. Canada has deep roots in all of these — world-class labs, exceptional researchers, and early-stage companies that are genuinely competitive.
Here is what is different about Game 2: you cannot pack up a quantum computing facility or a robotics lab and move it to San Francisco. Unlike software, the physical infrastructure is sticky. The talent clusters around it. The companies that emerge will be rooted where the labs are.
And the ground-level signal I am seeing is genuinely encouraging. I have never met more professors and researchers who want to start companies — and who want to do it in Canada. That is new. That is meaningful.
The conditions are finally aligned to address the root problem, not just the symptoms. But the only trophy that ultimately matters is homegrown, world-class companies. And we can only win Game 2 — and ultimately the championship — if we build the owner mindset now, starting with the people who shape how the next generation of engineers think about what success looks like.
Addressing the supplier mindset and turning it into an owner mindset can create the domino effect that turns Canada’s bragging rights into lasting economic wins.
We are super excited to share our investment in Tiptree Systems!
Founded in Montreal by two Mila AI researchers, Dr. Martin Weiss and Nasim Rahaman, Tiptree is building an AI-native researcher and knowledge network: infrastructure for how AI researchers share, exchange, and advance knowledge.
There is an irony here. AI has advanced remarkably quickly, yet until now, there has not really been an AI-native way for AI researchers themselves to share knowledge and build on one another’s work. Tiptree is solving that problem.
This is exactly the kind of company that fits our thesis at Two Small Fish. We invest in technologies that can reshape large-scale behaviour, enabled by foundational shifts in computing. The collapsing cost of intelligence is changing not only how software is built but also how work gets done. It is also changing how knowledge can be organized, explored, and shared.
I cannot tell you how much my first computer, an Apple II, impacted me.
It was my first computer. It had a green monochrome monitor. It had 16KB of memory, which is roughly 2 million times less than the 32GB MacBook I am using to write this post. By any modern standard, it was primitive. To boot it, I had to use a cassette tape. Yes, cassette tape!
Thankfully, it had a few expansion slots, so the machine was quickly upgraded to 64KB, with a floppy drive and later two of them to facilitate copying disks, plus a sound card to make some noise. Still no hard drive, of course. That would have been too expensive to ask my parents to buy for me.
What made that machine special was not the hardware. It was what it unlocked for me.
For the first time, I could be creative through writing software. I started with the programming language BASIC, which felt magical back then. Occasionally, I had to write in assembly language, which meant dealing with 0s and 1s directly and pulling hair along the way. It was clunky. It was frustrating. It was also incredibly fun and deeply fulfilling when the program finally worked!
So I wrote games and other fun programs to keep myself entertained. Looking back, that was the real gift. My late father did not just buy me the best toy I could have imagined. He gave me a machine that allowed me to become a permissionless innovator, a tinkerer, a self-taught learner, and someone who learned early to think differently.
That mindset stayed with me.
It shaped how I see the world as an engineer, as a founder, and now as an investor. Long before I had the language for it, the Apple II taught me that technology is at its best when it gives people leverage, creativity, and the freedom to build.
Apple’s anniversary post mentions the Apple II among the products that helped define the company’s first 50 years. For me, it did something even more personal. It helped define mine.
Maybe that is where it all began. Thinking differently is not just about being creative. It is about seeing what others do not see yet. In many ways, that idea has stayed with me ever since and still shapes how I think about technology, innovation, and investing today.
Looking back, I think learning to think differently was where the idea that seeing the future is our superpower first took shape.
And thank you to one little Apple II with 16KB of memory, a cassette tape, and just enough magic to change a kid’s life.
That is like saying humans need to sleep, eat, and drink. True, yes. Useful, no.
The more important question is: what does “high quality” actually mean in venture?
For us, it means the potential to become uniquely world class.
A company that can become the clear winner in an important category. A company with real moats. A company that can build something enormous.
This is why we spend so much time trying to understand what is truly unique about a company. Not what is interesting. Not what demos well. Not what sounds differentiated in a pitch deck. Not what the ARR is today. What is actually hard to replicate? What gets stronger over time? What creates a widening gap versus everyone else? And the only way to know is to spend time with these deep tech founders and really understand how the technology, the product, and the company work.
I have written a long blog post on this topic on Two Small Fish’s website. Here is the link.
We are super excited to share that Two Small Fish led YScope’s US$3.9 million financing, with Snow Angels (the Snowflake alumni investment syndicate), Next Wave NYC, UTEST, and other successful founders participating.
YScope was cofounded by University of Toronto Professor Ding Yuan, who is also CEO, Professor Michael Stumm, Dr. Kirk Rodrigues, Dr. David Lion, Yu (Jack) Luo, and Beverly Xu (Guangji Xu). It is a deeply impressive team building open-source logging infrastructure for the AI era, combining deep systems research with real-world production traction.
Its core technology, CLP (Compressed Log Processor), makes log storage, search, and analytics dramatically more efficient for both humans and AI, across cloud and edge environments.
We believe this is a massive opportunity. As the cost of intelligence collapses, AI agents, robots, autonomous vehicles, and other intelligent systems will generate orders of magnitude more machine-generated events. A robotic finger moves. A self-driving car makes a slight turn. An AI agent retries a task. Each action creates an event, and the infrastructure layer that can handle that explosion efficiently will matter enormously.
YScope is also a strong mutual fit for TSF. We invest in the next frontier of computing and its applications, and we know firsthand how painful logging becomes at scale. I have spent enough time with logs that I will never get back. At Wattpad, logging every tap, swipe, and click could easily add up to billions of events a day. That is why YScope’s traction is so compelling, from powering Uber’s production logging platform to operating across more than 1.5 million connected electric vehicles and being used by Fortune 500 organizations.
Congrats to Ding, Michael, Kirk, David, Jack, Beverly, and the entire YScope team. Full blog post here.
Today is Pi Day, and it feels like a good excuse to reflect on an old friend.
Most people say goodbye to our friend π after school. I’ve been lucky enough to stay in touch. The relationship has evolved over the years, from a childhood friendship in math class to something that followed me into engineering school and later into my work. It is a good reminder that the academic foundations we build early do not stay behind. They continue to shape how we see the world and how we build what comes next.
At Two Small Fish, the next frontier of computing is our investment thesis. We see it taking shape across five areas: Vertical AI Platforms, Physical AI, AI Infrastructure, Advanced Computing Hardware, and Smart Energy. For Pi Day, I thought it would be fun to pick one equation I learned along the way for each of these five areas, and reflect on how it still connects to the technologies shaping this next frontier.
For Vertical AI Platforms, I think of the Gaussian distribution: f(x) = 1/(σ√(2π)) · e^(-(x-μ)^2 / 2σ²), which is foundational in probability and statistics. Even as AI becomes more vertical and more embedded in real workflows, it still rests on probability, statistics, and uncertainty. π is there too.
In Physical AI, the equation I think of is ω = 2πf, which defines angular frequency. I studied control systems and, one summer during my junior year at university, wrote software to control a robotic arm. That was an early lesson that once software meets motion, π becomes part of how the physical world is described.
In AI Infrastructure, I think of the Fourier transform: X(f) = ∫ x(t)e^(-j2πft) dt. I studied signal processing, my bachelor’s thesis was in image processing, and my master’s thesis was on noisy CDMA wireless networks. That math shaped how I thought about signals, images, noise, and communication then, and Fourier shows up in modern LLMs now.
In Advanced Computing Hardware, my equation is ℏ = h/2π. I studied optics in communications, which included a lot of quantum mechanics, so Planck’s constant was part of the vocabulary of the field. What stayed with me is that π shows up at the quantum level as part of the structure, not just the math.
In Smart Energy, the equation I would use is Xₗ = 2πfL, which calculates inductive reactance. It is a simple reminder that in AC systems, frequency directly shapes behaviour. As energy systems become smarter and more dynamic, π remains embedded in the physics underneath.
That may be why Pi Day still resonates with me. π is one of those rare constants that keeps reappearing across disciplines, from robotics to quantum mechanics, from signal processing to energy systems, and now across the next frontier of computing.
P.S. I also realized I missed mentioning my other friend Euler back on February 7. Next time!
OpenClaw, an AI agent that can operate a computer on your behalf, has taken the world by storm. Unless you have been living under a rock, you have probably either tried it already or at least wanted to find out what all the buzz is about.
Many, however, have failed to get past installation because it is so difficult. There is a reason why thousands of people lined up for help just to get OpenClaw installed on their machines. More importantly, using it without proper safeguards can create a real security risk.
From my perspective, three issues stand out in OpenClaw’s current form.
First, it is difficult to install, even for technical users. That matters more than many builders realize. A product does not become broadly useful simply because it is powerful. It becomes useful when people can actually get it running without friction or handholding.
Second, it can create a real security risk if not used properly. Tools that operate at the machine level can be compelling, but they also introduce a very different level of responsibility. Most users do not want to expose their full machine environment just to perform a simple task.
Third, it can become expensive quickly. Token bills can become material before users even realize it. A tool may look impressive in a demo, but if the economics do not work, adoption will eventually stall. In AI, performance matters, but efficiency matters just as much.
This is why, after looking at many options, I chose to use Crate from our portfolio company, Gensee, myself, and I believe it is by far the best way to try OpenClaw.
It addresses all three issues directly: one-click install in 60 seconds, a secure sandbox that only accesses what you explicitly allow, and deep expertise from Dr. Shengqi Zhu and award-winning operating systems expert Professor Yiying Zhang, whose work on agentic optimization and efficiency is exactly what makes this possible. That expertise is also why they have been able to make Crate completely free to use.
In other words, it makes OpenClaw easy, safe, and completely free.
There is also a bonus. Crate comes with Gensee’s proprietary AI search engine built in. That search engine ranked #1 on Source Bench for finding the highest-quality web sources.
Another bonus is that Crate comes pre-installed with a set of common, useful skills vetted by the Gensee team for safety, while still allowing users to install additional skills themselves. That makes it both easier to get started and more flexible over time.
A final bonus is flexible control. Users can create multiple instances, pause and resume them, take snapshots, and roll back at any time. That means full control without the usual complexity.
So Gensee Crate is not just an easier and safer way to use OpenClaw. It is also a better one, and that points to where this market is going. The first wave of a technology shows what is possible; the next wave makes it practical for mainstream users. AI agents are now entering that phase. To become part of everyday workflows, they need to be easy to use, safe by design, and efficient enough to be economically viable. That is where adoption happens.
And that is why Gensee Crate is the best way to try out OpenClaw and why it is worth paying attention to.
If you are curious about OpenClaw, try Gensee Crate here.
At Two Small Fish Ventures, we invest in the next frontier of computing and its applications. Supporting that thesis is our focus on research grounded innovation, which means we spend a lot of time with people who are building from first principles and turning technical breakthroughs into real companies. Not surprisingly, many of those people are world-class women researchers, scientists, and engineers. We have been fortunate to back a good number of them, and we are better for it.
This shows up in our portfolio, but it also shows up in our own team. Roughly half of our team is female. Our investment team is also roughly half female, with Eva and Mikayla bringing perspectives that genuinely shape how we think, how we evaluate, and how we support founders.
This is not just something to celebrate. It makes us better. One of the most common pieces of feedback we hear from founders is that we ask very different questions. That is exactly the point. Different perspectives lead to better conversations, smaller blind spots, and stronger judgment. In deep tech, where the path from breakthrough to company is rarely straightforward, that matters.
So today, we celebrate the many women founders, researchers, scientists, and engineers we have backed, and the many more we hope to back in the years ahead.
AI has a massive efficiency problem. It uses too much compute. It costs too much. It uses too much energy. And it is too slow.
Today, it can take a serious cluster of GPUs and a very non-trivial amount of electricity just to answer a simple question like “Can you summarize this document?” or “What should I reply to this email?” The machinery underneath is anything but.
This is why we invested in ByteShape. The company was co-founded by a world-class team out of the University of Toronto: Professor Andreas Moshovos [link]—whose group’s papers have amassed more than 10,000 citations—together with scientists Miloš Nikolić [link], Enrique Torres Sánchez [link], and Ali Hadi Zadeh [link], whose life’s work is making computation more efficient. Both Ali and Miloš were also postgraduate affiliates of the Vector Institute, and Miloš’s PhD research formed the foundation of ByteShape’s core technology—work that earned him recognition as an “ML and Systems Rising Star” by MLCommons last year.
They are building the kind of deep technology that changes the economics of AI deployment, then changes what products become possible.
Quantization, In Plain English
Many techniques underpin what ByteShape does. One of them jumped out: quantization.
Quantization is about using fewer bits to represent the numbers inside a model. Many models are trained with higher precision formats because it helps learning remain accurate. But AI inference often does not need that much precision everywhere. If you can safely represent weights and activations with fewer bits, you shrink memory use and speed up compute, often dramatically, while keeping outputs essentially the same.
ByteShape’s approach, ShapeLearn, does this in a way that feels obvious in hindsight and very hard in practice. ShapeLearn adaptively taps into the AI training process to learn optimal datatypes for parameters and inputs. The result can be 7x faster training and 10x faster inference.
In layman’s terms, the idea is simple and powerful: fewer bits, less work, and smaller models, without sacrificing results. All is being done adaptively.
Then ByteShape takes it one step further. ShapeSqueeze is their lossless compression layer that applies per-value encoding to minimize off-chip data transfers, with up to 40% extra compression.
Put the two together, and you get something that really matters in the real world. ShapeLearn reduces what the model needs to store and compute. ShapeSqueeze reduces what the hardware needs to move around. Less compute and less data movement means faster AI, lower cost, and lower energy.
This is not limited to savings in cloud data centres. It is a step-function improvement in what can run locally, which means a step-function improvement in what products can exist. It opens the door to privacy-sensitive and offline workflows, on-device agents, and embedded intelligence in robots and machines where speed, power and thermals matter.
Why TSF invested
Two Small Fish Ventures is an early-stage deep tech venture capital firm investing globally in the next frontier of computing and its applications. We invest where foundational breakthroughs create the conditions for new category-defining companies, and we back founders at the earliest stages when the technology is ready for commercialization.
ByteShape fits that thesis perfectly. They are building a foundational efficiency layer for AI that can reshape performance and cost across cloud, enterprise, and edge deployments. And because all TSF partners are engineers with deep operating experience, we do not just evaluate the science. We lean into technology through commercialization, with hands-on support informed by having built and scaled companies ourselves.
With ByteShape, the future is models that run faster, use less energy, and fit on far smaller hardware, without sacrificing the quality that makes them worth using.
Today, writing software is no more difficult than pressing a button. You describe what you want. In a few minutes, not a mockup but a fully functional application is ready to use.
I can testify to this personally. In 15 minutes, using AI, I have “written” more software than I did in a full year when I was writing software professionally. Although my old skill is now obsolete, it is wonderful because I can build faster than I ever could. This is the best of times!
So yes, in a narrow sense, the old software opportunity is dead.
The writing has been on the wall for a while. Shallow tech software has been democratized and, in many cases, is not investable. Public markets have finally figured out that a new wave of software is coming. They just do not really know what it is yet, so they sell indiscriminately. Generic business and financial skills do not work during a paradigm shift because disruption does not show up neatly on a spreadsheet full of ARR, EBITDA, and CAGR. Those are the wrong questions to ask when the underlying rules are being rewritten.
At the same time, the early phase of a paradigm shift is often the best time to invest. The people who have new specific knowledge and the courage to build for an AI native world will have a clear edge and, if they are right, capture outsized returns.
Now here is the twist.
When the cost of X collapses, the world does not get less of the thing. It gets flooded with it. That is Jevons Paradox in action. Make something cheaper and easier, and overall demand goes up significantly, often faster than the drop in price. We have seen versions of this before as humanity adopted electricity, personal computers, the internet, and now intelligence.
So software is not dead. We are about to have 10x, 100x, maybe 1000x more software than we have today.
We have seen a similar movie in content. Thanks to the internet and mobile devices, as the cost of content creation and distribution dropped, the amount of content exploded. That created giants that seized the opportunity. Fun fact, I co-founded a business two decades ago on that thesis and rode that wave myself, so yes, I have been there and done that.
Back to software.
The question now is how to capture the opportunity when the world has 1000x more software and the cost of creating software is approaching zero. Inevitably, the business model shifts because we move to a different part of the price elasticity curve when software becomes abundant. When code becomes cheap, value migrates to what stays scarce.
Shallow tech, run-of-the-mill software companies, including a lot of AI wrappers, are generally not investable from a VC perspective because they are so easy to build, copy, and replace. I have been saying this for many years, even before ChatGPT came out. If you still need more evidence, you are already behind. The button is not coming. The button is here.
This does not mean these companies cannot make money. Some will. But “can generate cash when bootstrapping” and “can return a venture fund” are not the same statement.
In contrast, deep tech software is a fantastic opportunity. There is a reason TSF shifted to deep tech investments years ago. That was not an accident. When the cost curve of intelligence collapses, businesses whose primary moat is “we can write this software” or “we spent 100 engineer years building it” need a rethink.
This is why we are unapologetically investing in deep tech.
Deep tech software is a completely different sport. In many cases, the moat is not in the software. The moat is the unique technology embedded in the software, plus the data and the system it connects to. The software is the container. The defensibility sits underneath.
People often ask how to draw the line between deep tech software and everything else. We have a definition, and it is more true than ever in this “software is abundant” era. More importantly, making that call takes specialized skill. That is why deep tech investing is reserved for trained eyes, as it requires engineering judgment, product instinct, operating experience, and recognition of a market gap that comes from building and commercializing disruptive opportunities. We can do deep tech because we are equipped to do so. Been there. Done that.
To be clear, of course, I am not suggesting the only software opportunity is deep tech. There is also a massive opportunity in bespoke software and disposable software.
For decades, companies bought off-the-shelf software because that was the only option that made economic sense, even when the software was not a perfect fit for their workflow. You ended up customizing your workflow around the software. Bespoke-built software was too expensive, too slow, and too hard to maintain.
Now the economics are changing.
We can now build software for problems that were previously too small to matter economically. We can now create personal tools designed for an audience of one. We will ship internal workflows the way we send emails. We can now generate software that lives for a week, does its job, and disappears.
That is a massive opportunity. Much of it will look like a low-tech, large-scale service business. Some of it will become platforms and infrastructure for software generation itself. Some of it will become entirely new categories we do not have names for yet. Some of it will help make deep tech software even more defensible.
But the direction is clear. Software is becoming abundant, and the economics of software will be drastically different.
So, is software dead?
Yes, software as a scarce craft is dying.
Software-as-a-moat because “we spent 100-engineer-years building it” is dying.
But software as leverage is exploding. Software as the fabric of everything is exploding. The world is not losing software. The world is getting more of it than we can possibly imagine.
Back to the movie analogy. It is like the theatre business. The movie is not the only product. The experience is the product. The popcorn is the product. The atmosphere is the product. The movie is what gets you in the door.
For most of semiconductor history, progress was a simple loop. Shrink transistors. Fit more into the same area. Get faster compute as a byproduct.
That loop had a name. Moore’s Law. It traces back to Intel co-founder Gordon Moore. He observed in the 1960s that the number of transistors on a chip, and hence its capabilities, tended to double every two years. The industry turned that observation into a roadmap. It was never guaranteed to run forever. Now shrinking is harder because we are starting to hit many limits in physics and economics, and the cost of pushing the frontier keeps rising.
So if the curve is going to keep bending upward, the industry needs new scaling vectors beyond making everything smaller in two dimensions.
This is why Two Small Fish invested in Zinite in 2021 at the company’s inception. The thesis was simple then, and it is still simple now. Scale in the third dimension, using proprietary technology protected by patents to enable true 3D chips.
Zinite stayed deliberately stealth early on, focused on building the core and protecting it properly before saying too much. Five years after we invested, we can finally talk about it more openly.
The company is led by its CEO, Dr. Gem Shoute. Fun fact. Her breakthrough was strong enough that her professors and industry veterans (who helped create fundamental IP used in all chips since 2008) joined her as co-founders, Dr. Doug Barlage and Dr. Ken Cadien.
The Distance Tax
In a recent blog post, I used a factory analogy to explain why speed, latency, and energy are often bottlenecked by movement, not necessarily arithmetic.
In short, systems don’t lose because they can’t do math. GPUs are already very good at that. Systems lose speed because they can’t feed the math with data fast enough.
In many systems, moving data costs far more than doing the arithmetic. When movement is expensive, speed and energy efficiency get worse together.
AI inference exacerbates the problem because the computational characteristics of AI inference workloads put a premium on memory behaviour. In many cases, the limiting factor is not arithmetic. It is how efficiently the system can move data. Bringing memory closer to logic matters because it directly reduces that movement.
Sensing fits in the same frame as logic and memory. Sensors generate raw data at high volume. If the system’s first step is to ship raw data far away before anything useful happens, it pays in bandwidth, latency, and power. The more intelligence that can happen closer to where data is produced, the less the system wastes just transporting information.
So the distance tax is one big problem showing up in three places at once. Logic. Memory. Sensing.
Why 3D Matters for Speed and Energy
When people hear 3D chips, they think density. More transistors per area. That matters. The bigger lever is proximity. Current 3D approaches to deliver more performance per area rely on advanced packaging, which is hindered by cost and the distance tax.
If memory can live closer to logic, the system avoids transfers that dominate both performance and power. If compute and memory can sit closer to sensing, the system avoids hauling raw streams around before doing anything intelligent.
Every avoided transfer is a double win. Speed improves because stalls go down and effective bandwidth goes up. Energy improves because fewer joules are burned moving bits instead of doing work.
That is the two birds, one stone result.
Five years after we invested, Zinite is far from just a concept. The company is doing exceptionally well, and it represents the kind of platform that can extend performance gains into the post-Moore era by reducing the distance tax, not by asking physics for more shrink, but by making data travel less.
I spent Saturday morning in Hong Kong as a speaker at the Canadian Engineering Asia Pacific Conference, a gathering that felt historic.
Not one, not two, but eight deans of Canadian engineering. In the same room, on the same program, in Asia. The conference materials called it a “historic gathering,” and that’s not an exaggeration.
Hong Kong is the perfect place for this to happen. It has a very large base of Canadian engineering alumni. You could feel it immediately. The electromagnetic pull of hundreds of iron rings in the room. A community that’s stayed connected not just to each other, but to an idea.
And despite the diversity of schools, disciplines, and career paths represented, the conference kept circling back to a single word.
Trust.
Yes, one panel was explicitly about modern engineering ethics and building trust. It was moderated by Dean Kevin Deluzio (Queen’s University) and featured Dean Heather Sheardown (McMaster University), Dean Mary Wells (University of Waterloo), and Dean Caroline Cao (University of Ottawa). What struck me was how the theme showed up everywhere else too. Education, innovation, even the informal hallway conversations. Trust wasn’t a topic. It was the subtext.
This is where Canadian engineering has something uniquely world class to contribute. Why? Because we have a cultural and professional tradition that keeps pulling us back to first principles. What we build touches people. And we take an oath to uphold high ethical standards, safety, and integrity in our professional work. That oath is not performative. It is a commitment the public can hold us to. That is trust.
This conference also marked 100 years since the Calling of an Engineer tradition began in 1925, a uniquely Canadian ritual built around that vow, to uphold high ethical standards, safety, and integrity in our professional work.
That vow is trust.
My panel focused on the future of engineering education, and it was moderated by Dean Chris Yip (University of Toronto). I had the privilege of sharing the stage with Dean Phillip Choi (University of Regina), Dean James Olsen (University of British Columbia), and Dean Viviane Yargeau (McGill University). I shared a view that we are going through a platform shift driven by AI disruption. It is a foundational change that will reshape every sector and touch every aspect of our lives, including university education, where AI can reshape how university students learn and how courses are designed.
That is why I also believe this may be the best time to become an engineer. As an early stage investor in the next frontier of computing and its applications, I get to see this shift firsthand every day. The collapsing cost of intelligence, and hence abundance, is changing what is possible, and it is creating the conditions for entirely new category defining companies.
The most moving part of the day was the re obligation ceremony, hundreds of Canadian engineers forming a human chain to renew our vows.
Standing there, I was reminded of something simple. Canada’s brand, when we earn it, is built on trustworthiness.
Trust becomes a competitive advantage for Canada. But it’s not something you declare. It’s something you practice day in and day out.
That’s what the iron ring symbolizes at its best, not nostalgia, not ceremony, but a commitment to be worthy of trust through ethics, safety, and integrity, in the work we do and the systems we leave behind.
A century in, the ring still does what it was meant to do. And right now, that feels more important than ever.
And on that note, I trust we do not have to wait another 100 years for the next one. Let’s do an Iron Ring 101 next year!
P.S. The group picture is only University of Toronto, so you can tell how big the crowd was. We have eight universities represented!
We need new architectures to meet the speed, security, and energy demands of the next frontier of computing and its applications, which is the lens I used in The Factory Analogy.
Our portfolio company Applied Brain Research (ABR) just achieved a new milestone: ABR announced the successful closure of its oversubscribed seed funding round, including investment from TSF as a lead investor, with Eva Lau joining the board.
ABR created and patented a new type of AI model, called state space models, to make AI smaller, faster, and more energy efficient than transformer models. State space models deliver real-time voice and time series intelligence without the cloud, built for privacy and efficiency. ABR’s first chip, TSP1, delivers real-time, fully on-device voice AI without the cloud. Full vocabulary speech-to-text and text-to-speech are now possible at under 30mW.
At the edge, every millisecond and every milliwatt count.
For context:
30mW is 100× less than a 3W LED lightbulb.
A data-center GPU lives in a different universe: an NVIDIA H200 NVL is up to 600W.
Now connect that to the three constraints that define the edge:
Speed: for voice and interaction, half a second is half a second too late. Cloud voice is “a terrible experience,” plagued by delays.
Security: shipping voice data to the cloud bakes in privacy risk by default — which is why we keep coming back to intelligence that stays close to the user, as Brandon argued in his post In Favour of Intelligence That Stays Put. ABR calls out “privacy concerns” as a core issue with cloud voice.
Energy: edge devices are constrained by battery life and on-device resources. ABR’s on-device voice numbers move this from “interesting” to “deployable.”
This is why ABR enables numerous new use cases that weren’t viable before in categories like AR, robotics, wearables, medical devices, and automotive.
Imagine AR glasses (or other wearables) that respond to your command in real time without draining the battery. Imagine a robot that reacts with no hesitation. Imagine a medical device that can provide insight securely, without exporting sensitive data. Imagine a car that can respond to voice commands even when the network is unreliable. These are just a few examples. The list can go on and on.
Or as Eva put it in ABR’s announcement: sophisticated voice AI doesn’t require the cloud.
The machinery on the assembly line is world-class. On paper, it can produce an enormous volume of goods per hour. And it does.
Yet, the business still misses its targets. Why? Because outcomes are rarely limited by the assembly line itself.
The supply of raw materials to the machinery and the delivery of finished products to customers play equally vital roles. Let me be a bit poetic here:
Raw materials arrive late, the line waits. Finished goods pile high.
In the end, delivery is routes and time.
And when movement is the game, the bill runs high.
Each trip costs energy, in money and time.
This is the central lesson: world-class machinery does not guarantee a high-performing, high-throughput factory.
Speed is not just how fast the machinery can produce.
Latency is the total time from order to delivery.
Energy efficiency is about the total cost of keeping the whole operation moving.
They are related, but not the same problem, and they all contribute to overall performance.
The Compute Analogy
This is a perfect analogy for modern computing. The CPU and GPU are the machinery on the assembly line. They are very good at the arithmetic that turns data into answers.
However, many modern workloads are limited by the supply chain and delivery equivalents in chips and semiconductors. Data has to travel from storage to memory, from memory to the processor, and back again. The raw materials—data—spend a surprising amount of time in transfer before they become finished products in customers’ hands: answers.
That transfer time creates a triple threat to performance:
It hurts speed because the processor stalls while waiting to be fed.
It hurts latency because the system spends time moving data before it can produce an answer, and then spends time delivering that answer to where it is needed.
It hurts energy efficiency because moving bits costs power, dissipates waste heat, and repeated transfers compound the cost.
From Graphics to AI: Changing the Bottleneck
Remember, GPU stands for Graphics Processing Unit. It was originally designed and optimized for graphics—first for gaming in the 1990s—and later for other math-heavy tasks. The bottleneck back then was arithmetic, and GPUs were the solution that gave us the most bang for the buck.
But modern workloads—AI inference in particular—have different characteristics, which makes the bottlenecks show up differently. The computational characteristics of inference put immense pressure on memory behaviour and data transfer. In many cases, the limiting factor is not just the math anymore. It is the movement and the waiting. And the delivery problem is getting bigger too.
The Rise of the “Edge” Factory
Sensors are everywhere now. They generate raw data where the action is. If every sensor stream has to be shipped to a distant “factory” (a data center) before anything useful happens, latency and bandwidth also become part of the product.
That is why edge computing is increasingly important. It is the computing version of building smaller factories closer to customers and shipping less raw material—or sometimes no raw material—across the network.
Investing in New Architectures
Of course, this does not mean CPUs or GPUs are obsolete. It means there are many other bottlenecks now. We need:
Less distance between memory and compute.
Less shuttling of data inside the system.
Less distance between sensing and decision.
The Von Neumann architecture used by many modern computers today is about 80 years old. The first CPU is more than half a century old. The first GPU is almost 30 years old. It is time for new architectures.
This is a core part of our investment thesis in the next frontier of computing and its applications, specifically in Advanced Computing Hardware, one of the five areas we invest in. For many years, we have made investments in semiconductor companies, including Zinite, Hepzibah, ABR, and Blumind, that, through architectural innovation, address performance bottlenecks across speed, latency, and energy efficiency in ways faster GPUs alone will not solve.
We are super excited about this massive opportunity and are looking for new investments. If you are a deep tech researcher or founder in this area, please reach out to us at pitch@twosmallfish.vc.
I spent a full day at Ontario Tech University in Oshawa a few weeks ago. It was my first time on campus, despite it being just over a 40-minute drive from Toronto, where I live. I arrived curious and left with a clearer picture of what they’re building.
Ontario Tech is still a relatively young university, just over two decades old. What’s less well known—and something I didn’t fully appreciate before the visit—is how quickly it has grown in that time, now serving around 14,000 students, and how deliberately it has established itself as a research university rather than simply a teaching-focused institution.
That research orientation shows up not just in output, but in where the university has chosen to build depth—areas that sit close to real systems and real constraints.
This came through clearly in conversations with Prof. Peter Lewis, Canada Research Chair in Trustworthy Artificial Intelligence, whose work focuses on trustworthy and ethical AI. The university has launched Canada’s first School of Ethical AI, alongside the Mindful AI Research Institute, and the work here is grounded in how AI systems behave once deployed—how humans interact with them, and how unintended consequences are identified and managed.
Energy is another area where Ontario Tech has built serious capability. The university is home to Canada’s only accredited undergraduate Nuclear Engineering program, which is ranked third in North America and designated as an IAEA Collaborating Centre. In discussions with Prof. Hossam Gaber, the emphasis was on smart energy systems, where software, sensing, and control systems are developed alongside the physical energy infrastructure they operate within.
I also spent time with Prof. Haoxiang Lang, whose work in robotics, automotive systems, and advanced mobility sits at the intersection of computation and the physical world.
That work is closely tied to the Automotive Centre of Excellence, which includes a climatic wind tunnel described as one of the largest and most sophisticated of its kind in the world. The facility enables full-scale testing under extreme environmental conditions—from arctic cold to desert heat—and supports research that needs to be validated under real operating constraints.
I can’t possibly mention all the conversations I had over the course of the day—it was a full schedule—but I also spent time with Dean Hossam Kishawy and Dr. Osman Hamid, discussing how research, entrepreneurship, and industry engagement fit together at Ontario Tech.
The day also included time at Brilliant Catalyst, the university’s innovation hub, speaking with students and founders about entrepreneurship. I had the opportunity to give a keynote on entrepreneurship, and the visit ended with the pitch competition, where I handed the cheque to the winning team—a small moment that underscored how early many technical journeys begin.
Ontario Tech may be young, but it is already operating with the structure and discipline of a mature research institution, while retaining the adaptability of a newer one.
Thank you to Sunny Chen and the Ontario Tech team for the time, access, and thoughtful conversations throughout the day.
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This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
I wrote my master’s thesis on Code Division Multiple Access, or CDMA, a wireless communication technology that originated from military needs in World War II. CDMA uses a technique called direct sequence spread spectrum, which spreads a signal across a wide bandwidth so that it appears as random noise. This made it far better at encryption, resisting jamming, and avoiding eavesdropping. Needless to say, it was perfect for military environments long before it found its way into everyday communication.
A startup company called Qualcomm was beginning to commercialize CDMA. I spent countless hours studying their technical papers, which demonstrated how a technology with military grade robustness could also be applied to large scale commercial mobile networks. Working on that thesis in the 90s was also the first time I encountered the idea of dual use, the concept of a technology that can be used in both military and civilian environments, and one that has existed since the post–World War II era.
Geopolitics Has Recentered Dual Use
Fast forward to today. Geopolitics has returned to the foreground. Defence budgets around the world are rising. Countries are rethinking supply chains and rediscovering the importance of technological sovereignty. The focus is no longer only on wartime capability but also on the resilience of civilian systems that society relies on every day.
In this environment, dual use has moved from the background to the forefront of national strategy. In the AI era we are in, governments everywhere are looking for new technologies that strengthen national security and economic competitiveness at the same time. Technologies that once seemed far removed from defence are now recognized as essential.
A Tailwind for Deep Tech
For Two Small Fish Ventures, none of this comes as a surprise. Deep tech has always lived at the intersection of what is scientifically hard and what is societally important. Today, it naturally lends itself to dual use.
Breakthroughs in the five areas that TSF invests in — vertical AI platforms, physical AI, AI infrastructure, advanced computing hardware, and smart energy — were never designed to be solely military. Yet many of these technologies have clear applications in resilience, cybersecurity, automation, sensing, communication, and energy stability.
In other words, dual use does not narrow a company’s mission. It broadens it. It is the rare case where one innovation can truly kill two birds with one stone.
Defence Technology Is Not Only About Weapons
There is a common misconception that defence technology refers only to weapons. That has never been true.
Most technologies are neutral. I am certain our national defence department uses Microsoft Office, for instance. This is a reminder that much of what defence departments buy is not lethal but operational.
To be clear, we do not invest in companies whose sole purpose is military lethal weapons systems.
Our focus remains on building companies in the areas where we believe the next frontier of computing is taking shape. When those technologies also support national resilience, that is not mission drift. It is simply the nature of deep tech.
Deep tech requires scientific and engineering breakthroughs that are difficult to copy. In a dual use environment, this becomes an essential advantage.
A New Frontier for Founders
Founders often think of defence as a separate world. That is changing. Defence is a complicated beast, and anyone who believes they can simply walk in will be disappointed. But for those who understand the landscape and can navigate it, this is a generational opportunity waiting to be captured.
When I first studied CDMA decades ago, I never imagined that a communication technique developed for the battlefield would become the backbone of commercial wireless networks.
Today, many deep tech founders are standing at a similar moment. For founders and investors in deep tech, this is the beginning of an important cycle. And we are excited to support the innovators who will define what comes next.
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This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
In October, at our Two Small Fish Ventures AGM, I had the chance to sit down with Benjamin Bergen for a fireside chat. At the time, he was still leading the Council of Canadian Innovators. None of us knew he would soon become the new CEO of the CVCA. Looking back, the timing could not have been better.
I have known Benjamin for many years. When I was CEO of Wattpad, I worked closely with him through CCI, which played an important role in advocating for Canadian scaleups. That experience gave me a front row view of how policy, talent mobility, capital, and global markets intersect. I did not expect that perspective to become even more useful on the investor side, but today it is proving to be exactly that.
At Two Small Fish, our portfolio founders often hear us talk about our full cycle view of company building. We have built companies, operated them at global scale, navigated regulatory and geopolitical realities, and now invest across deep tech. We have seen the journey from the very first product decision all the way to commercialization. That experience matters today because geopolitics is no longer something happening far away. It is showing up directly in the work of founders.
The World Has Changed Irreversibly
Founders do not necessarily always think about politics, especially geopolitics. I certainly did not in my early days as a founder. But over the past year, the global environment has shifted in ways that affect talent, capital, customers, supply chains, and data. These forces are becoming part of the operating conditions for every innovative company.
At the AGM, Benjamin and I spent time unpacking what this new reality looks like.
Talent We spoke about the growing brain drain and how global mobility is changing. The tightening of the H1B program in the United States has created a ripple effect across the entire talent ecosystem. Early stage companies are rethinking where they build teams, and immigration policy is becoming a strategic consideration rather than an afterthought.
Capital The rise of protectionism and shifting global alliances are affecting how and where capital can move. The changing dynamics among the United States, China, and Canada raise new questions for both founders and investors. Some are beginning to view geographic diversification as a practical response to political uncertainty.
Customers National preference policies such as Buy Canadian and Buy American are becoming more common. These policies may begin as political statements, but they influence real procurement and partnership decisions. For founders, gaining early customers is no longer just about product and timing. There is a political dimension that needs to be understood.
Infrastructure and Defense We also talked about how export controls and security requirements are expanding. Technologies that once seemed purely commercial are now viewed through a strategic lens. Even young companies are discovering that they may be operating in areas that governments consider sensitive.
Supply Chains Global supply chains have shown their fragility in areas such as semiconductors, rare earth materials, and energy. These vulnerabilities create friction but also open new opportunities for companies building more resilient and regional alternatives.
Data Sovereignty Data localization and national data governance rules continue to spread. More countries want their data stored and processed within their borders. For companies operating internationally, this introduces new architectural and operational decisions much earlier in the journey.
Benjamin also shared how CCI’s new advisory group, Signa Strategies, is helping founders navigate exactly these types of challenges. It felt like a natural evolution of the work he has been doing for years.
As our conversation wrapped up, I was reminded how valuable it is to have seen this ecosystem from both sides. As a founder, I saw how talent, markets, and policy could quietly redirect a company’s path. Through CCI, I saw how national priorities and regulation shape the environment innovators work in. These experiences feel especially relevant now. The geopolitical questions that once appeared at the edges are moving closer to the center.
This is the environment founders are building in today. And with our full cycle experience, we hope to help them navigate it with clarity, context, and confidence.
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This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
At the beginning of this year, I wrote an op-ed for The Globe about what many were already calling the AI bubble. Nearly a year later, almost all of what I said remains true. The piece was always meant to be a largely evergreen, long term view rather than a knee jerk reaction.
The only difference today is that the forces I described back then have only intensified.
We are in a market where Big Tech, venture capital, private equity, and the public markets are all pouring unprecedented capital into AI. But to understand what is actually happening, and how to invest intelligently, we need to separate noise from fundamentals. Here are the five key points:
Why Big Tech Is Going All In while Taking Minimal Risk.
The Demand Side Is Real and Growing.
Not All AI Investments Are Created Equal.
Picking Winners Matters.
Remember, Dot Com Was a Bubble. The Internet Was Not.
1. Why Big Tech Is Going All In while Taking Minimal Risk
The motivations of the large technology companies driving this wave are very different from those of startups and other investors.
For Big Tech, AI is existential. If they underinvest, they risk becoming the next Blockbuster. If they overinvest, they can afford the losses. In practice, they are buying trillions of dollars worth of call options, and very few players in the world can afford to do that.
The asymmetry is obvious. If I were their CEOs, I would do the same.
But being able to absorb risk does not mean they want to absorb all of it. This is why they are using creative financing structures to shift risk off their balance sheets while remaining all in. At the same time, they strengthen their ecosystems by keeping developers, enterprises, and consumers firmly inside their platforms.
This is not classical corporate investing. Their objective is not just profitability. It is long term dominance.
For everyone outside Big Tech, meaning most of us, understanding these incentives is essential. It helps you place your bets intelligently without becoming roadkill when Big Tech transfers risk into the ecosystem.
2. The Demand Side Is Real
AI usage is not slowing. It is accelerating.
The numbers do not lie. Almost every metric, including model inference, GPU utilization, developer adoption, enterprise pilot activity, and startup formation, is rising. You can validate this across numerous public datasets. Directionally, people are using AI more, not less. And unlike previous hype cycles, this wave has real usage, real dollars, and real infrastructure behind it.
Yes, there is froth. But there are also fundamentals.
3. Not All AI Investments Are Created Equal
A common mistake is treating AI investing as a single category.
It is not.
Investing in a public market, commoditized AI business is very different from investing in a frontier technology startup with a decade long horizon. The former may come with thin margins, weak moats, and hidden exposure to Big Tech’s risk shifting. The latter is where transformational returns come from if you know how to evaluate whether a company is truly world class, differentiated, and defensible.
Lumping all AI investments together is as nonsensical as treating all public stocks as the same.
4. Picking Winners Matters
In public markets, you can buy the S&P 500 and call it a day. But that index is not random. Someone selected those 500 winners for you.
In venture, picking winners matters even more. It is a power law business. Spray and pray does not work. Most startups will not survive, and only the strongest will break out, especially in an environment as competitive as today.
Thanks to AI, we are in the middle of a massive platform shift. Venture scale outcomes depend on understanding technology deeply enough to see a decade ahead and identify breakout successes before others do. Long term vision beats short term noise. Daily or quarterly fluctuations are simply noise to be ignored.
5. Dot Com Was a Bubble. The Internet Was Not.
The dot com era had dramatic overvaluation and a painful crash, but the underlying technology still reshaped the world. The problem was not the internet. It was timing, lack of infrastructure, and indiscriminate investing in ideas that were either too early or simply bad.
Looking back, the early internet lacked essential components such as high speed access, mobile connectivity, smartphones, and internet payments. Although some elements of the AI stack may still be evolving, many of the major building blocks, including commercialization, are already in place. AI does not suffer from the same foundational gaps the early internet did.
Calling this a bubble as a blanket statement misses the nuance. AI itself is not a bubble. With a decade long view, it is already reshaping almost every industry at an unprecedented pace. Corrections, consolidations, and failures are normal. The underlying technological shift is as real as the internet was in the 1990s.
There is speculation. There are frothy areas. And yet, there are many areas that are underfunded. That is where the opportunities are.
⸻
History shows that great venture funds invest through cycles. They invest in areas that will be transformative in the next decade, not the next quarter.
For us, the five areas we focus on, including Vertical AI platforms, physical AI, AI infrastructure, advanced computing hardware, and smart energy, are the critical elements of AI. Beyond being our expertise, there is another important reason why these categories matter: Bubble or not, they will thrive.
We are not investing in hype, nor in capital intensive businesses where capital is the only moat, nor in companies where technology defensibility is low. As long as we stay disciplined and visionary, and continue to back founders building a decade ahead, we will do well, bubble or not.
After all, there may be multiple macro cycles across a decade. Embrace the bubble.
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This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
I had the opportunity to join a panel at the Impact 2025 Summit in Calgary, moderated by Raissa Espiritu, with Janet Bannister and Paul Godman. Ironically, none of us are labelled as impact investors, and I explained on stage why Two Small Fish Ventures does what we do.
At Two Small Fish Ventures, we’ve never called ourselves an impact fund. That’s not because we’re indifferent to impact; in fact, it’s core to what we do. Our focus is on deep tech, the next frontier of computing, where innovation can create meaningful, long-term change. Specifically, we invest in five key areas: Vertical AI Platforms, Physical AI, AI Infrastructure, Advanced Computing Hardware, and Smart Energy.
We care deeply about scientific advancement, and more importantly, about turning those breakthroughs into real-world impact. That’s how meaningful progress happens.
Eva is our General Partner, and both of us are immigrants. Diversity isn’t a marketing point for us; it’s part of who we are. It naturally shows up in our portfolio: about half of our companies have at least one female founder, and many come from underrepresented backgrounds. That said, uncompromisingly, we back amazing deep tech founders who are turning their creations into world-class companies.
It’s actually rare that we talk about topics like women investing or investing in underrepresented groups in isolation. Not because we don’t care, quite the opposite. The fact that Eva is one of the few female GPs leading a venture fund, and that we’re both immigrants, already says a lot. Our actions speak volumes. We walk the walk and talk the talk.
We need to deliver results. Period. Our competition isn’t other venture funds; it’s every other investment opportunity available in the market. If we can’t perform at the highest level — top decile in everything we do — we can’t sustain our mission. Delivering some of the best results in the industry enables us to do what we love and make an impact.
That’s why I believe impact and performance are not opposites. The most powerful kind of impact happens when companies succeed, when they become world-class companies. Strong returns and meaningful impact can, and should, reinforce each other.
I also talked about the importance of choosing the right vehicle for the right purpose. When we made a 2 million dollar donation to the University of Toronto to establish the Commercialization Catalyst Prize, it wasn’t about investing. It was about supporting a different kind of impact — helping scientists and engineers turn their research into innovations that can reach the world. Not every kind of impact should come from the same tool.
At the end of the day, labels matter less than intent and execution. We don’t need to call ourselves an impact fund to make a difference. Our goal is simple: to back bold deep tech founders using science and technology to build a better future and to do it with excellence.
A big thank you to Raissa, George Damian, Sylvia Wang, and the entire Platform Calgary team for putting together such a thoughtful and well-run event.
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This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
On Friday, October 17, 2025, Chancellor Kathleen Taylor at York University conferred on Eva Lau the degree of Doctor of Laws, honoris causa.
I purposely avoided hearing her practice so I could experience it on stage for the first time, just like everyone else in the audience.
It turned out to be the right call. By taking the risk of not previewing it, I gained an asymmetrical upside! Ironically, these are the lessons she shared. Frankly, I wish someone had told me these lessons when I was in my twenties.
Please read her remark when you have a moment:
********
Dean Zwick, faculty, honoured guests, proud families, and—most importantly—the graduating class of 2025: thank you. It is a profound honour to stand before you today.
First, I want to thank the school for recognizing my work in entrepreneurship and innovation and granting me this extraordinary honour.
I also want to thank my mom and my late father, whose leap of faith to immigrate to Canada opened the doors for me and my sister to build our lives here.
To my daughters—you’ve been my biggest motivators. You are the reason I push forward, because I want you to know your potential is uncapped. You can chart your own paths and build your own successes.
And to my husband, Allen: thank you for your love, support, and affirmations. You mean the world to me, and you make me a better person every day.
And to the graduating class—congratulations! Today is a celebration of your hard work, your determination, and your costly Red Bull habits. It is my greatest joy to share a few words with you. Since we are all business school graduates, let’s get straight to business. I want to share with you a strategy—a framework, at least for me—on how to calculate risk, how to execute with an edge, and how to maximize the upside, to a point that it can be transformational. That’s right, I am putting our education to work here. No group project required!
Lesson 1: Embrace Risk—But Know Your Bottom Line
In school, we learned about Risk Management in Finance. Identify the risks. Quantify them. Mitigate them. Protect value. Very neat, very rational.
But in life, risk doesn’t come with a spreadsheet. In life, managing risk means asking: how much am I truly willing to lose? Unless you define that, you can never truly take a risk.
When people read about the success of Wattpad, the story can look deceptively simple. We built the product. Users loved it. The product went viral. And ta-da! It became one of the most iconic internet platforms in the world, serving over 100 million users worldwide, sharing over 1 million new stories in 50 languages every day. We even have TV and movie products around the world. When the company was acquired in 2021, it was one of the most significant tech exits in Canadian history.
But the “ta-da” moment was actually years of sweat, doubt, and very small numbers. At the start in 2006, Wattpad didn’t just have few users—we had so few that our total ad revenue was…two dollars. Not two million. Not two thousand. Not twenty. Just two. And Allen and Ivan, the two cofounders, had to split it. I think one bought a coffee… the other just got the receipt.
Our family’s finances? Let’s just say “tough” doesn’t quite capture it. We were running low on savings and even had to leverage our house to keep everything going. Allen and I had many long kitchen-table talks. In the end, we decided we were willing to risk everything—even selling the house—if that’s what it took. But we drew a firm line: we were willing to go down to zero, but we were not willing to go into the negatives.
That’s what embracing risk looks like for an entrepreneur. It’s not about avoiding loss. It’s about defining your boundaries and then giving it everything you’ve got. Try your hardest to stay clear of the bottom line.
And when mobile computing took off with the launch of iphones and android devices, all that persistence paid off. Wattpad became the world’s number one story-sharing app on all app stores.
We took the same approach when exploring new frontiers at Wattpad—first with AI, then with entertainment. In 2012—long before “ChatGPT” became a household name—we became one of the first companies to deploy AI at scale on a commercial platform. It was a bold move, and yes, a risky one. Then in 2016, we leapt into film and TV production—an entirely different world for us. Both were high-stakes bets, but because we had clearly defined what we were willing to invest and what we were prepared to lose, we could take those risks with confidence.
So my first lesson: embrace risk. Define your bottom line so you can move forward without fear. Knowing your worst-case scenario gives you the freedom to take that leap of faith. In your case, living in your parents’ basement could be the worst-case scenario. But hey, you already know them well enough. I think you will survive.
Lesson 2: Leverage Your Uniqueness
Once you’ve defined your risk boundaries, the next step is execution. And here’s the secret: the best execution comes from knowing what makes us unique and leaning into it.
When I began my journey as a venture capitalist a decade ago, I knew I couldn’t just be another investor. What set me apart was lived experience: I had scaled a product from a few thousand users to tens of millions. I understood the fear, the pivots, and the sleepless nights—not from theory, but firsthand.
Before Wattpad, I worked in a semiconductor company, managing a product line that was competing with a startup at the time, called Nvidia. AMD later acquired the company for US$ 4 billion. That experience gave me the technical and operational lenses very few investors had.
And then there were my learnings from some of the best investors in the world—people who backed Twitter, Coinbase, Google, and even OpenAI. I had the opportunity to learn directly from them since they were also Wattpad investors.
All of that shaped my unique edge as a venture capitalist at Two Small Fish. With a distinct investment thesis, we became one of the few deep-tech investors in Canada, backing founders tackling hard technology problems with novel innovations. Today, I’m proud to say Two Small Fish is not only among the top-performing VC funds globally, but also a firm that founders love working with—because we do things differently.
That’s the second lesson: know our uniqueness and use it. Don’t downplay it. Don’t hide it. It’s our superpower.
Lesson 3: Chase Asymmetrical Upside
The third lesson is about aiming high. Really high. Chase the Asymmetrical Upside.
Entrepreneurship and innovation are not about making something just 10-20% better. They are about creating something 100 times, 1000 times better. Something transformational.
If you only focus on small, incremental gains, you might survive—but you won’t thrive when the next wave of disruption comes. But if you go after opportunities with asymmetrical upside—where the potential payoff is massive compared to the risk—you position yourself for breakthroughs.
Take Wattpad again. If we had only wanted to build a small reading app for a niche audience, that would have been fine. But by dreaming bigger—by imagining an AI-powered global entertainment company—the outcome was transformational.
And this applies to your careers too. You won’t change industries—or the world—by playing it safe. You have to reach for opportunities that feel a little terrifying, a little out of your league.
I like to remind young entrepreneurs: I have never seen a basketball player aim for the bottom of the net. They always aim above it. That’s how slam dunks happen.
So my third lesson: don’t settle for small steps. Chase the opportunities that stretch you, the ones that scare you, the ones that could redefine everything.
So, Class of 2025, to sum these up, I encourage you to:
Embrace risk. Define your boundaries. Know how much you’re willing to lose, and let that clarity free you.
Leverage your uniqueness. Don’t try to be a knockoff of someone else. Your unique mix of experiences, skills, and quirks is your competitive edge.
Chase asymmetrical upside. Don’t aim for incremental change. Aim for the slam dunk.
Your journey will not be a straight line. There will be pauses, setbacks, and zigzags. But each twist is part of the story that prepares you for the next leap forward.
So step into your future with courage. Take the risk! The world doesn’t need another safe bet—it needs bold leaders, innovative thinkers, and dreamers who are willing to take the shot.
Congratulations once again, Class of 2025. The future is yours—go and dunk it.
The Laus have some exciting news to share. We are making a $2 million donation to the University of Toronto, our alma mater, to launch the Eva and Allen Lau Commercialization Catalyst Prize for Computing & Engineering Innovation.
And the best part: U of T’s Faculty of Arts & Science and Faculty of Applied Science & Engineering will match our gift, doubling its impact. This partnership will give even more researchers the resources they need to take their inventions and turn them into impactful companies.
Why This Matters
Canada is full of world class talent. At U of T alone, researchers are pushing the boundaries of semiconductors, AI, robotics, and quantum technologies—fields that will shape the future. The brilliance is already here.
But getting from invention to an impactful company is not easy. What is often missing are the resources that help move ideas out of the lab: mentorship, funding, workspace, and access to prototyping labs. That is where this prize comes in.
Each year, one team from Arts and Science and one from Engineering will receive support to bridge that critical gap and bring their boldest ideas closer to reality.
Why Catalyst
We named this prize Catalyst for a reason. Commercialization does not happen in isolation. It takes a community of mentors, peers, industry partners, and funders to transform research into companies that scale.
Our hope is that the Catalyst Prize sparks more than just a few startups. We want it to inspire others to join in, to create the conditions where many more homegrown tech giants can start, grow, and scale right here in Canada.
U of T
The University of Toronto is already a leader in innovation and entrepreneurship. It is home to one of the world’s top university incubators, has helped launch more than 1,200 venture backed startups, and is ranked among the top ten universities worldwide for powering innovation .
Add to that U of T’s research depth, industry partnerships, and global alumni network, and you have a powerful engine for turning big ideas into global impact. We are thrilled to help fuel that engine.
Coming Full Circle
For us, this is also personal. U of T gave us our start, Allen in electrical engineering and Eva in industrial engineering, and laid the foundation for everything that followed. From building Wattpad to starting Two Small Fish Ventures, we have lived the journey from idea to scale.
Now, through the Catalyst Prize, and with U of T matching to double the impact, we want to give today’s researchers and students even more opportunities than we had.
Innovation is unpredictable and the path is seldom linear. But with the right support at the right time, sparks can turn into something extraordinary.
That is what the Catalyst Prize is all about, helping Canadian innovators move their ideas out of the lab and into the world.
When I was studying electrical engineering, out of my curiosity, I chose to take an elective course on quantum physics as part of advanced optics. It sparked my curiosity in quantum. The strange, abstract, counterintuitive rules, for example particles existing in multiple states or being entangled across distance, captivated me.
Error correction, closely related to fault tolerance in quantum systems today, is the backbone of telecommunications, one of the areas I majored in.
Little did I know these domains would converge in such a way that my earlier academic training would become relevant again years later.
For me, computing is not just my profession, it is also my hobby. As a science nerd, I actively enjoy following advances, and I keep going deeper down the rabbit hole of the next frontier of computing. That mix of personal curiosity and professional focus shapes how I approach both the opportunities and risks in the space. Over the past few years, I have gone deeper into the world of quantum. My academic and professional background gave me the footing to evaluate both what is technically possible and what is commercially viable.
From If to How and When
In June, I wrote Quantum Isn’t Next. It’s Now. We have passed the tipping point where the question is no longer if quantum technology will work, it is how and when it will scale.
This momentum is not just visible to those of us deep in the field. As the Globe and Mail recently reported, we at Two Small Fish have been following quantum for years, but did not think it was mature enough for an early-stage fund with a 10-year lifespan to back. This year, we changed our minds. As I shared in that article: “It’s much more investible now.”
The distinction is clear: when quantum was still a science problem, the central question was whether it could work at all. Now that it has become an engineering problem, the questions are how it will work at scale and when it will be ready for commercialization.
This shift matters for investors. Venture capital focuses on engineering breakthroughs, hard, uncertain, but achievable on a commercialization timeline. Fundamental science, which can take many more years to mature, is better supported by governments, universities, and non-dilutive funding sources. I will leave that discussion for another post.
One of Five Frontiers
At Two Small Fish Ventures, we have identified five areas shaping the next frontier of computing. Quantum falls under the area of advanced computing hardware, where the convergence of different areas of science, engineering, and commercialization is accelerating.
Each of these areas is no longer a speculative science experiment but a rapidly advancing field where engineering and commercialization are converging. Within the next ten years, the winners will emerge from lab prototypes and become scaled companies. Quantum is firmly on that trajectory.
How We Invest in Quantum
Our first principle at Two Small Fish is straightforward: we only invest in things we truly understand, from all three technology, product, and commercialization lenses. That discipline forces us to dig deep before committing capital. And after years of study, it is clear to us that quantum has moved into investable territory, but only selectively.
Not every quantum startup fits a venture time horizon. Some promising projects will take too many years to scale. But we are now seeing opportunities that, within a 10-year window, can realistically grow from an early-stage idea to a successful scale-up. That is the standard we apply to every investment, and quantum finally has companies that meet it.
From Sci-Fi to Reality
Canada has played an outsized role in building the foundation of quantum science. Now, it has the chance to lead in quantum commercialization. The next few years will determine which teams turn breakthrough science into enduring companies.
For investors, this is both an opportunity and a responsibility. The quantum era is not a distant possibility, it is here now. What once sounded like science fiction is now an investable reality. And for those willing to put in the work to understand it, the frontier is already here.
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This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Last year we invested in Axiomatic AI. Their mission is to bring verifiable and trustworthy AI into science and engineering, enabling innovation in areas where rigour and reliability are essential. At the core of this is Mission 10×30: achieving a tenfold improvement in scientific and engineering productivity by 2030.
The company was founded by top researchers and professors from MIT, the University of Toronto, and ICFO in Barcelona, bringing deep expertise in physics, computer science, and engineering.
Since our investment, the team has been heads down executing. Now they’ve shared their first public release: Axiomatic Operators.
What They’ve Released
Axiomatic Operators are MCP servers that run directly in your IDE, connecting with systems like Claude Code and Cursor. The suite includes:
AxEquationExplorer
AxModelFitter
AxPhotonicsPreview
AxDocumentParser
AxPlotToData
AxDocumentAnnotator
Why is this important?
Large Language Models (LLMs) excel at languages (as their name suggests) but struggle with logic. That’s why AI can write poetry but often has trouble with math — LLMs mainly rely on pattern matching rather than reasoning.
This is where Axiomatic steps in. Their approach combines advances in reinforcement learning, LLMs, and world models to create AI that is not just fluent but also capable of reasoning with the rigour required in science and engineering.
What’s Next
This first release marks an important step in turning their mission into practical, usable tools. In the coming weeks, the team will share more technical material — including white papers, demo videos, GitHub repositories, and case studies — while continuing to work closely with early access partners.
Find out more on GitHub, including demos, case studies, and everything else you need to make your work days less annoying and more productive: Axiomatic AI GitHub
We’re excited to see their progress. If you’re in science or engineering, we encourage you to give the Axiomatic Operators suite a try: Axiomatic AI.
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This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
In 1865, William Stanley Jevons, an English economist, observed a curious phenomenon: as steam engines in Britain became more efficient, coal use didn’t fall — it rose. Efficiency lowered the cost of using coal, which made it more attractive, and demand surged.
That insight became known as Jevons Paradox. To put it simply:
Technological change increases efficiency or productivity.
Efficiency gains lead to lower consumer prices for goods or services.
The reduced price creates a substantial increase in quantity demanded (because demand is highly elastic).
Instead of shrinking resource use, efficiency often accelerates it — and with it, broader societal change.
Coal, Then Light
The paradox first appeared in coal: better engines, more coal consumed. Electricity followed a similar path. Consider lighting in Britain:
Period
True price of lighting (per million lumen-hours, £2000)
Change vs. start
Per-capita consumption (thousand lumen-hours)
Change vs. start
Total consumption (billion lumen-hours)
Change vs. start
1800
£8,000
—
1.1
—
18
—
1900
£250
↓ ~30×
255
↑ ~230×
10,500
↑ ~500×
2000
£2.5
↓ ~3,000× (vs. 1800) / ↓ ~100× (vs. 1900)
13,000
↑ ~13,000× (vs. 1800) / ↑ ~50× (vs. 1900)
775,000
↑ ~40,000× (vs. 1800) / ↑ ~74× (vs. 1900)
Over two centuries, the price of light fell 3,000×, while per-capita use rose 13,000× and total consumption rose 40,000×. A textbook case of Jevons Paradox — efficiency driving demand to entirely new levels.
Computing: From Millions to Pennies
This pattern carried into computing:
Year
Cost per Gigaflop
Notes
1984
$18.7 million (~$46M today)
Early supercomputing era
2000
$640 (~$956 today)
Mainstream affordability
2017
$0.03
Virtually free compute
That’s a 99.99%+ decline. What once required national budgets is now in your pocket.
Storage mirrored the same story: by 2018, 8 TB of hard drive storage cost under $200 — about $0.019 per GB, compared to thousands per GB in the mid-20th century.
Connectivity: Falling Costs, Rising Traffic
Connectivity followed suit:
Year
Typical Speed & Cost per Mbps (U.S.)
Global Internet Traffic
2000
Dial-up / early DSL (<1 Mbps); ~$1,200
~84 PB/month
2010
~5 Mbps broadband; ~$25
~20,000 PB/month
2023
100–940 Mbps common; ↓ ~60% since 2015 (real terms)
>150,000 PB/month
(PB = petabytes)
As costs collapsed, demand exploded. Streaming, cloud services, social apps, mobile collaboration, IoT — all became possible because bandwidth was no longer scarce.
Intelligence: The New Frontier
Now the same dynamic is unfolding with intelligence:
Year
Cost per Million Tokens
Notes
2021
~$60
Early GPT-3 / GPT-4 era
2023
~$0.40–$0.60
GPT-3.5 scale models
2024
< $0.10
GPT-4o and peers
That’s a two-order-of-magnitude drop in just a few years. Unsurprisingly, demand is surging — AI copilots in workflows, large-scale analytics in enterprises, and everyday generative tools for individuals.
As we highlighted in our TSF Thesis 3.0, cheap intelligence doesn’t just optimize existing tasks. It reshapes behaviour at scale.
Why It Matters
The recurring pattern is clear:
Coal efficiency fueled the Industrial Revolution.
Affordable lighting built electrified cities.
Cheap compute and storage enabled the digital economy.
Low-cost bandwidth drove streaming and cloud collaboration.
Now cheap intelligence is reshaping how we live, work, and innovate.
As we highlighted in Thesis 3.0:
“Reflecting on the internet era… as ‘the cost of connectivity’ steadily declined, productivity and demand surged—creating a virtuous cycle of opportunities. The AI era shows remarkable parallels. AI is the first technology capable of learning, reasoning, creativity… Like connectivity in the internet era, ‘the cost of intelligence’ is now rapidly declining, while the value derived continues to surge, driving even greater demand.”
The lesson is simple: efficiency doesn’t just save costs — it reorders economies and societies. And that’s exactly what is happening now.
If you are building a deep tech early-stage startup in the next frontier of computing, we would like to hear from you. This is a generational opportunity as both traditional businesses and entirely new sectors are being reshaped. White-collar jobs and businesses, in particular, will not be the same. We would love to hear from you.
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This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
One of the most powerful frameworks I’ve come across is the Rule of 3 and 10, coined by Hiroshi Mikitani-san, founder and CEO of Rakuten. The idea is simple: every time a company triples in size, everything breaks.
As Rakuten grew from a handful of people into a global business, Mikitani-san noticed a clear pattern. At each stage — 1 to 3 people, 3 to 10, 10 to 30, 30 to 100, 100 to 300, and beyond — what worked before suddenly stopped working. And by everything, it really does mean everything: payroll, meetings, communication, budgeting, sales, even the org chart. The challenge is that many leaders blow right through these milestones without realizing what’s happening until it’s already broken.
What I Wish I Knew
I’ve been part of many really fast-growing companies — first as an employee, and later as a co-founder in two of them. And I can tell you, this rule is 100% true.
At Wattpad, I didn’t fully internalize it until we were approaching 100 people. By then, we had already missed natural breaking points where we could have rebuilt earlier. That lag made scaling harder than it needed to be.
Looking back, the stages feel something like this:
At 3 people, you’re a tight-knit unit where everyone knows everything.
At 10, you need to change how you communicate just to stay aligned.
At 30, the days of everyone reporting to the CEO are long gone — a first layer of leaders emerges.
At 100, there are layers of layers of leaders, and even well-designed systems need rethinking.
At 300, you’re running a completely different company than the one you started.
At 1,000, it feels like a mini-society with its own subcultures, bureaucracy, and politics — alignment becomes the hardest problem of all.
The Employee’s View
Before becoming an entrepreneur, I lived through this as an employee too. The breaking points are just as visible from the inside.
As companies scale, it gets harder to push things through. Meetings multiply, but decisions slow. Bystander problems appear — more people in the room, but fewer actually taking ownership. From the employee’s perspective, it feels frustrating and inefficient. But it’s not about capability; it’s about systems that no longer fit the size of the company.
Why This Matters
In the moment, it can feel like failure. But it isn’t. It’s simply that scale changes everything.
The good news: these challenges are solvable. Every growing company has faced them. The bad news: if you only react after things break, you’ll always be catching up instead of leading.
My Takeaway
If you’re building a fast-growing company, expect everything to break at 3, 10, 30, 100, 300, 1,000… and plan for it.
Don’t see it as failure. See it as evolution. Each breakdown is proof you’ve unlocked a new stage of growth. The chaos is part of the privilege — it means you’re building something worth scaling.
If I could go back and tell my younger CEO self one thing, it would be this: anticipate the breaks before they happen. Build a culture that embraces reinvention at every stage. You’ll save yourself and your team a lot of unnecessary pain — and you’ll enjoy the ride more.
P.S. The banner is using Ideogram Character to generate. It rocks!
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For nearly 70 years, the home electrical panel has looked the same. Meanwhile, the home itself is transforming: solar on the roof, batteries in the garage, heat pumps, EVs in the driveway, and smart appliances and devices everywhere.
And yet, the panel? Still the same. It is the last dumb box left, and FUTURi is fixing that with deep tech.
FUTURi’s Energy Processor
FUTURi Power, founded by Dr. Martin Ordonez (UBC Professor, Kaiser Chair at UBC, and recipient of the King Charles III Coronation Medal for leadership in clean energy innovation), reimagines the panel as the Energy Processor, a programmable energy computer that finally gives the home’s electrical system a brain. It is designed as a like-for-like replacement for the traditional panel that is future-proof and intelligently measures and coordinates loads, avoids peaks, and manages energy use at the edge.
Why This Matters
Homes are no longer passive energy consumers. They are dynamic nodes in the grid. By making the panel intelligent, FUTURi enables:
For homeowners: Achieve a 100% electric home without costly service upgrades. A smarter, more resilient, and efficient energy ecosystem.
For utilities: Demand peaks flattened, demand response (DR) programs and distributed energy resources (DERs) integrated, deferring costly capital expenditures.
For builders and communities: Intelligent electrification helps accelerate the deployment of built infrastructure without overloading the grid.
This is why FUTURi and utilities are already collaborating on projects to evaluate how Energy Processors can strengthen the grid and benefit customers.
Our Perspective
As Dr. Martin Ordonez, Founder and CEO of FUTURi Power, puts it: “Panels used to be passive. The Energy Processor is active, safe, and software-defined. It gives homes and grids a common language.” At TSF, Smart Energy is one of our five focus areas. Our thesis is simple: the cost of intelligence is collapsing, and the biggest opportunities lie where software and hardware come together to reshape behaviour.
FUTURi is exactly that blueprint for intelligent electrification: deep-tech power electronics plus intelligent control. That combination turns a 70-year-old box into the brain of the modern home. Dr. Ordonez and his team are globally recognized experts in electrification who are translating decades of pioneering research into transformative commercial solutions.
And this is just the beginning. There is so much more the company can do to make electricity truly intelligent. FUTURi has a bright future ahead (pun fully intended).
The cost of intelligence is dropping at an unprecedented rate. Just as the drop in the cost of computing unlocked the PC era and the drop in the cost of connectivity enabled the internet era, falling costs today are driving explosive demand for AI adoption. That demand creates opportunity on the supply side too, in the infrastructure, energy, and technologies needed to support and scale this shift.
In our Thesis 3.0, we highlighted how this AI-driven platform shift will reshape behaviour at massive scale. But identifying the how also means knowing where to look.
Every era of technology has a set of areas where breakthroughs cluster, where infrastructure, capital, and talent converge to create the conditions for outsized returns. For the age of intelligent systems, we see five such areas, each distinct but deeply interconnected.
1. Vertical AI Platforms
After large language models, the next wave of value creation will come from Vertical AI Platforms that combine proprietary data, hard-to-replicate models, and orchestration layers designed for complex and large-scale needs.
Built on unique datasets, workflows, and algorithms that are difficult to imitate, these platforms create proprietary intelligence layers that are increasingly agentic. They can actively make decisions, initiate actions, and shape workflows. This makes them both defensible and transformative, even when part of the foundation rests on commodity models.
This shift from passive tools to active participants marks a profound change in how entire sectors operate.
2. Physical AI
The past two decades of digital transformation mostly played out behind screens. The next era brings AI into the physical world.
Physical AI spans autonomous devices, robotics, and AI-powered equipment that can perceive, act, and adapt in real environments. From warehouse automation to industrial robotics to autonomous mobility, this is where algorithms leave the lab and step into society.
We are still early in this curve. Just as industrial machinery transformed factories in the nineteenth century, Physical AI will reshape industries that rely on labour-intensive, precision-demanding, or hazardous work.
The companies that succeed will combine world-class AI models with robust hardware integration and build the trust that humans place in systems operating alongside them every day.
3. AI Infrastructure
Every transformative technology wave has required new infrastructure that is robust, reliable, and efficient. For AI, this means going beyond raw compute to ensure systems that are secure, safe, and trustworthy at scale.
We need security, safety, efficiency, and trustworthiness as first-class priorities. That means building the tools, frameworks, and protocols that make AI more energy efficient, explainable, and interoperable.
The infrastructure layer determines not only who can build AI, but who can trust it. And trust is ultimately what drives adoption.
4. Advanced Computing Hardware
Every computing revolution has been powered by a revolution in hardware. Just as the transistor enabled mainframes and the microprocessor ushered in personal computing, the next era will be defined by breakthroughs in semiconductors and specialized architectures.
From custom chips to new communication fabrics, hardware is what makes new classes of AI and computation possible, both in the cloud and on the edge. But it is not only about raw compute power. The winners will also tackle energy efficiency, latency, and connectivity, areas that become bottlenecks as models scale.
As Moore’s Law hits its limit, we are entering an age of architectural innovation with neuromorphic computing, photonics, quantum computing, and other advances. Much like the steam engine once unlocked new industries, these architectures will redefine what is computationally possible. This is deep tech meeting industrial adoption, and those who can scale it will capture immense value.
5. Smart Energy
Every technological leap has demanded a new energy paradigm. The electrification era was powered by the grid. Today, AI and computing are demanding unprecedented amounts of energy, and the grid as it exists cannot sustain this future.
This is why smart energy is not peripheral, but central. From new energy sources to intelligent distribution networks, the way we generate, store, and allocate energy is being reimagined. The idea of programmable energy, where supply and demand adapt dynamically using AI, will become as fundamental to the AI era as packet switching was to the internet.
Here, deep engineering meets societal need. Without resilient and efficient energy, AI progress stalls. With it, the future scales.
Shaping What Comes Next
The drop in the cost of intelligence is driving demand at a scale we have never seen before. That demand creates opportunity on the supply side too, in the platforms, hardware, energy, physical systems, and infrastructure that make this future possible.
The five areas — Vertical AI Platforms, Physical AI, AI Infrastructure, Advanced Computing Hardware, and Smart Energy — represent the biggest opportunities of this era. They are not isolated. They form an interconnected landscape where advances in one accelerate breakthroughs in the others.
We are domain experts in these five areas. The TSF team brings technical, product and commercialization expertise that helps founders build and scale in precisely these spaces. We are uniquely qualified to do so.
At Two Small Fish, this is the canvas for the next generation of 100x companies. We are excited to partner with the founders building in these areas globally, those who not only see the future, but are already shaping it.
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A few years back, Eva met Dr. Scott Stornetta. Later, I did too. Alongside Dr. Stuart Haber, Scott is widely credited as the creator of blockchain. Blockchain is a technology built on a simple but radical idea at the time: decentralization. No single authority, no central point of control, just a trusted system everyone can rely on.
Now, these two scientists are teaming up again to start a new company, SureMark Digital. Their mission is to bring that same decentralized philosophy to identity and authenticity on the internet, enabling anyone to prove who they are, certify their work, and push back against deepfakes and impersonation. No middlemen. No central gatekeepers.
It took us about 3.141592654 seconds to get excited. We are now proud to be the co-lead investor in SureMark’s first institutional round.
At Two Small Fish, we love backing frontier tech that can reshape large-scale behaviour. SureMark checks every box.
Eva has written a deeper dive on what they are building and why it matters. You can read it here.
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At most dinners, introductions start with your name and maybe what you do.
At this one, we began with: “Second edition.” “Fourth edition.”
Why? Because this was our “School of Fish – Legends of Semiconductors” dinner, hosted at our home, where your relationship with the Sedra & Smith textbook was the common thread. (I’m second edition, if you’re wondering.)
We were incredibly honoured to have Dr. Adel Sedra, former Dean of Engineering at the University of Waterloo, join us. Recently appointed to the Order of Canada, Dr. Sedra is a towering figure in the world of electrical engineering. Since 1982, his textbook has taught more than three-quarters of the world’s electrical engineers. It is hard to find someone in the field who has not studied from it. I consider myself extraordinarily fortunate, not just to have learned from his book, but to have been his student more than 30 years ago at the University of Toronto. Few have had the privilege of learning directly from a legend.
We were equally honoured to host Benny Lau, co-founder of ATI Technologies, whose legacy lives on in AMD’s GPUs to this day. AMD acquired ATI for $5.4 billion nearly 20 years ago, still one of the largest tech acquisitions in Canadian history. When Eva worked at ATI, she had the chance to work closely with Benny. His presence brought our conversation full circle, from classroom to commercialization. Adding even more depth to the evening, Benny was also once a student of Dr. Sedra. Two generations of engineers at the same table, both shaped by the same teacher.
From left to right: Benny Lau, Eva Lau, Ljubisa Bajic
This evening was also a chance to reconnect with those who shaped my own journey. Martin Snelgrove and Raymond Chik, my professor and TA respectively, were both there and are now serial entrepreneurs. They are also co-founders of Hepzibah, a Two Small Fish portfolio company. (I still can’t help but sometimes call him Professor Snelgrove.) Xerxes Wania, another one of my TAs from back in the day, went on to build and exit two semiconductor companies and added his voice to the conversation.
From left to right: Xerxes Wania, Dr. Adel Sedra, Allen Lau, Martin Snelgrove, Raymond Chik
We were also joined by Ljubisa Bajic, former CEO of TensTorrent and now CEO of Taalas, who also spent part of his career at ATI, further adding to the thread that connected many of us. Chris Yip, Dean of Engineering at the University of Toronto, and Deepa Kundur, current Chair of U of T’s Department of Electrical & Computer Engineering—continuing the legacy of leadership that Dr. Sedra once held in that position—also attended. Professor Tony Chan Carusone, now also CTO of Alphawave Semi and coauthor of the Sedra & Smith textbook starting with the 8th edition, brought both academic and commercial perspectives to the table.
From the TSF portfolio side, we were thrilled to have Professor Doug Barlage of the University of Alberta and Professor Chris Eliasmith of the University of Waterloo, co-founders of Zinite and ABR, respectively.
And of course, our partner Dr. Albert Chen joined us. He is a graduate of Waterloo Engineering and knows a thing or two about semiconductors himself.
Semiconductors brought us together that night. Textbook and tapeout were what we talked about, and we all loved them.
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A swimming world champion, a cycling champion, and a marathon champion each tried their hand at a triathlon.
None of them even came close to the podium. All were easily defeated.
Why?
Because the swimming champion could not bike, nor could he run fast.
The cycling champion did not swim well.
The marathon runner was painfully slow in the water.
The winner?
It was someone who had been humbled by the swimming champion in the pool for years, finishing second in the world championships multiple times. He was an exceptional swimmer, yes. However, he could also bike fast and run hard. Not the best in any single discipline, but strong across all three. And that is what won him the race.
The takeaway:
To win in triathlon, you need to be competitive in all three disciplines.
The winner is often world class in one of them, but they must be very good if not great at the other two.
This is the same mistake many first time deep tech founders make.
They believe that superior technology alone is enough to win.
It is not.
While technology is crucial, and in fact it is table stakes and the foundation of innovation, it must be transformed into a usable product. If it does not solve a real problem in a way people can adopt and benefit from, its brilliance is wasted.
And even if you have built world class technology and a beautifully crafted product, you are still not done. Without effective commercialization, which includes distribution, pricing, sales, positioning, and partnerships, you will not reach the users or customers who need what you have built.
Neglecting any one of them is like trying to win a triathlon without training for the bike or the run.
Just like a triathlete must train in all three disciplines, a founder must excel across all three pillars:
Great and defensible technology
An excellent product
Execution on commercialization
You need all three.
That is how you win the world championship.
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In the history of human civilization, there have been several distinct ages: the Agricultural Age, the Industrial Age, and the Information Age, which we are living in now.
Within each age, there are different eras, each marked by a drastic drop in the cost of a fundamental “atomic unit.” These cost collapses triggered enormous increases in demand and reshaped society by changing human behaviour at scale.
From the late 1970s to the 1990s, the invention of the personal computer drastically reduced the cost of computing [1]. A typical CPU in the early 1980s cost hundreds of dollars and ran at just a few MHz. By the 1990s, processors were orders of magnitude faster for roughly the same price, unlocking entirely new possibilities like spreadsheets and graphical user interfaces (GUIs).
Then, from the mid-1990s to the 2010s, came the next wave: the Internet. It brought a dramatic drop in the cost of connectivity [2]. Bandwidth, once prohibitively expensive, fell by several orders of magnitude — from over $1,200 per Mbps per month in the ’90s to less than a penny today. This enabled browsers, smartphones, social networks, e-commerce, and much of the modern digital economy.
From the mid-2010s to today, we’ve entered the era of AI. This wave has rapidly reduced the cost of intelligence [3]. Just two years ago, generating a million tokens using large language models cost over $100. Today, it’s under $1. This massive drop has enabled applications like facial recognition in photo apps, (mostly) self-driving cars, and — most notably — ChatGPT.
These three eras share more than just timing. They follow a strikingly similar pattern:
First, each era is defined by a core capability, i.e. computing, connectivity, and intelligence respectively.
Second, each unfolds in two waves:
The initial wave brings a seemingly obvious application (though often only apparent in hindsight), such as spreadsheets, browsers, or facial recognition.
Then, typically a decade or so later, a magical invention emerges — one that radically expands access and shifts behaviour at scale. Think GUI (so we no longer needed to use a command line), the iPhone (leapfrogging flip phones), and now, ChatGPT.
Why does this pattern matter?
Because the second-wave inventions are the ones that lower the barrier to entry, democratize access, and reshape large-scale behaviour. The first wave opens the door; the second wave throws it wide open. It’s the amplifier that delivers exponential adoption.
We’ve seen this movie before. Twice already, over the past 50 years.
The cost of computing dropped, and it transformed business, productivity, and software.
Then the cost of connectivity dropped, and it revolutionized how people communicate, consume, and buy.
Now the cost of intelligence is collapsing, and the effects are unfolding even faster.
Each wave builds on the last. The Internet era was evolving faster than the PC era because the former leveraged the latter’s computing infrastructure. AI is moving even faster because it sits atop both computing and the Internet. Acceleration is not happening in isolation. It’s compounding.
If it feels like the pace of change is increasing, it’s because it is.
Just look at the numbers:
Windows took over 2 years to reach 1 million users.
Facebook got there in 10 months.
ChatGPT did it in 5 days.
These aren’t just vanity metrics — they reflect the power of each era’s cost collapse to accelerate mainstream adoption.
That’s why it’s no surprise — in fact, it’s crystal clear — that the current AI platform shift is more massive than any previous technological shift. It will create massive new economic value, shift wealth away from many incumbents, and open up extraordinary investment opportunities.
That’s why the succinct version of our thesis is:
We invest in the next frontier of computing and its applications, reshaping large-scale behaviour, driven by the collapsing cost of intelligence and defensible through tech and data moats.
The race is already on. We can’t wait to invest in the next great thing in this new era of intelligence.
Super exciting times ahead indeed.
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Footnotes
[1] Cost of Computing
In 1981, the Intel 8088 CPU (used in the first IBM PC) had a clock speed of 4.77 MHz and cost ~$125. By 1995, the Intel Pentium processor ran at 100+ MHz and cost around $250 — a ~20x speed gain at similar cost. Today’s chips are thousands of times faster, and on a per-operation basis, exponentially cheaper.
[2] Cost of Connectivity
In 1998, bandwidth cost over $1,200 per Mbps/month. By 2015, that figure dropped below $1. As of 2024, cloud bandwidth pricing can be less than $0.01 per GB — a near 100,000x drop over 25 years.
[3] Cost of Intelligence
In 2022, generating 1 million tokens via OpenAI’s GPT-3.5 could cost $100+. In 2024, it costs under $1 using GPT-4o or Claude 3.5, with faster performance and higher accuracy — a 100x+ reduction in under two years.
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In the early 2000s, it was a common joke in the tech world that “next year is the year of the smartphones.” People kept saying it over and over for almost a decade. It became a punchline. The industry nearly lost its credibility.
Until the iPhone launched. “Next year is the year of the smartphones” finally became true.
The same joke has followed quantum for the past ten years: next year is the year of quantum.
Except it hasn’t been. Not yet.
And yet, quietly, the foundations have been built. We’re not there, but we’re far from where we started.
We’re getting closer. Much closer. I can smell it. I can hear it. I can sense it.
Right now, without getting into too much technical detail, we’re still at a small scale: fewer than 100 usable qubits. Commercial viability likely requires thousands, if not millions. The systems are still too error-prone, and hosting your own quantum machine is wildly impractical. They’re expensive, fragile, and noisy.
At this stage, quantum is mostly limited to niche or small-scale applications. But step by step, quantum is inching closer to broader utility.
And while these things don’t progress in straight lines, the momentum is real and accelerating.
Large-scale, commercially deployable, fault-tolerant quantum computers accessed through the cloud are no longer science fiction. They’re within reach.
I spent a few of my academic years in signal processing and error correction. I’ve also spent a bit of time studying quantum mechanics. I understand the challenges of cloud-based access to quantum systems, and I’ve been following the field for quite a while, mostly as a curious science nerd.
All of that gives me reason to trust my sixth sense. Quantum is increasingly becoming a reality.
Nobody knows exactly when the iPhone moment or the ChatGPT moment of quantum will happen. But I’m absolutely sure we won’t still be saying “next year is the year of quantum” a decade from now.
It will happen, and it will happen much sooner than you might think.
This is an exciting time and the ideal time to take a closer look at quantum, because the best opportunities tend to emerge right before the technology takes off.
How can we not get excited about new quantum investment opportunities?
P.S. I’m excited to attend the QUANTUM NOW conference this week in Montreal. Also thrilled to see Mark Carney name quantum as one of Canada’s official G7 priorities. That short statement may end up being a big milestone.
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Yet the ocean remains surprisingly underdeveloped — in fact, it’s the least developed.
Land transportation has been electrified. In space, payload costs have dropped drastically. Now, it’s time for marine to catch up.
Unlike cars, you can’t simply add an electric motor and battery to a boat and make it work. Why? One reason is that water’s viscosity is much higher than air, meaning drag or resistance is an order of magnitude greater. As a result, replacing a gas motor with an electric one would require a gigantic battery, making it impractical and, frankly, unusable. That’s why marine electrification has lagged.
Until now.
The “iPhone moment” of marine transportation has arrived. ENVGO’s hydrofoiling NV1 tackles these multidisciplinary complications head-on. Led by successful serial entrepreneur Mike Peasgood, the team brings together expertise in AI, robotics, control systems, computer vision, autonomous systems, and more. Leveraging their prior success as drone pioneers at Aeryon, they are now building a flying robot — on water.
It’s day one of a large-scale transformation of marine transportation. Two Small Fish is privileged and super excited to lead this round of funding, alongside our good friends at Garage, who are also participating. We can’t wait to see how ENVGO reimagines the uncharted waters — pun fully intended.
Read our official blog post by our partner Albert here.
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When entrepreneurs exit their companies, it is supposed to be a victory lap. But in reality, many find themselves in an unexpected emotional vacuum. More often than you might think, I hear variations of the same quiet confession:
“It should have been the best time of my life. But I felt lost after the exit. I lost my purpose.”
After running Wattpad for 15 years, I understand this all too well. It is like training for and running a marathon for over a decade, only to stop cold the day after the finish line. No more rhythm. No more momentum. No next mile.
Do I Miss Operating
Unsurprisingly, people often ask me:
“Do you like being a VC?”
“Do you miss operating?”
My honest answer is yes and yes
(but I get my fix without being a CEO — see below).
Being a founder and CEO was deeply challenging and also immensely rewarding. It is a role that demands a decade-long commitment to building one and only one thing. And while I loved my time as CEO, I did not feel the need to do it again. Once in a lifetime was enough. I have started three companies. A fourth would have felt repetitive.
What I missed most was not the title or the responsibility. It was the people. The team. The day-to-day collaboration with nearly 300 passionate employees when I stepped down. That sense of shared mission — of solving hard problems together — was what truly filled my cup.
Let’s be honest: they call me especially when they believe I am the only one who can help them. Their words, not mine. And there have been plenty of those occasions.
That gives me the same hit of adrenaline I used to get from operating. At my core, I love solving hard problems. That part of me did not go away after my exit. I just found a new arena for it — and it is a perfect replacement.
A Playground for a Science Nerd
What people may not realize is that the deep tech VC job is drastically different from a “normal” VC job. As a deep tech VC, I am constantly stretched and go deep — technically, intellectually, and creatively. It forces me to stay sharp, push my boundaries, and reconnect with my roots as a curious, wide-eyed science nerd.
There is something magical about working with founders at the bleeding edge of innovation. I get to dive into breakthrough technologies, understand how they work, and figure out how to turn them into usable and scalable products. It feels like being a kid in a candy store — except the candy is semiconductors, control systems, power electronics, quantum, and other domains in the next frontier of computing.
How could I not love that?
Ironically, I had less time to indulge this curiosity when I was a CEO. Now I can geek out and help shape the future at the same time. It is a net positive to me.
You Do Not Have to Love It All
Of course, every job — including CEO and VC — has its less glamorous parts. Whether you are a founder or a VC, there will always be administrative tasks and responsibilities you would rather skip.
But I have learned not to resent them. As I often say:
“You do not need to love every task. You just need to be curious enough to find the interesting angles in anything.”
Those tasks are the cost of admission to being a deep tech VC. A small price to pay to do the work I love — supporting incredible entrepreneurs as they bring transformative ideas to life, and finding joy in doing so. And knowing what I know now, I do not think I would enjoy being a “normal” VC. I cannot speak for others, but for me, this is the only kind of venture work that truly energizes and fulfills me.
A New Season. A New Purpose.
So yes, being a VC brings me as much joy — and arguably even more fulfillment (and I am surprised that I am saying this) — than being a CEO. I feel incredibly lucky. And I am all in.
It feels like all my past experience has prepared me for what I do today. I often describe this phase of my life this way:
Wattpad was my regular season. TSF is my playoff hockey.
It is faster. It is grittier. The stakes feel higher. Not because I am building one company, but because I am helping many shape the future.
That’s 10 years, 120 months, and 3,653 days (yes, we counted the leap years). What started as a bold experiment in early-stage investing has become a decade-long journey of backing audacious founders building at the edge of what’s possible.
Over the weekend, we wired funds for our 60th first investment. That’s not including the many follow-on cheques we’ve written along the way—if we counted those, the number would be much higher. We’re not naming the company just yet, but like the 59 before it, this one reflects deep conviction. We think it’ll make a splash!
For years, we’ve said we write 5 to 7 new cheques per year. Not because we aim for a quota, but because this is what a power-law portfolio construction strategy naturally produces. In venture, just a few outlier companies drive the vast majority of returns. The trick is to consistently back companies with 100x potential. That’s the focus—not pacing. And yet, the numbers tell their own story: we’ve averaged exactly six new investments a year. Apparently, clarity of focus brings consistency as a byproduct.
We’re now six months into our tenth year, and we’re right on pace.
To the founders we’ve backed: thank you for trusting us at the earliest, riskiest stage.
To those we haven’t met yet: if you’re building deep tech in the next frontier of computing, we’d love to hear from you. We invest globally. If you’ve got a breakthrough, we can help turn it into a product. If you’ve got a product, we can help turn it into a company.
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I recently spent a few weeks in Asia, visiting Tokyo, Hong Kong, Singapore, and Taiwan before returning to Toronto. Eva joined me for the first part of the journey, while I spent time in Singapore on my own, a city I’ve visited numerous times before. In Taiwan, I was accompanied by Albert, who was born there and still has family ties in the region.
This was by far my longest trip in quite some time. These destinations represent some of the world’s most developed economies, with GDP per capita levels comparable to or exceeding those in North America. Singapore, for instance, has a per capita GDP of around 90,000 USD, roughly 50 percent higher than the United States’ 66,000 USD.
Conversations and Perspectives
Coincidentally, my visit aligned with Liberation Day. Needless to say, it sparked many fascinating conversations, including the so-called “penguin tariffs,” whether AI is already smarter than certain politicians, and everything in between. Around that time, I also came across a perspective that stood out. While tariffs were initially expected to threaten Asian economies, many locals believed they had ended up affecting the United States more. Businesses in the Asia Pacific region had begun diversifying away from reliance on the US market years ago. As a result, they now have more leverage, and the direct impact of tariffs has been relatively limited. The broader concern was the possibility of a global recession.
Tech Energy in the Region
Across all four regions, I witnessed growing momentum in tech entrepreneurship. I had the chance to speak at tech conferences, lead masterclasses, take part in fireside chats, and encourage high school students to consider entrepreneurship as a path worth exploring.
Why It’s Happening
Why is this happening? These regions have strong technical capabilities. Taiwan, for example, manufactures about 90 percent of the world’s most advanced chips, and its capabilities are unmatched by any other country. Singapore, on the other hand, excels in semiconductor fabrication and biotechnology, and its presence in AI and computing infrastructure continues to grow.
Understanding the Cultural Landscape
At the same time, the cultural differences between East and West remain clear. The East tends to emphasize social harmony, collective behaviour, and conformity. The West often puts more weight on individual expression and free spirit.
Even small things reflect these differences. Take jaywalking. In Tokyo and Singapore, it is rare. People stare at you if you do it. In contrast, after jaywalking was recently legalized in New York City, I actually felt social pressure to jaywalk. Not doing so made me feel out of place.
Why Culture Matters in Business
For companies working across borders, recognizing these kinds of cultural nuances is not optional. It is essential. A one-size-fits-all approach often leads to missteps.
The Bicultural Perspective
Having been raised in Asia and now living in Canada for decades, I’ve come to appreciate the value of navigating both worlds. That dual perspective has become a quiet but important asset in both my personal and professional life. It is not a liability.
As I often say:
“Bamboo is neutral. If it’s used as a ceiling, it becomes a barrier. But if it’s used as a pole for jumping, one can leap incredibly high. Biculturalism is a powerful asset. If you leverage it in the right context, it can become your unfair advantage.”
Biculturalism, when used with intention, becomes a meaningful advantage. It helps you understand nuance, communicate across different environments, and approach global opportunities with more adaptability.
Looking Ahead
In an increasingly interconnected world, going global is no longer just a choice. During Asian Heritage Month, this feels especially relevant. Let’s celebrate not only our roots but also the advantages that come from navigating multiple worlds.
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Driven by rapid advances in AI, the collapse in the cost of intelligence has arrived—bringing massive disruption and generational opportunities.
Building on this platform shift, TSF invests in the next frontier of computing and its applications, backing early-stage products, platforms, and protocols that reshape large-scale behaviour and unlock uncapped, new value through democratization. These opportunities are fueled by the collapsing cost of intelligence and, as a result, the growing demand for access to intelligence as well as its expansion beyond traditional computing devices. What makes them defensible are technology moats and, where fitting, strong data network effects.
Ormore succinctly: We invest in the next frontier of computing and its applications, reshaping large-scale behaviour, driven by the collapsing cost of intelligence and defensible through tech and data moats.
Watch this 2-minute video to learn more about our approach:
Our Evolution: From Network Effects to Deep Tech
When we launched TSF in 2015, our initial thesis centred around network effects. Drawing from our experience scaling Wattpad from inception to 100 million users, we became experts in understanding and leveraging exponential value and defensibility created by network effects at scale. This expertise led us to invest—most as the very first cheque—in massively successful companies such as BenchSci, Ada, Printify, and SkipTheDishes.
We achieved world-class success with this thesis, but like all good things, that opportunity diminished over time.
Our thesis evolved as the ground shifted toward the end of 2010s. A couple of years ago, we articulated this evolution by focusing on early-stage products, platforms, and protocols that transform user behaviour and empower businesses and individuals to unlock new value. Within this broad focus, we zoomed in specifically on three sectors: AI, decentralized protocols, and semiconductors. That thesis guided investments in great companies such as Story, Ideogram, Zinite, and Blumind.
But the world doesn’t stand still. In fact, it has never changed so rapidly. This brings us to the next and even more significant shift shaping our thesis.
A New Platform Shift: The Cost of Intelligence is Collapsing
Reflecting on the internet era, the core lesson we learned was that the internet was the first technology in human history that was borderless, connected, ubiquitous, real-time, and free. At its foundation was connectivity, and as “the cost of connectivity” steadily declined, productivity and demand surged, creating a virtuous cycle of opportunities.
The AI era shows remarkable parallels. AI is the first technology capable of learning, reasoning, creativity, cross-domain functionality, and decision-making. Like connectivity in the internet era, “the cost of intelligence” is now rapidly declining, while the value derived from intelligence continues to surge, driving even greater demand.
This shift will create massive economic value, shifting wealth away from many incumbents and opening substantial investment opportunities. However, just like previous platform shifts, the greatest opportunities won’t come from digitizing or automating legacy workflows, but rather from completely reshaping workflows and user behaviour, democratizing access, and unlocking previously impossible value. These disruptive opportunities will expand into adjacent areas, leaving incumbents defenceless as the rules of the game fundamentally change.
Intelligence Beyond Traditional Computing Devices
AI’s influence now extends far beyond pre-programmed software on computing devices. Machines and hardware are becoming intelligent, leveraging collective learning to adapt in real-time, with minimal predefined instruction. As we’ve stated before, software alone once ate the world; now, software and hardware together consume the universe. The intersection of software and hardware is where many of the greatest opportunities lie.
As AI models shrink and hardware improves, complex tasks run locally and effectively at the edge. Your phone and other edge devices are rapidly becoming the new data centres, opening exciting new possibilities.
Democratization and a New Lens on Defensibility
The collapse in the cost of intelligence has democratized everything—including software development—further accelerated by open-source tools. While this democratization unlocks vast opportunities, competition also intensifies. It may be a land grab, but not all opportunities are created equal. The key is knowing which “land” to seize.
Historically, infrastructure initially attracts significant capital, as seen in the early internet boom. Over time, however, much of the economic value tends to shift from infrastructure to applications. Today, the AI infrastructure layer is becoming increasingly commoditized, while the application layer is heavily democratized. That said, there are still plenty of opportunities to be found in both layers—many of them truly transformative. So, where do we find defensible, high-value opportunities?
Our previous thesis identified transformative technologies that achieved mass adoption, changed behaviour, democratized access, and unlocked unprecedented value. This framework remains true and continues to guide our evaluation of “100x” opportunities.
This shift in defensibility brings us to where the next moat lies.
New Defensibility: Deep Tech Meets Data Network Effects
Defensibility has changed significantly. In recent years, the pool of highly defensible early-stage shallow tech opportunities has thinned considerably, with far fewer compelling opportunities available. As a result, we have clearly entered a golden age of deep tech. AI democratization provides capital-efficient access to tools that previously required massive budgets. Our sweet spot is identifying opportunities that remain difficult to build, ensuring they are not easily replicated.
As “full-spectrum specialists,” TSF is uniquely positioned for this new reality. All four TSF partners are engineers and former startup leaders before becoming investors, with hands-on experience spanning artificial intelligence, semiconductors, robotics, photonics, smart energy, blockchain and others. We are not just technical; we are also product people, having built and commercialized cutting-edge innovations ourselves. As a guiding principle, we only invest when our deep domain expertise can help startups scale effectively and rapidly cement their place as future industry-disrupting giants.
Moreover, while traditional network effects have diminished, AI has reinvigorated network effects, making them more potent in new ways. Combining deep tech defensibility with strong data-driven network effects is the new holy grail, and this is precisely our expertise.
What We Don’t Invest In
Although we primarily invest in “bits,” we will also invest in “bits and atoms,” but we won’t invest in “atoms only.” We also have a strong bias towards permissionless innovations, so we usually stay away from highly regulated or bureaucratic verticals with high inertia. Additionally, since one of our guiding principles is to invest only when we have domain expertise in the next frontier of computing, we won’t invest in companies whose core IP falls outside of our computing expertise. We also avoid regional companies, as we focus on backing founders who design for global scale from day one. We invest globally, and almost all our breakout successes such as Printify have users and customers around the world.
Where We’re Heading
Having recalibrated our thesis for this new era, here’s where we’re going next.
We have backed amazing deep tech founders pioneering AI, semiconductors, robotics, photonics, smart energy, and blockchain—companies like Fibra, Blumind, ABR, Axiomatic, Hepzibah, Story, Poppy, and Viggle—across consumer, enterprise, and industrial sectors. With the AI platform shift underway, many new and exciting investment opportunities have emerged.
The ground has shifted: the old playbook is out, the new playbook is in. It’s challenging, exciting, and we wouldn’t have it any other way.
To recap our core belief, TSF invests in the next frontier of computing and its applications, backing early-stage products, platforms, and protocols that reshape large-scale behaviour and unlock uncapped, new value through democratization. These opportunities are fueled by the collapsing cost of intelligence and, as a result, the growing demand for access to intelligence as well as its expansion beyond traditional computing devices. What makes them defensible are technology moats and, where fitting, strong data network effects.
Ormore succinctly: We invest in the next frontier of computing and its applications, reshaping large-scale behaviour, driven by the collapsing cost of intelligence and defensible through tech and data moats.
So, if you’ve built interesting deep tech in the next frontier of computing, we invest globally and can help you turn it into a product. If you have a product, we can help you turn it into a massively successful business. If this sounds like you, reach out.
P.S. If you enjoyed this blog post, please take a minute to like, comment, subscribe and share. Thank you for reading!
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
A solo musician doesn’t need a conductor. Neither does a jazz trio.
But an orchestra? That’s a different story. You need a conductor to coordinate, to make sure all the parts come together.
Same with AI agents. One or two can operate fine on their own. But in a multi-agent setup, the real bottleneck is orchestration.
Yesterday, we announced our investment in GenseeAI. That’s the layer the company is building—the conductor for AI agents, i.e. the missing intelligent optimization layer for AI agents and workflows. Their first product, Cognify, takes AI workflows built with frameworks like LangChain or DSPy and intelligently rewrites them to be 10× faster, cheaper, and more reliable. It’s a bit like “compilation” for AI. Given a high-level workflow, Cognify produces a tuned, executable version optimized for production. Their second product, currently under development, goes one step further: a serving layer that continuously optimizes AI agents and workflows at runtime. Think of it as an intelligent “virtual machine” for AI, where the execution of agents and workflows is transparently and “automagically” improved while running.
If you’re building AI systems and want to go from prototype to production with confidence, get in touch with the GenseeAI team.
Read Brandon‘s blog post here or in the following for all the details:
At Two Small Fish, we invest in founders building foundational infrastructure for the AI-native world. We believe one of the most important – yet underdeveloped – layers of this stack is orchestration: how generative AI workflows are built, optimized, and deployed at scale.
Today, building a production-grade genAI app involves far more than calling an LLM. Developers must coordinate multiple steps – prompt chains, tool integrations, memory, RAG, agents – across a fragmented and fast-moving ecosystem and a variety of models. Optimizing this complexity for quality, speed, and cost is often a manual, lengthy process that businesses must navigate before a demo can become a product.
GenseeAI is building the missing optimization layer for AI agents and workflows in an intelligent way. Their first product, Cognify, takes AI workflows built with frameworks like LangChain or DSPy and intelligently rewrites them to be faster, cheaper, and better. It’s a bit like “compilation” for AI: given a high-level workflow, Cognify produces a tuned, executable version optimized for production.
Their second product–currently under development–goes one step further: a serving layer that continuously optimizes AI agents and workflows at runtime. Think of it as an intelligent “virtual machine” for AI: where the execution of agents and workflows is transparently and automatically improved while running.
We believe GenseeAI is a critical unlock for AI’s next phase. Much of today’s genAI development is stuck in prototype purgatory – great demos that fall apart in the real world due to cost overruns, latency, and poor reliability. Gensee helps teams move from “it works” to “it works well, and at scale.”
What drew us to Gensee was not just the elegance of the idea, but the clarity and depth of its execution. The company is led by Yiying Zhang, a UC San Diego professor with a strong track record in systems infrastructure research, and Shengqi Zhu, an engineering leader who has built and scaled AI systems at Google. Together, they bring a rare blend of academic rigor and hands-on experience in deploying large-scale infrastructure. In early benchmarks, Cognify delivered up to 10× cost reductions and 2× quality improvements – all automatically. Their roadmap – including fully automated optimization, enterprise integrations, and a registry of reusable “optimization tricks” – shows ambition to become the default runtime for generative AI.
As the AI stack matures, we believe Gensee will become a foundational layer for organizations deploying intelligent systems. It’s the kind of infrastructure that quietly powers the AI apps we’ll all use – and we’re proud to support them on that journey. If you’re building AI systems and want to go from prototype to production with confidence, get in touch with the team at GenseeAI.
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Yesterday was Star Wars Day — aka “May the Fourth be with you” — and it got me thinking, so I put together this blog post.
You might notice my title is “Operating Partner,” not “General Partner,” “Managing Partner,” or “Board Partner.” That’s intentional because I spend most of my time working directly with portfolio CEOs.
The Operating Partner role has its roots in private equity. Historically, Operating Partners are often former CEOs or COOs who use their experience to guide leadership teams, improve operational execution, and drive results, ultimately increasing the value of portfolio companies.
As far as I know, I’m the only former scale-up CEO in Canada who plays this role in an early-stage VC. At least, ChatGPT and Perplexity couldn’t find anyone else! Even in the U.S., this is very rare.
That said, I’ve always felt the “Operating Partner” title is a bit misleading. Unlike many private equity Operating Partners, I don’t step into full-time or part-time leadership roles within portfolio companies. I don’t give advice or directives either. Instead, I help CEOs solve their own problems rather than solving problems for them.
My single objective is to help portfolio CEOs improve the quality of their decisions by leveraging my experience.
Why? Most CEOs don’t need to be told what to do—they already know. Telling a CEO to grow their KPIs faster or hire great people is useless.
No CEO intentionally grows slower or hires bad people!
The real challenge for CEOs isn’t the what—it’s the how. This is where I come in, helping them navigate the how: strategic thinking, future-proofing, and decision-making that drive tangible progress, while staying alert to blind spots that could undermine success.
Hiring is an example. Many venture firms have talent partners who assist portfolio companies with recruitment. These partners, often from recruitment backgrounds, are excellent at sourcing candidates once roles are defined. However, they usually lack deep business context and may not fully understand the culture of the companies they’re supporting. This can result in untargeted candidates who don’t fit. I experienced this issue firsthand when I was a CEO.
That’s why I strongly favour internal recruiters who have an intimate understanding of the business and culture. Even so, recruiters typically get involved after roles are clearly defined. Before that, to design the organization, we need someone who has visibility into the broader perspective of the business. Only one person truly has it: the CEO. Besides, CEOS usually can’t ask their leaders about organizational design for obvious reasons.
That’s where I step in—well before recruiters are involved. I act as a sounding board for organizational design, considering not just immediate hiring needs but also how roles and teams will evolve over time. What level of talent should they hire now? When will this position need to level up? What downstream implications will these decisions have?
By addressing these questions early, I help ensure hiring decisions are aligned with the company’s long-term strategy and culture.
Of course, hiring is just one area where I provide support. Design future-proof stock option plans? Manage internal and external communication challenges? Interact with strategic conglomerates? Navigate inbound acquisition offers? Resolve leadership dysfunction? Handle unreasonable investors? Make board meetings more effective? Fend off super aggressive competitors or internet giants?
And yes, one of the most frequent requests I get is: “Can you help me with my pitch deck?”
Bring them on!
I’ve faced these challenges firsthand multiple times, and when CEOs bring them to me, I’m ready to share my war scars.
At the minimum, I help narrow the options from “I don’t know how” to a set of multiple choices. I don’t make decisions for CEOs; I help them make better ones. They are ultimately responsible for their decisions, and I see my role as a guide, not a decision-maker.
Being the CEO of a fast-scaling company is an enormous challenge that people should not underestimate—the level of experience, capacity, intensity, and mental strength that one needs to cope with. That’s why it is the loneliest job. Empathy is not enough. The best help I ever got was from a more experienced CEO than me at the time — someone who had walked the road ahead — and now it’s my turn to pay it forward. It is payback time for me.
The more I think about it, the less “Operating Partner” seems to fit. I don’t step into the spotlight or take over operations. My role is more like Yoda—helping Skywalker fight the battles while staying behind the scenes.
So perhaps my title shouldn’t be Operating Partner after all. Maybe it should just be… Yoda.
May the Force be with you!
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This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Thank you to The Globe for publishing my op-ed about AI last week. In it, I draw parallels between the dot-com crash and the current AI boom—keeping in mind the old saying, “History doesn’t repeat itself, but it often rhymes.” The piece also explores how the atomic unit of this transformation is the ever-declining “cost of intelligence.” AI is the first technology in human history capable of learning, reasoning, creativity, cross-domain thinking, and decision-making. This fundamental shift will impact every sector, without exception, spurring the rise of new tech giants and inevitable casualties in the process. The key is knowing which land to grab!
The piece is now available below.
In the past month, everyone I spoke to has been talking about DeepSeek and Nvidia. Is Nvidia facing extinction? Have certain tech giants overspent on AI? Are we seeing a bubble about to burst, or just another public market overreaction? And what about traditional sectors, like industrials, that haven’t yet felt AI’s impact?
Let’s step back. We’ll revisit companies that soared or collapsed during the dot-com crash – and the lessons we can learn. As Mark Twain reputedly said, “History doesn’t repeat itself, but it often rhymes.”
The answer is that the reports of Nvidia’s demise are greatly exaggerated, though other companies face greater danger. At the same time, new opportunities are vast because this AI-driven shift could dwarf past tech disruptions.
Before 2000, the dot-com mania hit full speed. High-flying infrastructure players such as Global Crossing – once worth US$47-billion – provided backbone networks. Cisco delivered networking equipment, and Sun Microsystems built servers. However, amid the crash, Global Crossing went bankrupt in January, 2002. Cisco plummeted from more than US$500-billion in market cap to about $100-billion. Sun Microsystems sank from a US$200-billion market cap to under US$10-billion.
They failed or shrank for different reasons. Global Crossing needed huge investments before real revenue arrived. Cisco had decent unit economics but lost pricing power when open networking standards commoditized its gear. Sun Microsystems suffered when cheaper hardware and free, open-source software (such as Linux and Apache) undercut it, and commodity hardware plus cloud computing made its servers irrelevant.
However, these companies did not decline because they were infrastructure providers. They declined because they failed to identify the right business model before their capital ran out or were disrupted by alternatives, including open or free systems, despite having the first-mover advantage.
Meanwhile, other infrastructure players thrived. Amazon, seen mostly as an e-commerce site, earned 70 per cent of its operating profit from Amazon Web Services – hosting startups and big players such as Netflix. AWS eliminated the need to buy hardware and continually cut prices, especially in its earlier years, catalyzing a new wave of businesses and ultimately driving demand while increasing AWS’s revenue.
In hindsight, the dot-com boom was real – it simply took time for usage to catch up to the hype. By the late 2000s, mobile, social and cloud surged. Internet-native giants (Netflix, Google, etc.) grew quickly with products that truly fit the medium. Early front-runners such as Yahoo! and eBay faded. Keep in mind that Facebook was founded in 2004, well after the crash, and Apple shifted from iPods to the revolutionary iPhone in 2007, which further catalyzed the internet explosion. A first-mover advantage might not always pay off.
The first lesson we learned is that open systems disrupt and commoditize infrastructure. At that time, and we are seeing it again, an army of contributors drove open systems for free, allowing them to out-innovate proprietary solutions.
Companies that compete directly against open systems – note that Nvidia does not – are particularly vulnerable at the infrastructure layer when many open and free alternatives (such as those solely building LLMs without any applications) exist. DeepSeek, for example, was inevitable – this is how technology evolves.
Open standards, open source and other open systems dramatically lower costs, reduce barriers to AI adoption and undermine incumbents’ pricing power by offering free, high-quality alternatives. This “creative destruction” drives technological progress.
In other words, OpenAI is in a vulnerable position, as it resembles the software side of Sun Microsystems – competing with free alternatives such as Linux. It also requires significant capital to build out, yet its infrastructure is rapidly becoming commoditized, much like Global Crossing’s situation. On the other hand, Nvidia has a strong portfolio of proprietary technologies with few commoditized alternatives, making its position relatively secure. Nvidia is not the new Sun Microsystems or Cisco.
Most importantly, the disruption and commoditization of infrastructure also democratize AI innovation. Until recently, starting an AI company often required raising millions – if not tens of millions – just to get off the ground. That is already changing, as numerous fast-growing companies have started and scaled with minimal initial capital. This is leading to an explosion of innovative startups and further accelerating the flywheel.
The next lesson we learned is that the internet was the first technology in human history that was borderless, connected, ubiquitous, real-time, and free. Its atomic unit is connectivity. During its rise, “the cost of connectivity” steadily declined, while productivity gains from increased connectivity continued to expand demand. The flywheel turned faster and faster, forming a virtuous cycle.
Similarly, AI is the first technology in human history capable of learning, reasoning, creativity, cross-domain functions and decision-making. Crucially, AI’s influence is no longer confined to preprogrammed software running on computing devices; it now extends into all types of machines. Hardware and software, combined with collective learning, enable autonomous cars and other systems like robots to adapt intelligently in real time with little or no predefined instructions.
These breakthroughs are reaching sectors scarcely touched by the internet revolution, including manufacturing and energy. This goes beyond simple digitization; we are entering an era of autonomous operations and, ultimately, autonomous businesses, allowing humans to focus on higher-value tasks.
As with connectivity costs in the internet era, in this AI era, “the cost of intelligence” has been steadily declining. Meanwhile, the value derived from increased intelligence continues to grow, driving further demand – this mirrors how the internet played out and is already happening again for AI. The parallels between these two platform shifts suggest that massive economic value will be created or shifted from incumbents, opening substantial investment opportunities across early-stage ventures, growth-stage private markets and public investments.
Just as the early internet boom heavily focused on infrastructure, a significant amount of capital has been invested in enabling AI technologies. However, over time, economic value shifts from infrastructure to applications – just as it did with the internet.
This doesn’t mean there are no opportunities in AI infrastructure – far from it. Remember, more than half of Amazon’s profits come from AWS. Services, such as AWS, that provide access to AI, will continue to benefit as demand soars. Similarly, Nvidia will continue to benefit from the rising demand. However, many of today’s most-valuable companies – both public and private – are in the application layer or operate full-stack models.
Despite these advancements, this transformation won’t happen overnight, but it will likely unfold more quickly than the internet disruption – which took more than a decade – because many core technologies for rapid innovation are already in place.
AI revenues might appear modest today and don’t yet show up in the public markets. However, if we look closer, some AI-native startups are already growing at an unprecedented pace. The disruption isn’t a prediction; it’s already happening.
As Bill Gates once said, “Most people overestimate what they can achieve in one year and underestimate what they can achieve in ten years.”
The AI revolution is just beginning. The next decade will bring enormous opportunities – and a new wave of tech giants, alongside inevitable casualties.
It’s a land grab – you just need to know which land to seize!
P.S. If you enjoyed this blog post, please take a minute to like, comment, subscribe and share. Thank you for reading!
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
When Two Small Fish first started in 2015, we formulated our “Thesis 1.0” to focus on network effects exclusively. We leveraged our hands-on product experience in scaling Wattpad from 0 to 100 million users—essentially a marketplace for readers and writers—and applied a similar lens to other verticals, both in B2C and B2B.
It worked incredibly well for TSF because, at the time, network effects were the holy grail for defensibility, yet they were often misunderstood (for example, going viral is not the same as having network effects, and simply operating a marketplace does not guarantee strong network effects!). Our skill is more transferable than you might think!
So, Eva created the ASSET framework, which helped us identify the best network-effect investment opportunities and, more importantly, helped entrepreneurs understand and increase their network effect coefficient—the measure of true network effects—and ultimately embed strong network effects into their products. In short:
• A stands for “atomic unit”
• S stands for “seed the supply side”
• The other S stands for “scale the demand side”
• E stands for “enlarge the network effect” or “enhance the network coefficient”
• T stands for “track proprietary insights”
This framework provided a simple yet systematic way to judge whether a company truly had network effects or merely the illusion of them.
However, toward the end of the last decade, it became increasingly difficult to find investable network-effect opportunities. Well-established incumbents already had very strong network effects in place, effectively setting the world order. It became exceedingly difficult for emerging disruptors—both in consumer and enterprise spaces—to find a gap to break through.
We began looking for other forms of technology defensibility (for example, semiconductors) and gradually moved away from “shallow tech” network-effect investments, as we found very few investable opportunities. In fact, our last shallow tech investment was made about three years ago.
Then, in late 2022, ChatGPT arrived.
As the world now understands, generative AI is the first technology in human history capable of learning, reasoning, creativity, cross-domain functionality, and decision-making. It’s the most significant platform shift since mobile, social, and cloud computing in the late 2010s—and arguably the biggest one in human history. It also means the playing field has been leveled. Today, there are numerous ways to create new products with powerful network effects that can render incumbents’ offerings obsolete (for example, I haven’t used Google Search regularly for a long time) because newcomers can disrupt incumbents from all three angles: technology, product, and commercialization (e.g., business models). Incumbents are vulnerable!
On the other hand, the ASSET framework also needed a refresh, as we’re no longer dealing with simple, well-understood marketplaces. What if one side of the marketplace is now AI? Even though our original framework was designed to handle data-driven network effects, the speed and scale of data generation have multiplied by orders of magnitude. How does this affect enlarging the network effects and increasing the coefficient?
The good news is that there are now ways to massively increase the network effect coefficient in a remarkably short time. The bad news is that all your competitors—large or small—can do the same. Competition has never been fiercer.
After ChatGPT was released, we quickly revised our ASSET framework to version 2.0. Since then, we’ve been guest-lecturing this masterclass worldwide for well over a year. By fully leveraging AI’s creativity and reasoning capabilities, entrepreneurs can now harness human-machine collaboration to supercharge both the demand and supply sides, blitz-scale, and create new atomic units. Here’s the gist of 2.0:
• A – Atomic Unit of Product
• S – Super Seed the Supply Side (now amplified by Gen AI)
• S – Supercharge the Demand Side (now leveraging Gen AI)
• E – Exponential Engagement (using the human + AI combo)
• T – Transform Business with New AI-powered Atomic Units
Like 1.0, this new framework is easy to understand but difficult to master—and it’s even more complex now because, with Gen AI, it’s non-linear. Our masterclass covers the lecture material, but the real work happens in our private tutoring, where execution matters—and this is how we help our portfolio companies win.
The old network effect is dead. Thanks to the AI platform shift, network effects are roaring back in a different and far more potent way in the new world order. The combination of deep tech defensibility plus network effect defensibility is the new holy grail—and we are specialized in both.
With the AI platform shift, all of a sudden, there are many new investable opportunities that didn’t exist before. At the same time, the ground has shifted: the old playbook is out, and the new playbook is in. It’s exciting; we love the challenge, and we wouldn’t have it any other way.
P.S. If you enjoyed this blog post, please take a minute to like, comment, subscribe and share. Thank you for reading!
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Fibra is developing smart underwear embedded with proprietory textile-based sensors for seamless, non-invasive monitoring of previously untapped vital biomarkers. Their innovative technology provides continuous, accurate health insights—all within the comfort of everyday clothing. Learning from user data, it then provides personalized insights, helping women track, plan, and optimize their reproductive health with ease. This AI-driven approach enhances the precision and effectiveness of health monitoring, empowering users with actionable information tailored to their unique needs.
Fibra has already collected millions of data points with its product, further strengthening its AI capabilities and improving the accuracy of its health insights. While Fibra’s initial focus is female fertility tracking, its platform has the potential to expand into broader areas of women’s health, including pregnancy detection/monitoring, menopause, detection of STDs and cervical cancer and many more, fundamentally transforming how we monitor and understand our bodies.
Perfect Founder-Market Fit
Fibra was founded by Parnian Majd, an exceptional leader in biomedical innovation. She holds a Master of Engineering in Biomedical Engineering from the University of Toronto and a Bachelor’s degree in Biomedical Engineering from TMU. Her achievements have been widely recognized, including being an EY Women in Tech Award recipient, a Rogers Women Empowerment Award finalist for Innovation, and more.
We are thrilled to support Parnian and the Fibra team as they push the boundaries of AI-driven smart textiles and health monitoring. We are entering a golden age of deep-tech innovation and software-hardware convergence—a space we are excited to champion at Two Small Fish Ventures.
Stay tuned as Fibra advances its mission to empower women through cutting-edge health technology.
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
The Two Small Fish team is thrilled to announce our investment in Hepzibah AI, a new venture founded by Untether AI’s co-founders, serial entrepreneurs Martin Snelgrove and Raymond Chik, along with David Lynch and Taneem Ahmed. Their mission is to bring next-generation, energy-efficient AI inference technologies to market, transforming how AI compute is integrated into everything from consumer electronics to industrial systems. We are proud to be the lead investor in this round, and I will be joining as a board observer to support Hepzibah AI as they build the future of AI inference.
The Vision Behind Hepzibah AI
Hepzibah AI is built on the breakthrough energy-efficient AI inference compute architecture pioneered at Untether AI—but takes it even further. In addition to pushing performance/power harder, it can handle training loads like distillation, and it provides supercomputer-style networking on-chip. Their business model focuses on providing IP and core designs that chipmakers can incorporate into their system-on-chip designs. Rather than manufacturing AI chips themselves, Hepzibah AI will license its advanced AI inference IP for integration into a wide variety of devices and products.
Hepzibah AI’s tagline, “Extreme Full-stack AI: from models to metals,” perfectly encapsulates their vision. They are tackling AI from the highest levels of software optimization down to the most fundamental aspects of hardware architecture, ensuring that AI inference is not only more powerful but also dramatically more efficient.
Why does this matter? AI is rapidly becoming as indispensable as the CPU has been for the past few decades. Today, many modern chips, especially system-on-chip (SoC) devices, include a CPU or MCU core, and increasingly, those same chips will require AI capabilities to keep up with the growing demand for smarter, more efficient processing.
This approach allows Hepzibah AI to focus on programmability and adaptable hardware configurations, ensuring they stay ahead of the rapidly evolving AI landscape. By providing best-in-class AI inference IP, Hepzibah AI is in a prime position to capture this massive opportunity.
An Exceptional Founding Team
Martin Snelgrove and Raymond Chik are luminaries in this space—I’ve known them for decades. David Lynch and Taneem Ahmed also bring deep industry expertise, having spent years building and commercializing cutting-edge silicon and software products.
Their collective experience in this rapidly expanding, soon-to-be ubiquitous industry makes investing in Hepzibah AI a clear choice. We can’t wait to see what they accomplish next.
P.S. You may notice that the logo is a curled skunk. I’d like to highlight that the skunk’s eyes are zeros from the MNIST dataset. 🙂
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Note: One of the most common pieces of feedback we receive from entrepreneurs is that TSF partners don’t think, act, or speak like typical VCs. The Contrarian Series is meant to demystify this, so founders know more about us before pitching.
When I said “Two Small Fish love Zero TAM businesses,” I said it so matter-of-factly that the crowd was taken aback. I even saw quite a few posts on social media that said, “I can’t believe Allen Lau said it!”
Of course, any business will need to go after a non-zero TAM eventually. But hear me out.
Here’s what I did at Wattpad: I never had a “total addressable market” slide in the early days. I just said, “There are five billion people who can read and write, and I want to capture them all!”
Even when we became a scaleup, I kept the same line. I just said, “There are billions of people who can read, write, or watch our movies, and I want to capture them all!”
Naturally, some VCs tried to box me into the “publishing tool” category or other buckets they deemed appropriate. But Wattpad didn’t really fit into anything that existed at the time. Trust me, I tried to find a box I would fit in too, but none felt natural.
Why? That’s because Wattpad was a category creator. And, of course, that meant our TAM was effectively zero.
In other words, we made our own TAM.
Many of our portfolio companies are also category creators, so their decks often don’t have a TAM slide either.
Yes, any venture-backed company eventually needs a large TAM. And, of course, I don’t mean to suggest that every startup needs to be a category creator.
That said, we’re perfectly fine—in fact, sometimes we even prefer—seeing a pitch deck without a TAM slide. By definition, category creators have first-mover advantages. More importantly, category creators in a large, winner-take-all market—especially those with strong moats—tend to be extremely valuable at scale and, hence, highly investable.
So, founders, if your company is poised to create a large category, skip the TAM slide when pitching to Two Small Fish. We love it!
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
It’s been almost three years since I stepped aside from my role as CEO of Wattpad, yet I’m still amazed by the reactions I get when I bump into people who have been part of the Wattpad story. The impact continues to surface in unexpected and inspiring ways frequently.
Wattpad has always been a platform built on storytelling for all ages and genders. That being said, our core demographic—roughly 50% of our users—has been teenage girls. Young women have always played a pivotal role in the Wattpad community.
Next year, Wattpad will turn 20 (!)—a milestone that feels both surreal and deeply rewarding. When we started in 2006, we couldn’t have imagined the journey ahead. But one thing is certain: our early users have grown up, and many of them are now in their 20s and 30s, making their mark on the world in remarkable ways.
A perfect example: at our recent masterclass at the University of Toronto, I ran into Nour. A decade ago, she was pulling all-nighters reading on Wattpad. Today, she’s an Engineering Science student at the University of Toronto, specializing in machine intelligence. Her story is not unique. Over the years, I’ve met countless female Wattpad users who are now scientists, engineers, and entrepreneurs, building startups and pushing boundaries in STEM fields.
This is incredibly fulfilling. Many of them have told me that they looked up to Wattpad and our journey as a source of inspiration. The idea that something we built has played even a small role in shaping their ambitions is humbling.
Now, as an investor at Two Small Fish, I’m excited about the prospect of supporting these entrepreneurs in the next stage of their journey. Some of these Wattpad users will go on to build the next great startups, and it would be incredible to be part of their success, just as they were part of Wattpad’s.
On this International Women’s Day, I want to celebrate this unintended but, in hindsight, obvious outcome: a generation of young women who grew up on Wattpad are now stepping into leadership roles in tech and beyond. They are the next wave of innovators, creators, and entrepreneurs, and I can’t wait to see what they build next.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
I’d like to extend my heartfelt congratulations to Richard Sutton, co-founder of Openmind Research Institute and a pioneer in Reinforcement Learning, for being honoured with the 2024 Turing Award—often described as the “Nobel Prize of Computing.” This accolade reflects his groundbreaking contributions, which have shaped modern AI across a wide spectrum of applications, from LLMs to robotics and everything in between. His influence resonates throughout classrooms, research, and everyday life worldwide.
As a self-professed science nerd, I’ve had the privilege and honour of working with him through the Openmind board. Rich co-founded Openmind alongside Randy Goebel and Joseph Modayil as a non-profit focused on conducting fundamental AI research to better understand minds. We believe that the greatest breakthroughs in AI are still ahead of us, and that basic research lays the groundwork for future commercial and technological innovations.
A core principle of Openmind—and a guiding philosophy of its co-founders—is a commitment to open research: there are no intellectual property restrictions on its work, ensuring everyone can contribute to and build upon this shared body of knowledge. Rich’s vision and dedication continue to inspire researchers and practitioners around the world to push the boundaries of AI and openly share their insights. This Turing Award is a well-deserved recognition of his transformative impact, and I can’t wait to see the breakthroughs that lie ahead as his work continues to redefine our understanding of intelligence.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
In many companies, the bottleneck isn’t necessarily in the execution of decisions. The real bottleneck is the excessive time people waste making decisions.
When I was Wattpad’s CEO, everyone in the company knew I had a simple 2×2 framework to empower the whole team to make fast, high-quality decisions – all by themselves!
The essence of this framework comes down to two questions:
• Is this decision reversible?
• Is this decision consequential?
These two factors create four types of decisions:
1. Reversible and inconsequential
2. Reversible and consequential
3. Irreversible and inconsequential
4. Irreversible and consequential
Examples of Each Type
1. Reversible and Inconsequential
This actually makes up the bulk of decisions in a company:
• Internal Slack messages? Delete them if you don’t like them.
• Marketing team’s benign social media copy?Remove the post if it doesn’t work.
• Small typo like the one in the above image? Yes, I purposely left the typo there. I look sloppy, but I could silently replace it with a better one when I have time.
• Small bugs in the product? If a bug fix causes other problems, revert the changes.
The list goes on. The trick is to empower each person in the company to make these decisions independently. I reinforced the same message to the Wattpad team over and over again:
From the most junior interns to the most senior leaders—you’re empowered to make the call all by yourself.
No boss to ask. No approval process. Just do it!
The company moves fast when most decisions don’t require a meeting!
2. Irreversible and Inconsequential
Here’s an example:
At one point, we ran out of space at Wattpad’s Toronto HQ and needed overflow space. We found a small office—just a few hundred square feet with a couple of meeting rooms—in the building right next door. The location was perfect, but the space itself? Just okay.
The problem was the lease—it was relatively long. Once we signed, we couldn’t back out. That limited our flexibility (irreversible), but we knew that if we needed more room, we could always find another expansion space. The cost was small in the grand scheme of things (inconsequential).
Given our growth, there was little downside to signing the lease. So we moved fast, signed the deal, and moved on to the next item on the to-do list.
For this type of decision, you can still move fast. Just be careful—double-check the lease for any hidden “gotchas.” It’s not about if we sign or not. We will sign, but we just want to make sure the bases are covered before we do.
You’d be surprised how much time people waste on indecision. Just make the call and do the due diligence!
When done properly, product releases can be very consequential but still reversible. At Wattpad, we released high-risk software all the time—but always with a way to roll back if things didn’t work.
We knew how to press the undo button!
For these kinds of decisions, move fast and make the call—but monitor the outcome and always be ready to press undo.
Important: How to Increase the Quality of These Decisions
For both Irreversible and Inconsequential decisions and Reversible and Consequential decisions, always ask:
Is there any way to make this decision more reversible or less consequential?
If you can tweak the decision to minimize fallout—no matter how small—do it. It will save time and stress down the road.
4. Irreversible and Consequential
Many of these are leadership-team-level or CEO-level decisions.
They’re rare but also the hardest to make. They require a lot of context, consideration, and, sometimes, choosing between two bad options. Occasionally, you get a good one and choose between a few great choices.
The ultimate example for me?
Whether to take the company public, maintain the status quo and keep going, or accept an acquisition offer.
Sometimes, knowing which quadrant a decision falls into is an art. But imagine if we didn’t have this framework—slow decision-making would have ground the company to a halt.
The key to moving fast isn’t just execution—it’s deciding fast, too.
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This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
“Deep Tech” is one of those terms that gets thrown around a lot in venture capital and startup circles, but defining it precisely is harder than it seems. If you check Wikipedia, you’ll find this:
Deep technology (deep tech) or hard tech is a classification of organization, or more typically a startup company, with the expressed objective of providing technology solutions based on substantial scientific or engineering challenges. They present challenges requiring lengthy research and development and large capital investment before successful commercialization. Their primary risk is technical risk, while market risk is often significantly lower due to the clear potential value of the solution to society. The underlying scientific or engineering problems being solved by deep tech and hard tech companies generate valuable intellectual property and are hard to reproduce.
At a high level, this definition makes sense. Deep tech companies tackle hard scientific and engineering problems, create intellectual property, and take time to commercialize. But what do substantial scientific or engineering challenges actually mean? Specifically, what counts as substantial? “Substantial” is a vague word. A difficult or time-consuming engineering problem isn’t necessarily a deep tech problem. There are plenty of startups that build complex technology but aren’t what I’d call deep tech. It’s about tackling problems where existing knowledge and tools aren’t enough.
In 1964, Supreme Court Justice Potter Stewart famously said, “I know it when I see it” when asked to describe his test for obscenity in Jacobellis v. Ohio. By no means am I comparing deep tech to obscenity—I don’t even want to put these two things in the same sentence. However, there is a parallel between the two: they are both hard to put into a strict formula, but experienced technologists like us recognize deep tech when we see it.
So, at Two Small Fish, we have developed our own simple rule of thumb:
If we see a product and say, “How did they do that?” and upon hearing from the founders how it is supposed to work, we still say, “Team TSF can’t build this ourselves in 6–12 months,” then it’s deep tech.
At TSF, we invest in the next frontier of computing and its applications. We’re not just looking for smart founders. We’re looking for founders who see things others don’t—who work at the edge of what’s possible. And when we find them, we know it when we see it.
This test has been surprisingly effective. Every single investment we’ve made in the past few years has passed it. And I expect it will continue to serve us well.
P.S. If you enjoyed this blog post, please take a minute to like, comment, subscribe and share. Thank you for reading!
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Most people don’t realize just how global Wattpad’s business is. Here are a few fun facts:
• Only 25% of our 100 million users are from North America, while 25% come from LATAM, 25% from Europe, and 25% from Asia.
• Of the 50 languages on Wattpad, the most popular isn’t English—it’s Spanish. Other widely used languages include Bahasa Indonesia (10 million users) and Tagalog (6 million users), with millions more reading and writing in Italian, French, German, Portuguese, Vietnamese, and many others.
• Not only have our print books (yes, we’re a book publisher too) been New York Times bestsellers, but they’ve also hit #1 in multiple countries, including Germany and Colombia.
• #1 on Netflix globally and other streaming platforms? We’ve done that many times—including the Spanish smash hit A Través De Mi Ventana (Through My Window), which we co-produced with Netflix. Many #1-rated TV shows worldwide are based on Wattpad stories—and we co-produce them.
• #1 at the box office? We’ve achieved that in multiple countries as well.
How did we build this?
A lot of things made this happen, but I’ll highlight a few. It started on day one. Here’s a screenshot of our website when we launched in 2006.
Notice that we already supported many key languages worldwide. Why? Because only about 400 million people speak English as their first language—that’s less than 5% of the world’s population.
And we were right! The first language that took off wasn’t something we predicted—it was Vietnamese. We couldn’t have guessed that!
When the first Android phone came out (the T-Mobile G1), we were one of the first to support it. At that time, the iPhone was primarily a high-GDP country phenomenon, while low-GDP countries were dominated by $30 Android phones. When I travelled to these regions, I frequently brought back bags of inexpensive phones so our team could test and ensure our app worked on low-end devices. This allowed us to dominate globally.
When we raised growth capital, we didn’t just seek funding from Silicon Valley investors—we broadened our investor base to include backers from other countries. This helped us learn the nuances of international expansion while gaining support from investors who understood these markets.
When we launched subscriptions, we recognized that a one-size-fits-all model wouldn’t work. Some countries preferred à la carte purchases over all-you-can-read models. So, we introduced our own virtual currency, allowing users to buy content à la carte.
When we expanded into movies and TV shows, we didn’t just partner with Hollywood studios—we forged partnerships with entertainment companies across five continents. This ensured Wattpad story adaptations could be seen everywhere.
And the list goes on.
None of this happened automagically. It took years of conscious, deliberate effort. But once we built the foundation, expanding into new countries became incremental. There’s no free lunch, but it’s also not rocket science—it got easier and easier as we grew.
We built a truly global powerhouse with 100 million users.
If we could do it, you can too.
Choosing between the U.S. and international expansion is a false dichotomy—you can do both. As the world shifts toward intangible assets, building a global business is easier than ever.
Keep in mind that while the U.S. is the largest economy, it only accounts for approximately 26% of the world’s GDP. To create true optionality, not expanding globally—especially beyond the U.S.—is not an option.
Our experience in building a successful global business also allows us to help our portfolio companies scale internationally. We’ve been through the challenges of global expansion firsthand, and we actively share these insights to support the next generation of world-changing companies. Reach out to us if you want to be part of it!
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
The tariffs are coming. We all know this isn’t really about fentanyl—only 19 kg of the U.S.’s supply comes from Canada, while close to 10,000 kg was seized at the U.S. border.
Even if we solved this tiny issue, Trump would find something else—maybe he’d complain that the snow in NYC is due to cold air from Canada and slap us with another tariff.
Trump’s playbook is simple: weaponize everything at his disposal to get what he wants.
He’s imposing tariffs on everything from us. We can debate whether to slap tariffs on orange juice or hair dryers in response, but that won’t materially change the outcome. How we react now is just noise—he holds all the leverage anyway. Canada will suffer in the short term, no matter what.
But we shouldn’t let a crisis go to waste. This is a golden opportunity to fix systemic issues that were previously near impossible to address—like interprovincial trade barriers. Yet even fixing that won’t solve the root problem.
Stepping back, the real issue is one of the first principles of leadership: Optionality.
Having alternatives always provides leverage. This principle applies broadly—not just to negotiations, but also to fundraising, supplier relationships, operations, company survival, M&A, and beyond—including leading a country.
Trump understands leverage better than most. This isn’t just about negotiation—even if we reach a deal this time, any agreement with him isn’t worth the paper it’s written on.
As a country, we are far too dependent on the U.S., and Trump knows it. Only by addressing our lack of optionality can we deal with him—and future U.S. presidents—on equal footing.
There is no quick fix. Only a new, decisive, visionary Prime Minister can guide Canada out of this mess.
The only way forward is to leverage what we do best—energy, natural resources, AI, and more—to create true optionality. As the world shifts toward intangible assets, ironically, our proximity to the U.S. is becoming less of a hindrance to diversification.
We must control our own destiny. We cannot allow any single country—U.S. or otherwise—to hold us hostage.
Only optionality can make Canada strong and free.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Sonos replaced its CEO last week. The company faced significant backlash after launching a redesigned app earlier last year that was plagued by bugs, missing features, and connectivity issues, frustrating customers and tarnishing its reputation. This also led to layoffs, poor sales, and a significant drop in stock price.
While I usually don’t comment on companies I’m not involved with, as a long-time Sonos user, I was very frustrated that the alarm feature I had been relying on to wake me up in the morning for well over a decade disappeared overnight. There were other issues, too.
Throughout my career, I have worked on numerous redesign projects. A fiasco like this is totally avoidable. Today, I am sharing a couple of internal blog posts I wrote for my team (when I was Wattpad’s CEO) about this topic. Of course, these are just examples of the general framework I used. In practice, there are many specific details in each redesign that I helped guide the team through, as frameworks like this are like a hammer. Even the best hammer in the world is still just a hammer. The devil is in the details of how you use it.
These internal blog posts are just some of the hammers and drills in my toolbox that I use to help our portfolio CEOs navigate trade-offs and move fast without breaking things.
Happy reading through a sample of my collection of half a million words!
Note: These two posts have been mildly edited to improve readability.
Blog Post #1 – Subject: Feature Backward Compatibility
I have gone through major technology platform redesigns many times in my career. One problem that arises every single time is backward compatibility.
The reason is easy to understand: users can interact with complex products (such as Wattpad) in a million different ways. There is no way the engineering team could anticipate all the permutations.
There are two common ways to solve this problem. First, run an extensive beta program. This is what big companies like Apple and Microsoft do when they update their operating systems. This approach is also a great way to push some of the responsibility to their app developers. Even with virtually unlimited resources, crowdsourcing from app developers is still a far better approach. However, running an extensive beta program takes a lot of time and resources. Most companies can’t afford to do that.
The other approach is to roll out the changes progressively and incrementally. It is very tempting to make all the big changes at once, roll them out in one shot, and roll the dice. However, I am almost certain that it will backfire. Not only is it a frustrating experience for both users and engineers, but it also makes the project schedule much less predictable and, in most cases, causes the project to take much longer than anticipated.
Next year, when we focus on our redesign to reduce tech debt, don’t forget to set aside some time budget for these edge conditions that are so easily overlooked. Also, think about how we can roll out the changes more incrementally to minimize the negative impact on our users.
Blog Post #2 – Subject: The Reversibility and Consequentiality Framework
The other day, I spoke to the CEO of another consumer internet company. In terms of the scale of its user base, this company is much smaller than Wattpad, but we are still talking about millions of users here.
Like us, this company has been around for over a decade. Not surprisingly, technical debt has been an ongoing concern. A few years ago, the team decided to completely redesign its platform from the ground up. The redesign was a multi-year effort, and the team finally pulled back the curtain a year ago. While it is working fine now, this CEO told me that it took a few months before they fixed all the issues and reimplemented all the “missing” features because many of their users were using the product in “interesting” ways that the new version did not support.
These problems are fairly common when redesigning a new system from the ground up. In practice, it is simply impossible to take all the permutations into account, no matter how carefully you plan. However, if we mess things up, our user base is so large that it might negatively impact (or ruin!) 100 million people’s lives in the worst-case scenario.
On the flip side, over-planning could burn through a lot of unnecessary cycles.
One way or another, we should not let these challenges deter us from moving forward or even slow us down because there are many ways to mitigate potential problems. In principle, ensuring that the rollout is reversible and inconsequential is key.
The former is easy to understand: Can we roll back when things go wrong? Do we have a kill switch when updating our mobile apps? These are best practices that we have already been using.
However, at times, these best practices might not be possible. Can we reduce the consequentiality when rolling out? If the iOS app were completely redesigned, could we do it in smaller chunks, parallel-run the new and old versions at the same time, or try the new version on 0.1% of our users first? If not, could we roll out the new app in a small country first?
Again, our objective is not to avoid any problem at all costs. Our objective is to minimize (but not eliminate) the negative impact when things go wrong—not if things go wrong. Although Wattpad going dark for 100 million people for an extended period of time is not acceptable, in the spirit of speed, it is perfectly okay if we have ways to hit reverse or reduce the impact to only a small percentage of our users. These are not rocket science, but they do require a bit more thoughtfulness because our user base is so large that we can’t simply roll the dice.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
We are thrilled to announce that Albert Chen is joining Two Small Fish as a Venture Partner!
Albert brings a wealth of experience to our team. Like all our partners at TSF, Albert’s expertise spans the full spectrum—from technical innovation to product development to operational leadership in entrepreneurial startups. His impressive academic background further underscores his exceptional capabilities.
Albert earned his Ph.D. in BioMEMS, Acoustics, and Medical Engineering from the University of Waterloo. He also completed his undergraduate studies in Systems Design Engineering at Waterloo and participated in an international exchange program in Electrical Engineering at National Taiwan University.
Albert’s professional career is equally remarkable. Most notably, he served as the CTO of robotics and edge AI company Forcen. His diverse experience also includes roles at Metergy (smart energy), Excelitas (photonics), and North (smart glass, acquired by Google).
This is just a glimpse of Albert’s impressive journey. Follow him on LinkedIn to learn more about his background and accomplishments.
At Two Small Fish Ventures, we are committed to supporting bold founders shaping the future of technology through our experience. Albert’s extensive academic background, combined with his hands-on leadership and innovation experience, makes him an invaluable addition to our team.
Please join us in welcoming Albert to Two Small Fish!
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Who are the top 50 VCs in Canada? Two Small Fish Ventures is one of them! At Two Small Fish Ventures, we are deeply honoured to be named among Canada’s top 50 venture capital firms in this year’s edition of The 50 — the annual guide produced by the Canadian Venture Capital & Private Equity Association (CVCA) and the Trade Commissioner Service (TCS).
This recognition is not just a badge for us; it’s a reflection of the thriving and globally respected Canadian venture ecosystem we are proud to be part of. We share this honour with an incredible group of firms that are shaping the future of technology, science, and innovation across the country and beyond.
If you are an entrepreneur, this list represents the Canadian VCs you should talk to — firms committed to partnering with visionary founders, pushing boundaries, and building category-defining companies.
We look forward to continuing to back the next generation of transformational founders and are grateful to the CVCA and TCS for this spotlight.
The Full List: Canada’s Top 50 VCs
Here’s the full list of the firms recognized this year (in alphabetical order):
This is the picture I used to open our 2024 AGM a few months ago. It highlights how drastically the landscape has changed in just the past couple of years. I told a similar story to our LPs during the 2023 AGM, but now, the pace of change has accelerated even further, and the disruption is crystal clear.
The following outlines the reasons behind one of the biggest shifts we identified as part of our Thesis 2.0 two years ago.
Like many VCs, we evaluate pitches from countless companies daily. What we’ve noticed is a significant rise in startups that are nearly identical to one another in the same category. Once, I quipped, “This is the fourth one this week—and it’s only Tuesday!”
The reason for this explosion is simple: the cost of starting a software company has plummeted. What once required $1–2M of funding to hire a small team can now be achieved by two founders (or even a solo founder) with little more than a laptop or two and a $20/month subscription to ChatGPT Pro (or your favourite AI coding assistant).
With these tools, founders can build, test, and iterate at unprecedented speeds. The product build-iterate-test-repeat cycle is insanely short. If each iteration is a “shot on goal,” the $1–2M of the past bought you a few shots within a 12–18 month runway. Today, that $20/month can buy you a shot every few hours.
This dramatic drop in costs, coupled with exponentially faster iteration speeds, has led to a flood of startups entering the market in each category. Competition has never been fiercer. This relentless pace also means faster failures, and the startup graveyard is now overflowing.
For early-stage investors, picking winners from this influx of startups has become significantly harder. In the past, you might have been able to identify the category winner out of 10 similar companies. Now, it feels like mission impossible when there are hundreds—or even thousands—of startups in each category. Many of them are even invisible, flying under the radar for much longer because they don’t need to fundraise.
Of course, there will still be many new billion-dollar companies. In fact, I am convinced that this AI-driven platform shift will produce more billion-dollar winners than ever—across virtually every established category and entirely new ones that don’t yet exist. But by the law of large numbers, spotting them among thousands of startups in each category is harder than ever.
If you’re using the same lens that worked in the past to spot and fund these future tech giants, good luck.
That’s why, for a long time now, we’ve been using a very different lens to identify great opportunities with highly defensible moats to stay ahead of the curve. For example, we’ve been exclusively focused on deep tech—a space where we know we have a clear edge. From technology to product to operations, we have the experience to cover the full spectrum and support founders through the unique challenges of building deep tech startups. So far, this approach has been working really well for us.
I guess we are taking our own advice. As a VC firm, we also need to be constantly improving and striving to be unrecognizable every two years!
There’s no doubt the rules of early-stage VC have shifted. How we access, assess, and assist startups has evolved dramatically. The great AI democratization is affecting all sectors, and venture capital is no exception.
For investors who can adapt, this is a time of unparalleled opportunity—perhaps the greatest era yet in tech investing. The playing field has been levelled, and massive disruption (and therefore opportunities) lies ahead. Incumbents are vulnerable, and new champions will emerge in each category – including VC!
Investing during this platform shift is both exciting and challenging. And I wouldn’t want it any other way, because those who figure it out will be handsomely rewarded.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
The next frontier of AI lies at the edge — where data is generated. By moving AI toward the edge, we unlock real-time, efficient, and privacy-focused processing, opening the door to a wave of new opportunities. One of our most recent investments, Applied Brain Research (ABR), is leading this revolution by bringing “cloud-level” AI capabilities to edge devices.
Why is this important? Billions of power-constrained devices require substantial AI processing. Many of these devices operate offline (e.g., drones, medical devices, and industrial equipment), have access only to unreliable, slow, or high-latency networks (e.g., wearables and smart glasses), or must process data streams in real time (e.g., autonomous vehicles). Due to insufficient on-device capability, the only solution today is to send data to the cloud — a suboptimal or outright infeasible approach.
How does ABR solve this? ABR’s groundbreaking technology addresses these challenges by delivering “cloud-sized” high-performance AI on compact, ultra-low-power devices. This shift is transforming industries such as consumer electronics, healthcare, automotive, and a range of industrial applications, where latency, reliability, energy efficiency, and localized intelligence are essential.
What is ABR’s secret sauce? ABR’s unique approach is rooted in computational neuroscience. Co-founded by Dr. Chris Eliasmith, CTO and Head of the University of Waterloo’s Computational Neuroscience Research Group, ABR leverages a brain-inspired invention called the Legendre Memory Unit (LMU), which was invented by Dr. Eliasmith and his team of researchers. LMUs are provably optimal for compressing time-series data—like voice, video, sensor data, and bio-signals—enabling significant reductions in memory usage. Running the
LMU on ABR’s unique processor architecture has created a breakthrough that “kills three birds with one stone” by:
1. Increasing performance,
2. Reducing power consumption by up to 200x, and
3. Cutting costs by 10x.
This is further turbocharged by ABR’s AI toolchain, which enables customers to deploy solutions in weeks instead of months. Time is money, and ABR’s technology allows for advanced on-device functions—like natural language processing—without relying on the cloud. This unlocks entirely new use cases and possibilities.
At the helm of ABR is Kevin Conley, the CEO and a former CTO of SanDisk, alongside Dr. Chris Eliasmith. Together, they bring exceptionally strong leadership across both hardware and software domains—a rare but powerful combination that gives ABR a significant competitive advantage.
ABR’s vision aligns perfectly with our investment thesis and our belief that edge computing and software-hardware convergence represent the next frontier of opportunity in computing. We’re excited to see ABR power billions of devices in the years to come.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
In the past few days, Eva and I had the privilege of joining the University of Toronto delegation in Stockholm to celebrate University Professor Emeritus Geoffrey Hinton, the 2024 Nobel Laureate in Physics. The events, organized by the University, were a fitting tribute to Professor Hinton’s groundbreaking contributions to AI, a technology that will transform our world in the decades to come.
The celebration was a blend of thoughtful discussions, historic venues, and memorable moments. It all began with a birthday party for Professor Hinton, followed by a fireside chat, an inspiring dinner at the iconic Vasa Museum, and a panel exploring Canada’s leadership in AI at the Embassy of Canada to Sweden. Each event underscored not only Professor Hinton’s remarkable achievements but also the global impact of Canadian innovation in AI and technology more broadly.
Rather than recount every detail, I’ll let the pictures and their captions tell the story of this extraordinary week. It was an incredible opportunity for us to honour a visionary scientist.
Eating birthday cake with University of Toronto President Meric Gertler and Dean, Faculty of Arts & Science at University of Toronto Melanie Woodin.This was the chip that was built for Professor Hinton in the late 80s for him to test his artificial neural network.The chip was developed before sub-micron technology was widely available. Professor Hinton believes it might be 3-5 microns, but even he wasn’t 100% sure. Upon closer inspection, it appears there were six neurons on the grid.Taking a picture with U of T President Meric Gertler and Chancellor Wes Hall and Professor Leah Cowen.We are dining in front of the unique and well preserved warship Vasa from 1628!Fireside chat with University Professor Emeritus Geoffrey Hinton, and Patchen Barss, science journalist, speaker and author.Taking a picture with Untether AI co-founder Raymond Chik and Vector Institute CEO Tony Gaffney at the reception after the fireside chat. An insightful panel moderated by Professor Leah Cowen. Panellists included Professor Eyal de Lara, Vector Institute CEO Tony Gaffney, Professor David Lie and Professor Amy Loutfi.Ericsson’s Head of AI Jörgen GustafssonView Jörgen Gustafsson and Jason LaTorre, the Ambassador of Canada to Sweden.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Important: Before continuing, read SRTX‘s CEO Katherine Homuth’s posts first (here and here).
Hi Katherine,
I read your blog posts about your current challenges and future plans. Originally, I planned to reply to you privately, but in the end, I decided to share my response as an open letter on my blog.
First of all, if you think I’m going to give you any advice, you’d be mistaken.
Why? Because I don’t think I’m qualified. I have never built a company that reinvented the textile industry. Unless I have “been there, done that,” you shouldn’t listen to me — even though TSF has been an investor in SRTX since the early days.
That said, there are numerous similarities between SRTX and Wattpad. One lesson I learned might be useful to you.
Both SRTX and Wattpad set out to reinvent industries that had remained largely unchanged for the past century. Wattpad raised over $100M USD and lost millions per year to build the business’s foundation — overcoming the chicken-and-egg problem — before we could monetize profitably. That had been our strategy from day one, and it was hard to explain on a spreadsheet. From the outside, it looks like it’s all wins. From the inside, we don’t know if the next leap forward will be our last.
Sound familiar? Like you mentioned, SRTX also raised well over $100M USD and lost millions of dollars to build the foundation of the business — overcoming the chicken-and-egg problem — before you could monetize profitably. That’s been your strategy from day one, and it was hard to explain on a spreadsheet. From the outside, it looks like it’s all wins. From the inside, you don’t know if the next leap forward will be your last.
When an entrepreneur is building a transformative company in an unconventional way, they will inevitably attract a lot of naysayers. These naysayers are usually missing key context (which is fine, as you don’t have to convince everyone), give unsolicited bad advice (which is uncool but typical of armchair coaches trying to look smart), and fail to recognize that there’s more than one way to build a massively successful company.
Here’s an example.
A few months after Wattpad was acquired, someone said to me:
“Congrats on your acquisition. But you could have been more capital-efficient. Compared to most B2B SaaS companies, your exit value relative to capital raised was not as high as it could be.”
WTF? He might as well have said McDonald’s generates more revenue than you.
Of course, we all know the proper benchmark is to compare Wattpad to other consumer companies like Snap, Twitter, or Facebook. In fact, Wattpad was massively more capital efficient — both on a per-user basis and an exit-value basis — than most other consumer companies at similar or larger scales. In some cases, we were ahead by an order of magnitude.
I wasn’t angry, upset, or offended by this ignorance, naivety, or arrogance because, over the years, I’ve had to deal with many naysayers — even after Wattpad’s successful exit.
Here’s the important lesson I learned:
Naysayers will always naysay.
They want to make themselves look smart.
They want to feel superior to you.
They don’t want to admit they were wrong, so they continue to naysay.
Most people don’t believe in moonshots because they can’t do what you do.
If you can use them to fire yourself up, that’s great. If not, don’t even spend a millisecond on them. Your time and energy are better spent focusing on finding a handful of new investors who believe in your vision, growing a fanbase that loves your product, and scaling your company. These are what you have been doing. The results will speak for themselves.
If anything, SRTX has de-risked so much over the years. Millions of people are already buying your unbreakable tights. It’s the best-selling tight in North America — unbreakable or not. A lot of capital has been raised, enabling your mega factory to become a reality. Major B2B partnerships have been formed to scale. New products, beyond tights, are soon to launch.
You’re very close to the top of Mount Everest. Who cares about those people who don’t dare to leave base camp?
Best,
Allen
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Note: One of the most common pieces of feedback we receive from entrepreneurs is that TSF partners don’t think, act, or speak like typical VCs. The Contrarian Series is meant to demystify this, so founders know more about us before pitching.
For Wattpad, it was exactly ten years between raising our first round of venture capital in 2011 and the company’s acquisition in 2021. Over that decade, we discussed countless topics in our board meetings.
But one topic we never discussed? Exit strategies.
I distinctly remember, a couple of years before the acquisition, I raised the question to a board member. “We’ve been venture-backed for almost ten years now. Should we start talking about exit…”
I couldn’t even finish the sentence. That board member cut me off:
“Allen, I just want you to build a great company.”
That moment stuck with me. Only after the acquisition did I fully appreciate the significance of those ten years as a venture-backed company without focusing on an exit.
Wattpad’s four largest investors—USV, Khosla Ventures, OMERS, and Tencent—enabled us to focus on building the business, not selling it. OMERS, as a pension fund, and Tencent, as a strategic investor, don’t operate under the typical 10-year fund cycle that drives many venture firms to push for exits. USV, with its consistent track record of generating world-class returns, had the trust of its LPs to prioritize long-term value over short-term outcomes. And Khosla Ventures? Well, no one can tell Vinod Khosla what to do, and he loves making big, long-term bets.
Their perspectives freed us to focus on building a great company rather than prematurely worrying about how to sell it.
In early 2020, a year before Wattpad was acquired for US$660M, we set an ambitious company objective: to become “Investment Ready.” This meant ensuring we could scale profitably and confidently project $100M+ in revenue with a minimum of 40% year-over-year growth. By the end of 2020, we wanted to be in a position to choose between preparing for an IPO (we even reserved our ticker symbol WTPD), raising growth capital to accelerate expansion, or scaling organically without any additional funding.
When an inbound acquisition offer came in mid-2020, this optionality proved invaluable. It allowed us to run a proper process with multiple interested parties. We were clear with potential acquirers: our preference was to remain independent. If the offer wasn’t higher than the value we could command through an IPO, we weren’t interested, and we would walk away. Because we had the fundamentals to back it up, no one doubted us.
This underscores an important point: the best way to generate a great outcome is to build an amazing business. Focus on creating value, and optionality will follow.
Any CEO who claims to have an exit strategy—especially in the early stages—is either naïve, disillusioned, or lying.
Here’s the reality: M&A is far less common than people think. The pool of serious potential acquirers often narrows to just a handful in the best-case scenarios. And even then, the stars have to align—you need the right timing, the right strategic fit, and the right price. It’s easier said than done.
Of course, that doesn’t mean I ignored the idea of acquisition entirely (and founders should consider M&A, but only under the right circumstances, and I will save it for another blog post). For instance, we built relationships with potential strategic acquirers and stayed aware of the landscape. But the time I spent on this was minimal. Even my leadership team occasionally asked why I never talked about M&A. The answer was simple: it wasn’t a priority.
Too many founders overthink their “exit strategy,” and it often backfires. Changing their product to appeal to a potential acquirer? Building one-sided partnerships in the hope they’ll buy the company? Hope is not a strategy.
The same goes for VCs. Some overthink their portfolio companies’ “exit strategy” because they worry about selling before the 10-year fund window closes. While this concern is valid, it doesn’t mean they should push their best portfolio companies to sell. There are many ways for VCs to liquidate their positions without forcing a sale. Ironically, the best way for a founder to help their investors exit is to focus on increasing enterprise value. Shares in a great company are always in demand.
For an early-stage startup, having an exit strategy is as absurd as asking an infant to decide which jobs they’ll apply to after university. The founders’ job is to nurture that infant—raise them into a great human being. The results will follow.
Build a great business, and everything else will fall into place. There’s an old saying: Great companies get bought, not sold. It couldn’t be more true.
P.S. Founders, if you have an exit strategy slide in your pitch deck, please remove it before pitching to us. TYSM!
P.P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
I was fortunate to not only learn from his textbook but also to be a student in his class. Few have the privilege of learning directly from a legend, and I consider myself incredibly lucky to have been in the right place at the right time—more than 30 years ago—to benefit from his lectures.
Who am I talking about? Professor Adel Sedra.
I wanted to take a moment to congratulate Professor Sedra on the recognition of his incredible legacy with the launch of a new permanent exhibit at the University of Toronto. His textbook, Microelectronic Circuits, co-authored with the late Professor Kenneth C. Smith, has been a cornerstone of engineering education for decades. To date, it has gone through eight editions (with Professor Tony Chan Carusone also part of the editorial team), sold more than a million copies, and been translated into nearly a dozen languages.
Here’s a fact I only recently discovered: it’s estimated that over three-quarters of electrical engineers in the world since 1982 have studied this book—yes, 75%!—widely known as “Sedra/Smith” after its authors.
“When they first sat down in 1982 to create the first draft, I don’t think either of the two co-authors fully realized that it would become the gold standard in the field,” said Christopher Yip, Dean of U of T Engineering.
As a professor, Professor Sedra was simply unparalleled in the field of microelectronics. His passion for teaching was evident, and his exams? They were tough—though I like to think I did alright! 😉
Watching this video gave me goosebumps.
As a 20-year-old at the time, I didn’t fully comprehend or appreciate that I was sitting in a classroom with a legendary professor, studying one of the earlier editions of what would become a truly iconic textbook.
Professor Sedra’s contributions to engineering education and his impact on generations of students are unmatched. This exhibit is a fitting tribute to a man who shaped how the world learns about microelectronics.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
There are three distinct phases in the journey of building a great tech company: technology, product, and commercialization. These phases are sequential yet interconnected and sometimes overlap. Needless to say, mastering each is critical to the company’s eventual success. However, it’s important to recognize their differences.
• Building technology is about founders creating what they love. It’s driven by passion and expertise and often leads to groundbreaking innovations.
• Building a product is about creating something others love to use. This is where usability and solving real problems come into focus.
• Commercialization is about building something people will pay for and driving revenue. This phase transforms users into paying customers or finds someone else to pay for it, such as advertisers.
These phases are related but distinct. Great technology doesn’t guarantee anyone will use it, and a widely-used product doesn’t always lead to revenue. I’ve seen many technologists create incredible technologies no one adopts, as well as popular products that fail to commercialize effectively (though it’s rare for a product with tens of millions of users to fail entirely).
For deep tech companies, these phases often have minimal overlap and unfold sequentially. The technology might take years to develop before a usable product emerges, and commercialization may come even later.
In contrast, shallow tech B2B SaaS products often see complete overlap between the phases. For example, a subscription model is typically apparent from the outset, and the tech, product, and commercialization phases blend seamlessly.
Wattpad is also a good example of how these phases can play out differently. Initially, we built our technology and product hand in hand, creating a platform loved by millions of users. However, its commercialization—whether through ads, subscriptions, or movies, the three revenue models we had—was deliberately delayed. Many people assumed we didn’t know how to make money without understanding this counterintuitive approach (but of course, we purposely kept some of our strategies under wraps). This approach allowed us to use “free” as a potent weapon to dominate—and eliminate—our competitors in a winner-takes-all strategy. Operating for years with minimal revenue was clearly the right decision for the market dynamics and our long-term goals. More on this in a separate blog post.
Given this variability, asking, “What is your revenue?” must be thoughtful and context-specific. For some companies, the absence of revenue may be an intentional and brilliant strategy. For others, insufficient revenue could signal serious trouble. It all depends on the company’s stage, strategy, and goals. Understanding the sequence, timing, and specific needs of a business model is crucial for both investors and entrepreneurs. Zero revenue could be a blessing in the right context. On the other hand, pushing for revenue growth—let alone the wrong type of revenue growth—can be fatal, a scenario we’ve seen many times.
At Two Small Fish Ventures, we are very thoughtful and experienced investors. We understand that starting to generate revenue—or choosing not to generate revenue—at the right time is one of the secrets to success that very few people have mastered. We practise what we preach. Over the past two years, all but one of TSF’s investments have been pre-revenue.
No revenue? No problem. In fact, that’s great. Bring them on!
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Those who know me well would tell you I am a pretty boring person. I don’t have many hobbies, but one thing I do love is gadgets. For instance, I’m a big fan of DIY home automation. Practically every electronic device in my house is voice-controlled, automated, and Wi-Fi-connected—if it can be, it probably is. Here’s a fun example:
I love robots doing things for me because, frankly, I’m too busy.
At this rate, I might run out of IP addresses! Sure, I could change my network’s subnet to enable more, but every time I tinker with my setup, I have to invest time getting everything right again—something I don’t have in abundance. Anyway, I digress.
One gadget I’ve wanted for years but hesitated to get is a home energy storage and backup system, like Tesla’s Powerwall. The Powerwall 2 has been around since 2016, but for years, the Powerwall 3 was “just around the corner,” with rumours of its launch “next month” seemingly every month. I didn’t want to invest in a device I planned to use for a decade only for it to become obsolete right after I bought it.
Finally, the wait is over. Powerwall 3 became available earlier this year, and I’m glad I waited. Its specs—peak power, continuous power, and efficiency—are significantly upgraded from Powerwall 2. That said, I was a little disappointed that its battery capacity remained unchanged.
I’m told this was the first Powerwall 3 installation in Canada, which is pretty exciting! It’s a beautiful piece of technology, though I don’t see much of it since it’s tucked away in the basement. Paired with solar panels, I hope to “off the grid” as much as possible.
As good as the Powerwall 3 is, it’s only part of the solution. While it handles storage and backup very well, it doesn’t provide fine-grained energy monitoring, let alone control. To address this, I also installed a Sense energy monitor. This device, connected to the electrical panel, collects real-time data from electrical currents to identify unique energy signatures for every appliance and device in the home. It’s a hack, a retrofit solution and imperfect, but it’s probably the best option for someone like me, who is entrenched in the Tesla ecosystem.
The energy space hasn’t changed much in the past half-century. Take the electric panel, for example—it’s still essentially the same analog system I remember from my childhood. However, with the rapid acceleration of the energy transition, smarter energy systems are becoming critical as hardware and software converge to enable new possibilities.
A big thanks to James and Dave from the Borealis Clean Energy team for helping me with this project —and for arriving in style with Canada’s first Cybertruck. The project has so many moving parts. Their expertise made this journey much smoother.
Unboxing PW3!Zooming in to the power electronics.The electricians are working hard. It is a big job!It is done!A big thank you to James.This is the Tesla Gateway, a separate box we need to install. It is a smaller box—roughly a quarter of the size of PW3—and where “the brain” is located. Adding Sense – the orange box – to my old-school electric panel to help me with device-level monitoring.First Cybertruck in Canada. This thing draws attention.
In previous blog posts (here and here), I’ve delved into the mathematical model for constructing an early-stage VC portfolio designed to achieve outsized returns. In short, investing early to build a concentrated portfolio of fewer than 20 moonshot companies, each with the potential for 100x returns or more, is the way to go.
The math is straightforward—it doesn’t lie. Not adhering to this model can significantly reduce the likelihood of achieving exceptional returns.
However, simply following this model is not enough to guarantee outsized results. Don’t mistake correlation for causation! The real challenge lies in identifying, evaluating, and supporting these “100x” opportunities to help turn their vision into reality.
At TSF, we use a simple framework to evaluate whether a potential investment can meet the 100x criteria:
10x (early stage) x 10x (transformative behaviour) = 100x conviction
The first “10x” is straightforward: We invest when companies are in their earliest stages. For instance, over the past two years, all but one of TSF’s investments have been pre-revenue. This made financial analysis simple—those spreadsheets were filled with zeros!
Many of these companies are also pre-traction. While having traction isn’t a bad thing, savvy investors shouldn’t rely on it for validation. The reason is simple: traction is visible to everyone. By the time it becomes apparent, the company is often already too expensive and out of reach.
At TSF, we have a unique advantage. Before transitioning to investing, all TSF partners were engineers, product experts, successful entrepreneurs, and operators—including a “recovering CEO”—that’s me! Each partner brings distinct domain expertise, collectively creating a broad and deep perspective. This allows us to invest only when we possess the domain knowledge needed to fully evaluate an opportunity. We “open the hood” to determine whether the technology is genuinely unique, defensible, and disruptive, or whether it is easily replicable. If it’s the latter, we pass quickly. A strong, defensible tech moat is a key criterion for us. This approach means we might pass on some promising “shallow-tech” opportunities, but we’re very comfortable with that. After all, we believe the best days of shallow tech are behind us.
Maintaining a concentrated portfolio allows us to commit only to investments where we have unwavering conviction. In contrast, a large portfolio would require us to find a large number of 100x opportunities and pursue those we might not fully believe in. Frankly, I wouldn’t sleep well if we took that route. This route would also make it difficult to provide the meaningful, tailored support we’ve promised our entrepreneurs (more on that in a future post).
When evaluating product potential, we look beyond the present. At TSF, we assess how a technology might reshape the landscape over the next decade or more. We start by understanding the intrinsic needs of the user and envision how a product could fundamentally change customer or end-user behaviour. This is crucial: if a product that addresses a massive opportunity has a strong tech moat, first-mover advantages, and the ability to change behaviour while facing few viable alternatives, it can unlock significant new value and create a defensible, category-defining business.
This often translates into substantial commercialization potential. If we can foresee how the product might evolve into adjacent markets (its second, third, or even fourth act) with almost uncapped possibilities, we achieve the “holy trinity” of tech-product-commercialization potential—forming the second 10x of our conviction.
Here’s how we describe it:
Two Small Fish Ventures invests in early-stage products, platforms, and protocols that transform user behaviour and empower businesses and individuals to unlock new, impactful value.
This thesis underpins our investment decisions and ensures that each choice we make aligns with our long-term vision for transformative innovation.
While this framework may sound simple, executing it well is extremely difficult. It requires what I call a “crystal ball” skill set that spans the full spectrum of entrepreneurial, technical, product, and operational backgrounds.
Over the past decade, we’ve built a portfolio of more than 50 companies across three funds. By employing this approach, the entrepreneurs we’ve supported have achieved numerous breakout successes. This post outlines our “secret sauce,” and we will continue to leverage it.
As you can see, early-stage VC is more art than science. To do it well requires thoughtfulness, insight, and the ability to envision the future as a superpower. It’s challenging but incredibly rewarding. I wouldn’t trade it for anything.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
More than two decades ago, before I started my first company, I was involved with an internet startup. Back then, the internet was still in its infancy, and most companies had to host their own servers. The upfront costs were daunting—our startup’s first major purchase was hundreds of thousands of dollars in Sun Microsystems boxes that sat in our office. This significant investment was essential for operations but created a massive barrier to entry for startups.
Fast forward to 2006 when we started Wattpad. We initially used a shared hosting service that cost just $5 per month. This shift was game-changing, enabling us to bootstrap for several years before raising any capital. We also didn’t have to worry about maintaining the machines. It dramatically lowered the barrier to entry, democratizing access to the resources needed to build a tech startup because the upfront cost of starting a software company was virtually zero.
Eventually, as we scaled, we moved to AWS, which was more scalable and reliable. Apparently, we were AWS’s first customer in Canada at the time! It became more expensive as our traffic grew, but we still didn’t have to worry about maintaining our own server farm. This significantly simplified our operations.
A similar evolution has been happening in the semiconductor industry for more than two decades, thanks to the fabless model. Fabless chip manufacturing allows companies—large or small—to design their semiconductors while outsourcing fabrication to specialized foundries. Startups like Blumind leverage this model, focusing solely on designing groundbreaking technology and scaling production when necessary.
But fabrication is not the only capital-intensive aspect. There is also the need for other equipment once the chips are manufactured.
During my recent visit to ventureLAB, where Blumind is based, I saw firsthand how these startups utilize shared resources for this additional equipment. Not only is Blumind fabless, but they can also access various hardware equipment at ventureLAB without the heavy capital expenditure of owning it.
Let’s see how the chip performs at -40C!
Jackpine (first tapeout)
Wolf (second tapeout)
BM110 (third tapeout)
The common perception that semiconductor startups are inherently capital-intensive couldn’t be more wrong. The fabless model—in conjunction with organizations like ventureLAB—functions much like cloud computing does for software startups, enabling semiconductor companies to build and grow with minimal upfront investment. For the most part, all they need initially are engineers’ computers to create their designs until they reach a scale that requires owning their own equipment.
Fabless chip design combined with shared resources at facilities like ventureLAB is democratizing the semiconductor space, lowering the barriers to innovation, and empowering startups to make significant advancements without the financial burden of owning fabrication facilities. Labour costs aside, the upfront cost of starting a semiconductor company like Blumind could be virtually zero too.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
When it comes to watches, my go-to is a Fitbit. It may not be the most common choice, but I value practicality, especially when not having to recharge daily is a necessity to me. My Fitbit lasts about 4 to 5 days—decent, but still not perfect.
Now, imagine if we could extend that battery life to a month or even a year. The freedom and convenience would be incredible. Considering the immense computing demands of modern smartwatches, this might sound far-fetched. But that’s where our portfolio company, Blumind, comes into play.
Blumind’s ultra-low power, always-on, real-time, offline AI chip holds the potential to redefine how we think about battery life and device efficiency. This advancement enables edge computing with extended battery life, potentially lasting years – not a typo – instead of days. Products powered by Blumind can transform user behaviours and empower businesses and individuals to unlock new and impactful value (see our thesis).
Blumind’s secret lies in its brain-inspired, all-analog chip design. The human brain is renowned for its energy-efficient computing abilities. Unlike most modern chips that rely on digital systems and require continuous digital-to-analog and analog-to-digital conversions (which drain power), Blumind’s approach emulates the brain’s seamless analog processing. This unique architecture makes it perfect for power-sensitive AI applications, resulting in chips that could be up to 1000 times more energy-efficient than conventional chips, making them ideal for edge computing.
Blumind’s breakthrough technology has practical and wide-ranging applications. Here are just a few use cases:
• Always-on Keyword Detection: Integrates into various devices for continuous voice activation without excessive power usage.
• Rapid Image Recognition: Supports always-on visual wake word detection for applications such as access control, enhancing human-device interaction with real-time responses.
• Time-Series Data Processing: Processes data streams with exceptional speed for real-time analysis in areas like predictive maintenance, health monitoring, and weather forecasting.
These capabilities unlock new possibilities across multiple industries, including wearables, smart home technology, security, agriculture, medical, smart mobility, and even military and aerospace.
A few weeks ago, I visited Blumind’s team at their ventureLAB office and got an up-close look at their BM110 chip, now in its third tapeout. Blumind exemplifies the future of semiconductor startups through its fabless model, which significantly lowers the initial infrastructure costs associated with traditional semiconductor companies. With resources like ventureLAB supporting them, Blumind has managed to innovate with remarkable efficiency and sustainability. (I’ll share more about the fabless model in an upcoming post.)
I’m thrilled to see where Blumind’s journey leads and how its groundbreaking technology will transform daily life and reshape multiple industries. When devices can go years without needing a recharge instead of mere hours, that’s nothing short of game-changing.
Image: Close-up view of BM110. It is a piece of art!
Image: Qualification in action. Note that BM110 (lower-left corner) is tiny and space-efficient.
Image: The Blumind team is working hard at their ventureLAB office. More on this in a separate blog post here.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
We’re thrilled to share that Printify, a company we have proudly backed since its first funding round, has entered into a merger with Printful (see report by TechCrunch). As long-time supporters of the Printify team, we at Two Small Fish Ventures are incredibly happy with this outcome, which marks a significant milestone in the production-on-demand industry and an exciting moment for everyone involved.
Printify and Printful are both leading platforms that empower entrepreneurs and businesses to create and sell custom products worldwide without the need to hold inventory, thanks to their advanced production-on-demand fulfillment networks. Printify has been growing rapidly, now boasting a team of over 700 employees. Combined with Printful’s team, the newly merged company will have well over 2,000 employees, making it by far the number one player in the production-on-demand market.
Printful, with over $130 million raised and a valuation exceeding $1 billion, and Printify, backed by $54.1 million in funding, have established themselves as the top two global leaders in this field. This merger solidifies their position as the dominant force in the industry, setting new standards and driving innovation in production-on-demand services worldwide. We’re proud to have supported Printify from the very beginning and look forward to witnessing the next chapter in their remarkable journey.
P.S. In true spirit of unity, founders Lauris Liberts and James Berdigans have sealed the deal by swapping T-shirts with each other’s logos—because nothing says “teamwork” like wearing the competition’s brand!
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
In 2006, Wattpad started as a simple mobile reading app, mainly for classic books. Fifteen years later, it evolved into a global, AI-powered, multi-platform entertainment company with numerous blockbusters before being acquired.
As you can imagine, my role as CEO at the start of Wattpad—when it was just the co-founders and a few hundred users—was drastically different from leading a team of hundreds of employees and overseeing a platform with 100 million users.
A Typical Entrepreneur’s Evolution
In the early years, the founders focused solely on building a product and finding product-market fit, with little thought given to the business side. At this stage, the CEO is the engineer writing code, the product manager, and the product visionary, all rolled into one.
As traction builds and product-market-fit comes into sight, the CEO’s role begins to shift. Suddenly, hiring becomes a priority, and managing people and operations takes center stage. The CEO goes from being a product builder to a hiring and people manager who leads a small, close-knit team and handles the operations that come with it.
Fast forward another phase, and the company is growing even faster. Now, the CEO is no longer just a manager but the manager of managers, responsible for hiring leaders who can build and lead their own teams. Communication becomes an even more critical skill, as the CEO now leads a much larger team—many of whom don’t frequently interact with the CEO. Business models become increasingly crucial, and new tasks, like fundraising, take on greater importance.
As growth continues, the CEO’s role shifts yet again, this time to hiring leaders of leaders—or even leaders of leaders of leaders. Now, the CEO is juggling closing million-dollar sales with key customers, navigating strategic partnerships, working with the CFO to manage finances at scale, media interviews, building the brand, international expansion, raising capital from large institutional investors, and, of course, leading hundreds or thousands of employees. The skill set required here is worlds apart from that of the early days of coding and prototyping.
Entrepreneurship Is Constant Reinvention
Each phase of a company’s growth requires a radically different skill set: moving from building the idea to scaling a product, building the team, leading a large organization, and eventually creating a profitable business. The entrepreneur evolves from crafting the “secret sauce” to building a factory to mass-produce it.
I have yet to meet an entrepreneur who possessed all these skills from the start. The journey demands constant learning—whether it’s coding, product design, finances, fundraising, marketing, sales, or leadership.
I can testify to this: there were numerous times when I thought the company was a well-oiled machine. Six months later, things would feel like they were falling apart. It wasn’t because I had messed up, but because the environment had changed drastically in such a short time. I had to keep upping my game to keep pace with the company. I am completely different from—and better than—the version of myself a decade ago—and not just once, but many times over.
As an entrepreneur, be prepared. As your company scales, you’re effectively getting a new job every few months. This journey is thrilling and challenging, and filled with lifelong learning and self-improvement.
The Biggest Takeaway
And yet, the most important product you’re building isn’t your company’s product. It isn’t even the company—it’s yourself.
If, every two years, you’re not almost unrecognizable from your former self, you’re not growing fast enough, and you will be left behind by your own fast-growing company.
This takeaway isn’t just for CEOs. It applies to anyone working at a fast-scaling company and to anyone with a growth mindset. If you get this right, everything else will follow, and you’ll be in good shape. From my experience, this is one of the most crucial mindset-building tools you can have.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
More than two decades ago, I co-founded my first company, Tira Wireless. The business went through several iterations, and eventually, we landed on building a mobile content delivery product. We raised roughly $30M in funding, which was a significant amount at the time. We even ranked as Canada’s Third Fastest Growing Technology Company in the Deloitte Technology Fast 50.
We had a good run, but eventually, Tira had to shut its doors.
We made numerous strategic mistakes, and I learned a lot—lessons that, quite frankly, helped me make far better decisions when I later started Wattpad.
One of the most important mistakes we made was falling into the “bridge technology” trap.
What is the “bridge technology” trap?
Reflecting on significant “platform shifts” over recent decades reveals a pattern: each shift unleashes waves of innovation. Consider the PC revolution in the late 20th century, the widespread adoption of the internet and cloud computing in the 2000s, and the mobile era in the 2010s. These shifts didn’t just create new opportunities; they also created significant pain points as the world tried to leap from one technology to another. Many companies emerged to solve problems arising from these changes.
Tira started when the world began its transition from web to mobile. Initially, there were countless mobile platforms and operating systems. These idiosyncrasies created a huge pain point, and Tira capitalized on that. But in a few short years, mobile consolidated into just two major players—iOS and Android. The pain point rapidly disappeared, and so did Tira’s business.
Similarly, most of these “bridge technology” companies perform very well during the transition because they solve a critical, short-term pain point. However, as the world completes the transition, their business disappears. For instance, numerous companies focused on converting websites into iPhone apps when the App Store launched. Where are they now?
Some companies try to leverage what they’ve built and pivot into something new. But building something new is challenging enough, and maintaining a soon-to-be-declining bridge business while transitioning into a new one is even harder. This is akin to the innovator’s dilemma: successful companies often struggle with disruptive innovation, torn between innovating (and risking profitable products) or maintaining the status quo (and risking obsolescence).
As an investor, it makes no sense to invest in a “bridge” company that is fully expected to pivot within a few years. A pivot should be a Plan B, not Plan A. It’s extremely rare for bridge technology companies to become great, venture-scale investments. In fact, I can’t think of any off the top of my head.
We are currently in the midst of a tectonic AI platform shift. We’re seeing a huge volume of pitches, which is incredibly exciting. Many of these startups built great technologies and products. However, a significant number of these pitches also represent bridge technologies. As the current AI platform shift matures, these bridge technologies will lose relevance. Sometimes, it’s obvious they’re bridge technologies; other times, it requires significant thought to identify them. This challenge is intellectually stimulating, and I enjoy every moment of it. Each analysis informs us of what the future looks like, and just as importantly, what it will not look like. With each passing day, we gain stronger conviction about where the world is heading. It’s further strengthening our “seeing the future is our superpower” muscle, and that’s the most exciting part.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
#paid was one of the first investments we made at Two Small Fish Ventures. It’s been over a decade since we backed Bryan and Adam, who were still working out of Toronto Metropolitan University’s DMZ at the time. They had a vision to build a platform that connected creators and brands before “creator” was even a term! Back then, influencer and creator marketing campaigns were just tiny experiments.
A decade later, the creator economy has taken off. It’s now a $24 billion market—an order of magnitude larger than just a few years ago, with no signs of slowing down. The next wave of growth is still ahead as ad spending continues to shift away from traditional media. With the global ad market approaching $800 billion, one thing remains true: ad dollars follow the eyeballs—always. And where are those eyeballs today? On creators and influencers.
Today, #paid has become the world’s dominant platform, with over 100,000 creators onboard. It addresses a significant challenge: most creators don’t know how to connect with brands, especially iconic brands like Disney, Sephora, or IKEA. On the other hand, brands struggle to find the right creators amidst a sea of talent. #paid bridges this gap, acting as the marketplace that makes collaboration easy. They use data-driven insights to determine what makes a successful match, ensuring that both creators and brands can find each other effortlessly.
At #paid, brands and creators work with a dedicated team of experts to build creative strategies backed by research, first-party data, and industry benchmarks. This means campaigns run smoothly, allowing creators to focus on doing what they love—creating—without getting bogged down by administrative tasks.
I’m not just speaking as an investor—I’ve actually run a campaign with #paid as an influencer myself, and I can personally vouch for how seamless the experience was.
If you think #paid is all about TikTok, Snap, or Instagram, think again. Brands leverage #paid content across every platform. Want proof? Just check out the Infiniti TV commercial, which came from a #paid campaign.
How about billboards in major cities like NYC, Toronto, and more? #paid has that covered too.
#paid also brings creators and marketers together in real life. I had the privilege of speaking at their Creator Marketing Summit in NYC a few weeks ago, and I was amazed at how far #paid has come. The summit brought together hundreds of creators and top brand marketers—an impressive showcase of the platform’s evolution.
Looking back on this journey, here are my key takeaways:
• Great companies take a decade to build.
• To create a category leader, especially in winner-take-all markets, the idea has to be bold and often misunderstood at first. Bryan and Adam saw something that few others did, and their first-mover advantage has solidified #paid’s leading position today.
• There’s no such thing as “done.” #paid constantly reinvents itself. Generative AI is another exciting opportunity for step-function growth, and I can’t wait to see what’s next.
Bryan and Adam should be incredibly proud of what they’ve accomplished.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Early-stage venture capital (VC) has always been the oddball in asset management. Unlike other asset classes, it offers the highest potential returns, but it also comes with the highest variance—especially when portfolio construction isn’t done right. On top of that, it has an inherent “default rate” of about 80%.
Tell a traditional fund manager about this 80% default rate, and you’ll likely get a strange look.
A few months ago, I was trying to explain how VC works to a fund manager. After covering the usual points—how VC is essentially a home run derby with many misses—he paused and said, “I get it. VC is like buying call options on startups.”
I hadn’t considered it that way before, but he was absolutely right.
For those unfamiliar, buying a call option gives you the right, but not the obligation, to purchase a stock at a predetermined price (the strike price) before a specified expiration date. Investors use this strategy to profit from an anticipated—but not guaranteed—increase in the stock’s price. If the stock price rises above the strike price (plus the premium paid), the option becomes profitable. The potential profit is theoretically unlimited, while the maximum loss is limited to the premium paid.
Similarly, investing in a startup gives you the chance to acquire equity at an attractive price, with a ~20% chance the startup will take off—though this usually takes about a decade to materialize. VCs use this strategy to profit from a potential—but not guaranteed—rise in the company’s value. If the startup succeeds and its valuation soars beyond the investment (plus associated costs), the return can be massive. The potential profit is virtually unlimited if the company becomes a breakout success, while the maximum loss is limited to the initial investment.
VC and call options are strikingly similar, don’t you think? They’re like twins!
From now on, I’ll tell people: Venture capital is call options on startups.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
TLDR – 20 companies in a VC portfolio is the optimal balance between risk and reward, offering a very high chance of hitting outsized returns without significant risk of losing money. This is exactly the approach we follow at Two Small Fish Ventures, as we keep our per-fund portfolio size limited to roughly 20 companies.
In my previous post, VC is a Home Run Derby with Uncapped Runs, I illustrated mathematically why early-stage venture funds’ success doesn’t hinge on minimizing failures, nor does it come from hitting singles (e.g., the number of “3x” companies). These smaller so-called “wins” are just noise.
As I said:
“Venture funds live or die by one thing: the percentage of the portfolio that becomes breakout successes — those capable of generating returns of 10x, 100x, or even 1000x.”
To drive high expected returns for VCs, finding these breakout successes is key. However, expected value alone doesn’t tell the full story. We also need to consider variance. In simple terms, even if a fund’s expected return is 5x or 10x, it doesn’t necessarily mean it’s a good investment. If the variance is too high—meaning the fund has a low probability of achieving that return and a high probability of losing money—it would still be a poor bet.
For example, imagine an investment opportunity that has a 10% chance of returning 100x and a 90% chance of losing everything. Its expected return is 10x (i.e., 10% x 100x + 90% x 0x = 10x). But despite the attractive expected return, it’s still a terrible investment due to the extremely high risk of total loss.
That said, there’s a time-tested solution to turn this kind of high-risk investment into a great one: diversification. While everyone understands the importance of diversification, the real key lies in how it’s done. By building a properly diversified portfolio, we can reduce variance while maintaining a high expected return. This post will illustrate mathematically how the right portfolio construction allows venture funds to generate outsized returns while ensuring a high probability of success.
Moonshot Capital vs. PlayItSafe Capital: A Quick Recap
Let’s start by revisiting our two hypothetical venture capital firms: Moonshot Capital and PlayItSafe Capital. Moonshot Capital swings for the fences, aiming to find the next 100x company while expecting most of the portfolio to fail. PlayItSafe Capital, on the other hand, protects downside risk (at least that’s what they think), but by avoiding bigger risks, it sacrifices the chance of finding outsized returns.
• Moonshot Capital: Out of 20 companies, 17 resulted in strikeouts (0x returns), 3 companies achieved 10x returns, and 1 company achieved a 100x return.
• PlayItSafe Capital: Out of 20 companies, 7 resulted in strikeouts (0x returns), 7 companies broke even (1x), 5 companies achieved 3x returns, and 1 company achieved a 10x return.
Here’s how their expected returns compare:
• Moonshot Capital has an expected return of 6.5x, thanks to one company yielding 100x and three companies yielding 10x (i.e. (1 x 100 + 3 x 10 +16 x 0) x $1 = $130).
• PlayItSafe Capital has a much lower expected return of 1.6x, with its highest return from one 10x company, five 3x returns, and several breakeven companies (i.e. (1 x 10 + 5 x 3 + 7 x 1 + 7 x 0) x $1 = $32).
Despite these differences in expected returns, what’s surprising is that counterintuitively, the probability of losing money (i.e., achieving an average return of less than 1x at the fund level) is quite similar for both firms.
Let’s dive into the math to see how we calculate these probabilities:
Moonshot Capital: 12.9% Probability of Losing Money
1. Expected Return :
2. Variance :
3. Standard Deviation :
4. Standard Error :
Using a normal approximation, the z-score to calculate P(X < 1) is:
Looking this up in the standard normal distribution table gives us:
P(X < 1) = 0.129 or 12.9%
PlayItSafe Capital: 11.6% Probability of Losing Money
Similarly, looking this up in the standard normal distribution table gives us (sparing you all the equations):
P(X < 1) = 0.116 or 11.6%
Shockingly, these two firms’ probabilities of losing money are essentially the same. The math does not lie!
Here’s a graphical representation of the outcomes (probability density) for Moonshot Capital and PlayItSafe Capital.
Probability Density Graphs: Comparing Moonshot and PlayItSafe
As you can see, Moonshot has higher upside potential, as the density peaks at 6x, while PlayItSafe is more concentrated around lower returns. Since their downside risks are more or less the same while PlayItSafe’s approach significantly limits its upside, counterintuitively PlayItSafe is far riskier from the risk-reward perspective.
Proper Portfolio Construction: How Portfolio Size Affects Returns
To further optimize Moonshot’s strategy, we will explore how different portfolio sizes affect the balance between risk and reward. Below, I’ve analyzed the outcomes (i.e. portfolio size sensitivity) for Moonshot Capital across portfolio sizes of n = 5, n = 10, n = 20, and n = 30.
The graph below shows the probability density curves for Moonshot Capital with varying portfolio sizes:
As you can see, smaller portfolios (n = 5, n = 10) exhibit higher variance, with a greater spread of potential outcomes. Larger portfolios (n = 20, n = 30) reduce the variance but also diminish the likelihood of hitting outsized returns.
Why 20 is the Optimal Portfolio Size
1. Why 20 is Optimal:
At n = 20, Moonshot Capital strikes an ideal balance. The risk of losing money, i.e. P (X < 1), remains manageable at 12.9%, while the probability of outsized returns remains high: 62.1% chance of hitting a return higher than 5x. This suggests that Moonshot’s high-risk, high-reward approach pays off without exposing the fund to unnecessary risk.
2. Why Bigger Isn’t Always Better (n = 30):
When the portfolio size increases to n = 30, we see a significant drop-off in the likelihood of outsized returns. The probability of achieving a return higher than 5x drops significantly from 62.1% at n = 20 to 41.9% at n = 30, and counterintuitively, the risk of losing money starts to increase. This suggests that larger portfolios can dilute the impact of the big wins that drive fund returns. It also mathematically explains why “spray-and-pray” does not work for early-stage investments.
3. The Pitfalls of Small Portfolios (n = 5 and n = 10):
At smaller portfolio sizes, such as n = 5 or n = 10, the variance increases significantly, making the portfolio’s returns more unpredictable. For example, at n = 5, the probability of losing money is significantly higher, and the risk of extreme outcomes becomes more pronounced. At n = 10, the flat-curve suggests that the variance is very high. This high variance means the returns are volatile and difficult to predict, increasing risk.
Conclusion: How to Win the Home Run Derby With Uncapped Runs
The key takeaway here is that Moonshot Capital’s strategy of swinging for the fences doesn’t mean taking on excessive risk. With 20 companies in the portfolio, Moonshot is the optimal between risk and reward, offering a very high chance of hitting outsized returns without significant risk of losing money.
While n=20 is optimal, n=10 is also pretty good, but n=30 is significantly worse. So, a ‘concentrated’ approach – but not ‘n=5 concentrated’ – is far better than ‘spray and pray,’ if you have to pick between the two.
This is exactly the approach we follow at Two Small Fish Ventures. We don’t write a cheque unless we have that magical “100x conviction.” We also keep our per-fund portfolio size limited to roughly 20 companies. This blog post mathematically breaks down one of our many secret sauces for our success.
Don’t tell anyone.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Today’s blog post is brought to you by Eva Lau. She will talk about one of our recent investments: Axiomatic AI.
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Congratulations to Axiomatic on their recent US$6M seed round led by Kleiner Perkins! Two Small Fish Ventures is thrilled to be an early investor since the company’s inception—and the only Canadian investor—in what promises to be a game-changer in solving fundamental problems in physics, electronics, and engineering.
Why is this important? Large Language Models (LLMs) excel at languages (as their name suggests) but struggle with logic. That’s why AI can write poetry but struggles with math, as LLMs mainly rely on ‘pattern-matching’ rather than ‘reasoning.’
This is where Axiomatic steps in. The company’s secret sauce is its new AI model called Automated Interpretable Reasoning (AIR), which combines advances in reinforcement learning, LLMs, and world models. Axiomatic’s mission is to create software and algorithms that not only automate processes but also provide clear, understandable insights to fuel innovation and research, ultimately solving real-world problems in engineering and other industrial applications.
The startup is the brainchild of world-renowned professors from MIT, the University of Toronto, and The Institute of Photonic Sciences (ICFO) in Barcelona. The team includes leading engineers, physicists, and computer science experts.
With its innovative models, the startup fits squarely within our fund’s focus: the next frontier of computing and its applications. As all TSF partners are engineers, product experts, and recent operators, we are uniquely positioned to understand the potential of Axiomatic and support the team.
Axiomatic’s new AIR model is well-positioned to accelerate engineering and scientific discovery, boosting productivity by orders of magnitude in the coming years, and ultimately make the world’s information intelligible.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Co-founded by AI and reinforcement learning luminaries Rich Sutton, Randy Goebel and Joseph Modayil, Openmind is a Canadian non-profit focused on conducting fundamental AI research to better understand minds.
We believe the greatest advancements in AI are yet to come. Basic research is essential to understanding what is scientifically possible before pursuing the next generation of commercial and technological developments.
A key aspect of Openmind is its commitment to open research. Openmind places no intellectual property restrictions on its research, allowing everyone to contribute to and build upon this shared knowledge.
As a board member, I will leverage my decades-long experience in building, operating, and investing in AI companies to support Openmind’s mission. Supporting innovation is one of my life’s passions, and I am thrilled to accept this position and join a team dedicated to pioneering advancements in AI.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
We’re thrilled to share that Toronto-based Viggle AI, a Canadian start-up revolutionizing character animation through generative AI, has raised US$19 million in funding. The round was led by a16z with Two Small Fish participating as a significant investor. As part of the investment, I also became an advisor to the company.
Creators are unleashing their creativity with Viggle AI by generating some of the most entertaining memes and videos online. You’ve probably seen a clip of Joaquin Phoenix’s Joker persona replacing recreating Lil Yachy’s walkout from the Summer Smash Festival – it was made with Viggle AI!
But Viggle AI is much more than a simple meme generator. It’s a powerful platform that can completely reinvent how games, animation, and other videos are produced.
Powered by JST-1, the first-in-the-world 3D-video foundation model with actual physics understanding, Viggle AI can make any character move as you want. Its unique AI model can generate high-quality, realistic, physics-based 3D animations and videos from either static images or text prompts.
For professional animation engineers, game designers, and VFX artists, this is game-changing. Viggle AI can streamline the ideation and pre-production process allowing them to focus on their creative vision and ultimately reduce production timelines.
And, for content creators and everyday users, Viggle AI can generate high-quality animations using simple prompts to create engaging animated character videos within a matter of minutes.
Easier. Faster. Cheaper. Viggle AI is a truly transformative product that will unlock new values for consumers and professionals alike.
Here are a couple of fun examples of Viggle AI in action – I was terrible at dancing, but now I can do it!
Since launching in March, Viggle AI has taken the internet by storm and now boasts over 4 million users. When the startup first landed on our radar it only had 1000s of users. This rapid growth is not only a testament to Viggle AI’s ability to create an engaging product but also Two Small Fish’s ability to spot tech giants in the making.
Two Small Fish has an unparalleled track record of helping create the future of content through technology. After all, the team built Wattpad from a simple app for fiction into a massive global entertainment powerhouse with 100 million users. Seeing the future is our superpower. We’re the best investors to help future tech giants like Viggle AI as they transform how content is created, remixed, customized, consumed, and interacted with. We’re excited to continue to play a role in reinventing content creation and entertainment.
Congratulations Hang Chu and the entire Viggle AI team!
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
The history of computing has been a constant shift of the centre of gravity.
When mainframe computers were invented in the middle of the last century, they were housed in air-conditioned, room-sized metal boxes that occupied thousands of square feet. People accessed these computers through dumb terminals, which were more like black and white screens and keyboards hooked to the computer through long cables. They were called dumb terminals because the smart part was all on the mainframes.
These computers worked in silos. Computer networks were very primitive. Data was mainly transferred through (physical!) punch cards and tapes.
The business model was selling hardware. During that era, giants like IBM and Wang emerged, and many subsequently submerged.
Hardware was the champion.
Mainframe computers in the 50s. Image source: Wikipedia
The PC era, which started in the 80s and supercharged in the 90s, ended the reign of the mainframe era. As computers became much faster while the price dropped by orders of magnitude, access to computing became democratized, and computers appeared on every desktop. We wanted these computers to talk to each other. Punch cards clearly no longer worked as there were millions of computers now. As a result, LANs (local area networks) were popularized by companies like Novell, which enabled the client/server architecture. Unlike the previous era, the “brains” were decentralized, with clients doing much of the heavy lifting. Servers still played a role, but for the most part, it was for centralized storage.
Although IBM invented the PCs, the business models shifted, creating the duopoly of Intel (and by association companies like Compaq) and Microsoft, with the latter capturing even more value than the former. The software era had begun.
Software became the champion. Hardware was dethroned to the runner-up.
Then, in the late 90s to the 2010s, the (broadband) web, mobile, and cloud computing came along. Connectivity became much less of an issue. Clients, especially your phones, continued to improve at a fast pace, but the capability of servers increased even faster. The “brains” shifted back to the server as that’s where the data is centralized. For the most part, clients were now responsible for user experience, important but merely a means to an end (of collecting data) rather than an end in themselves.
Initially, it appeared that the software-hardware duopoly would continue as companies like Netscape and Cisco were red hot, only to be dethroned by companies like Yahoo and AOL and later Google and Meta. Software and hardware were still crucial, but they became the enablers as the business model once again shifted.
Data became the newly crowned champion.
Fast forward to now, the latest—and arguably the greatest of all time—platform shift, powered by generative AI, is upon us. The ground beneath us is shifting again. On a per-user basis, generative AI demands orders of magnitude more energy. At a time when data centres are already consuming more energy than many countries, it is set to double again in two years to roughly equivalent to the electricity consumption of Japan. The lean startup era is gone. AI startups need to raise much more capital upfront than previous generations of startups because of the enormous cost of compute.
Expecting the server in the data centres to do all the heavy lifting can’t be sustainable in the long term for many reasons. The “brains” have once again started to shift back to the clients at the edge, and it is already happening. For instance, Tesla’s self-driving decisions are not going to make the round trip to its servers. Otherwise, the latency will make the split-second decisions a second too late. Another example, most people may not realize this, but Apple is an edge computing company already as its chips have had AI capabilities for years. Imagine how much more developers can do on your iPhone—at no cost to them—instead of paying a cloud provider to run some AI. That would be the Napster moment for AI companies!
Inevitably, now that almost every device can run some AI and is connected, things will be more decentralized.
In past eras, computing architectures evolved due to the constraints of—or the liberation of—computing capabilities, connectivity, or power consumption. The landscape has once again shifted. Like past platform shifts, there will be a new world order. The playing field will be levelled. Rules will be rewritten. Business models will be reinvented. Most excitingly, new giants will be created.
Every. Single. Time.
Seeing the future is our superpower. That’s why a while ago, at Two Small Fish Ventures, we have already revised our thesis. Now, it is all about investing in the next frontier of computing and its applications, with edge computing an important part of it. Our recent investments have been all-in on this thesis. If you are a founder of an early-stage, rule-rewriting company that is taking advantage of this massive platform shift, don’t hesitate to reach out to us. We love backing category creators in massive market opportunities.
We are all engineers, product builders and company creators. We know how things work. Let’s build the next champion together!
Update: This blog post was published just before Apple announced Apple Intelligence. I knew nothing about Apple Intelligence at that time. It was purely a coincidence. However, it did validate what I said.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
I haven’t been involved with Wattpad for a while now, so it’s a strange feeling—though not in a bad way—to catch up on all the details about WEBTOON and Wattpad in the SEC filing. From what I’ve gathered, WEBTOON is performing exceptionally well, with revenue now surpassing $1 billion.
Three years ago, one of the main reasons I was drawn to Naver WEBTOON among all the suitors was Naver’s intention to spin out WEBTOON, together with Wattpad, as a separate, entertainment-focused, NASDAQ-listed company. This was a significant undertaking with numerous challenges, and the WEBTOON team is delivering on the promise. I’m pleased to see that Wattpad is playing a crucial role in this upcoming IPO.
The timing has turned out to be ideal for both WEBTOON and myself personally. With the rise of generative AI, the media industry is undergoing a new wave of massive disruption. It’s exciting to see WEBTOON raising more capital to seize this opportunity. From a distance, I wish the WEBTOON team all the best!
At Two Small Fish Ventures, we’re equally excited as we witness many incredible AI-native media startups and are actively investing in several amazing ones. I’ll share more about this in future posts.
This is a once-in-a-decade, platform-shift opportunity. It is arguably the biggest platform shift in the past century! TSF is actively investing in the next frontier of computing and its applications as a lead investor or as part of a syndicate. If you’re a founder of an early-stage AI-native company—media or not—don’t hesitate to reach out to us, as TSF is a rare investor who understands this space extremely well, and possibly the best investor with real-world operating experience who can help you achieve massive success like Wattpad did.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
The month of May is Asian Heritage Month, honouring the lives and contributions of people of Asian origin.
This year, I would like to talk about one common issue among Asians—speaking up, or the lack thereof.
How often do you stop yourself from saying what needs to be said?
One of the biggest cultural differences that could hold Asians back is our tendency not to speak up. Since I was a kid, my parents and grandparents conditioned us to keep our heads down. Focus on your work, and as long as you do good work, your work will speak for itself.
This is all fine, except that in Western culture, certain behaviours are perceived as the norm. Leaders are expected to be vocal and own the stage.
I have seen firsthand very capable Asian people not getting promoted because they don’t say much. I have seen investors criticizing Asian founders for not having a take-over-the-world demeanour. In one specific example, a founder was having trouble raising capital despite the company doing really well. An existing investor (also Asian) told me privately that the main reason was that this founder didn’t act like a typical American founder.
Ouch! I instantly knew what he meant.
Speaking from my own experience, it took me decades to overcome this issue. I can’t speak for other Asian cultures, but in Hong Kong, during the era when I was growing up, parents would put masking tape on a kid’s mouth if they spoke too much. My parents never did this to me because I rarely said anything. 🙂 Even today, I have to constantly push myself to speak up. On some occasions, I still err on the side of not speaking up enough because it is still very unnatural for me. Your culture stays with you for life.
I can’t tell you exactly how to overcome this issue. To a degree, it has to come from within. You have to find your own way. For me, I kept telling myself I needed to err on the side of speaking up too much. Trust me, even with that, the end result is that on many occasions I still find myself thinking I could have spoken up more, even today. So, imagine if I didn’t give myself a little nudge. It took years of practice to overcome my own emotions. Eventually, I got used to it. Well, most of the time.
However, I don’t mean to say that it is all on Asians’ shoulders to overcome this. Asian or not, great leaders have the responsibility to create a safe environment for everyone to speak up in the first place.
Humility and kindness are great traits in Asian culture. Keep them. It is also okay to push yourself to be more vocal. The barrier is totally breakable, especially one step at a time. You just have to keep pushing. After all, speaking up is not mutually exclusive with your heritage!
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Thank you to The Globe for publishing my second op-ed in as many weeks: The depressing numbers of the venture-capital slump don’t tell the full story.
The piece is now available in full here:
Bright spots in the current venture capital landscape exist. You just need to know where to look.
Recent reports are right. Amid high interest rates, venture capitalists have a shrinking pool of cash to dole out to hopeful startups, making it more challenging for those companies to raise funding. In the United States, for example, startup investors handed out US$ 170.6 billion in 2023, a decrease of nearly 30 percent from the year before.
But the headline numbers don’t tell the whole story.
There’s a night-and-day difference between the experience of raising funds for game-changing, deep-technology startups that specialize in artificial intelligence and related fields, such as semiconductors, and those who try to innovate with what’s referred to as shallow tech.
Remember the late 2000s? Apple’s App Store wasn’t groundbreaking in terms of technical innovation, but it nonetheless deserves praise because it revolutionized the smartphone. Then, the App Store’s charts were dominated by simplistic applications from infamous fart apps to iBeer, the app that let you pretend you were drinking from your iPhone.
That’s the difference – those building game-changing tools and those whose products are simply trying to ride the wave.
Tons of startups are pitching themselves as AI or deep-tech companies, but few actually are. This is why many are having trouble raising funds in the current climate.
It’s also why the era of shallow tech is over, and why deep-tech innovations will reshape our world from here on out.
Toronto-based Ideogram, a deep-tech startup, was the first in the industry to integrate text and typography into AI-generated images. (Disclosure: This is a company that is part of my Two Small Fish Ventures portfolio. But I’m not mentioning it just because I have a stake in it. The company’s track record speaks for itself.)
Barely one year old, the startup has fostered a community of more than seven million creators who have generated more than 600 million images. It went on to close a substantial US$80-million Series A funding round.
As a comparison, Wattpad, the company I founded, which later sold for US$660-million, had raised roughly US$120-million in total. Wattpad’s Series A in 2011, five years since inception, was US$3.5-million.
The speed at which Ideogram achieved so much in such a short period of time is eye-popping.
The “platform shifts” over recent decades have largely played out in the same way. From the personal-computer revolution in the late 20th century to the widespread adoption of the internet and cloud computing in the 2000s, and then the mobile era in the 2010s, there’s a clear pattern.
Each shift unleashed a wave of innovation to create new opportunities and fundamentally reshape user behaviour, democratize access and unlock tremendous value. These shifts benefited the billions of internet users and related businesses, but they also paved the way for “shallow tech.”
The late 2000s marked the beginning of a trend where ease of creation and user experience overshadowed the depth of innovation.
When Instagram launched, it was a straightforward photo-sharing app with just a few attractive filters. Over time, driven by the massive amounts of data it collected, it evolved into one of the leading social media platforms.
This time is different. The AI platform shift makes it harder for simplistic, shallow-tech startups to succeed. Gone are the days of building a minimally viable product, accumulating vast data and then establishing a defensible market position.
We’re entering the golden age of deep-tech innovation, and in order to be successful, startups have to embrace the latest platform shift – AI. And this doesn’t happen by tacking on “AI” to a startup’s name the way many companies did with the “mobile-first” rebrand of the 2010s.
In this new era, technological depth is not just a competitive advantage but also a fundamental pillar for building successful companies that have the potential to redefine our world.
For example, OpenAI and Canada’s very own Cohere are truly game-changing AI companies that have far more technical depth than startups from the previous generation. They’ve received massive funding partly because the development of these kinds of products is very capital-intensive but also because their game-changing approach will revolutionize how we live, work and play.
Companies like these are the bright spots in an otherwise gloomy venture-capital landscape.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Thank you to The Globe for publishing my op-ed about the recent capital gains tax increase last week. The piece is now available here.
Once again, to summarize, as the world shifts to intangible assets, the consequences go far beyond brain drain and job loss. We risk losing out on the GREATEST prize: ownership of industry-disrupting, IP-based companies and technologies. This aspect, often overlooked, is illustrated with real-world numbers.
Not having significant ownership of these assets in the information age is equivalent to not having electricity and oil in the industrial age. This would have a devastating and long-term impact on our economy and reputation on the world stage. Canada would be left behind with digital breadcrumbs, selling our next generation short.
The policy change clearly didn’t take this into consideration. Saying that it impacts only 0.13% of the population is so wrong on many fronts. It is abundantly clear that it will impact EVERYONE.
Don’t forget to tell them.
Here is the full copy of my op-ed:
The Liberal government is increasing taxes on investment. Anyone experienced in entrepreneurship and investment knows this will stifle growth. We are at tremendous risk of losing our brightest entrepreneurs – along with the high-skilled jobs they create – to other countries.
This is evidenced by a new survey conducted after the capital-gains tax changes: Just 5.3 per cent of Canadian founders believe Canada is the best place to grow a company.
As the world shifts to intangible assets, the consequences go beyond brain drain and job loss. We will lose out on the greatest prize of the innovation economy: ownership of industry-disrupting companies and technologies. This would have a devastating and long-term impact on our economy and reputation on the world stage.
I will admit that this latest change to taxation has an immaterial impact on me personally. Wattpad, the company I co-founded, was acquired by Korean internet giant Naver for $840-million in 2021 so I’ve already paid my dues as stipulated under the budget at the time. But my experience illustrates how this tax change is detrimental to Canada and future generations.
Because I raised most of the capital from outside of Canada, only half of the company was owned by Canadians, including founders, employees and investors. In other words, when Wattpad was acquired, $420-million of the economic value left our country.
Before the tax hike, it was reported that when our tech startups become scaleups, about 75 cents out of every invested dollar comes from outside of Canada. This means many of these fast-growing companies are already majority-owned by foreigners.
As a venture capitalist, I see this trend play out all the time. The firm I co-founded, Two Small Fish Ventures, has a portfolio of 50 early-stage tech companies. We are the only Canadian investor in many of our recent investments. Foreign investors, especially U.S. investors, are aggressively writing cheques to own a significant portion of these early promising Canadian startups when they are relatively inexpensive.
The tax increase will only exacerbate this problem.
When a company’s assets are purely intangible, and its biggest investors and markets exist outside Canada, it’s natural and far easier for the company to move outside Canada or be acquired by foreigners, such as Wattpad. Needless to say, the economic value creation postacquisition is also captured outside of Canada.
One might argue that these companies create many jobs in Canada, so we still captured some value, right? Well, again, when a company’s assets are mostly intangible, the majority of the economic value created is captured by its IP, not the jobs created. As an example, Wattpad’s payroll was about $30-million per year, not small, but it is a minuscule number compared to the nearly billion dollars that the company was valued at.
There’s also a tectonic shift under way across the innovation economy. The rise of AI and related fields such as semiconductors in particular is an order of magnitude more capital-intensive than previous generations of tech companies. Canada has produced some of the best AI researchers in the world, but when 40 of Forbes’ 2024 AI 50 List are in the U.S. (and more than 30 of them in Silicon Valley) while only two are in Canada, we could have and should have owned a much bigger piece of the pie.
The best example is OpenAI, which was co-founded by Ilya Sutskever, a Canadian. The company is based in San Francisco. The majority of its employees are not in Canada. All the major investors are U.S.-based. Canada only has the bragging rights.
And, do I have to remind everyone that Elon Musk is also Canadian?
In the post-pandemic world, capital and talent are more mobile than ever. The pull to move to other countries is also stronger than ever. Canada is already becoming the best training ground for other countries to capture the value created by these companies outside of Canada.
I want Canada to win. I really do. What motivates me now as an investor is to help create more homegrown Canadian tech giants – and to keep them in Canada. My job just got much harder.
Higher taxes mean less capital, reduced investment, diminished ownership and fewer economic benefits. Period.
At a time when we need more capital to own a meaningful piece of the IP-based economy, our country is going backward. As the economy increasingly shifts toward intangible assets, we will be left behind with digital bread crumbs, selling our next generation short.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Over a decade ago, in his blog post titled “Why Software is Eating the World,” Marc Andreessen explained why software was transforming industries across the globe. Software would no longer be confined to the tech sector but permeated every aspect of our lives, disrupting traditional businesses and creating new opportunities, driving innovation and reshaping the competitive landscape. Overall, the post underscores the profound impact of software on the economy and society at large.
While the prediction in his blog post was mostly accurate, today, the world is still only partially eaten up by software. Although there are many opportunities for software alone to completely transform user behaviour, upend workflow, or cause other disruptions, the low-hanging fruits are mostly picked. That’s why I said the days of shallow tech are behind us now.
Moving forward, increasingly, there will be more and more opportunities that require hardware and software to be designed and developed together from the get-go to ensure that they can work harmoniously and make an impact that otherwise would not be possible. The best example that people can relate to today is Tesla. For those who have driven a Tesla, I trust many would testify that their software and hardware work really well together. Yes, their self-driving software might be buggy. Yes, the build quality of its hardware might not be the best. However, with many features on their cars – from charging to navigation to even warming up the car remotely – you can just tell that they are not shoehorning their software and their app into their hardware or vice versa.
On the other hand, on many cars from other manufacturers, you can tell their software and hardware teams are separated by the Grand Canyon and perhaps only seriously talk to each other weeks before the car is launched 🙂
We also witness the same thing down to the silicon level. From building the next AI chip to the industrial AI revolution to space tech, software and hardware convergence is happening everywhere. For instance, the high energy required by LLMs is partially because the software “works around” the hardware, which was not designed with AI in mind in the first place. Changes are already underway, ensuring that software and hardware dance together. There is a reason why large tech players like OpenAI and Google are planning to make their own chips.
We are in the midst of a once-in-a-decade “platform shift” because of generative AI. In the last platform shift more than a decade ago, when the confluence of mobile and cloud computing created a massive disruption, there was one “iPhone moment,” and then things progressed continuously. This time, new foundation models are launching at a break-neck pace, which is further exacerbated by open-source. So fast that we are now experiencing one iPhone moment every few weeks.
All of this happens when AI-native startups are an order of magnitude more capital-intensive than in the past cycle. At the same time, investors are also willing to write big cheques to these companies, but perhaps it is appropriate, given all the massive opportunities ahead of us.
Investing in this environment is both exciting and challenging as assessing these new opportunities is drastically different from the previous-generation software-only, shallow-tech startup.
The next few years are going to be wild.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
In the early 2010s, when Wattpad began raising capital from Silicon Valley, Valley VCs didn’t ask me ‘if’ I would move the company or open a second office there; they asked ‘when.’ They argued that Toronto lacked great product people and scale-up leaders, although we had top engineering talent. At that time, it was common for Valley VCs to ask non-Valley companies to move to the Valley as a condition for funding.
But I told them, ‘I won’t move.’
While their argument had a point, Valley VCs failed to see my “big-fish-small-pond” advantages. I don’t need to hire a million great people. After raising one of the largest funding rounds by a Canadian-based company at the time, I was absolutely sure we could hire “enough” great people to help us build a world-class company based in one of the most populous metropolises in North America called Toronto. Paradoxically, it could even work to our advantage. As one of Toronto’s biggest fish, we could hire the best. I couldn’t say the same thing if we moved to the Valley. Besides, building a company culture with a single office location was much easier.
It was a contrarian bet that few people saw, but it was so obvious to me. In hindsight, it was clear that it was the right call.
It all worked well until it didn’t. While the Toronto ecosystem went from strength to strength during the 2010s, it also meant that the talent competition became very fierce towards the end of the decade. The small pond became a much bigger pond, and there were a lot of big fish in it, including many Valley-based companies setting up shops here.
The tipping point for me was when someone bought the old building next to Wattpad HQ. Initially, we had no idea who wanted to turn it into an office tower until Google announced that it would hire a few thousand people. Where? Right next to Wattpad HQ.
My first-mover advantage has eroded. I had to figure out a new plan to regain my big-fish-small-pond advantage.
My solution was to establish a second HQ in a less populous city with a thriving tech ecosystem and an abundance of post-secondary institutions, where we could be the big fish again and have enough talent to enable us to continue to grow rapidly. It had to be a Canadian city because I wanted a few existing Wattpad employees to relocate there to help us “seed” the culture. It was far harder for me to pull it off if it was cross-border.
I toured around the country. I was impressed by what I saw. There were a handful of cities that met our criteria. I knew we could make it work.
At that time, I was already very familiar with Halifax, having been involved in the local ecosystem for a while. While there, I took advantage of the opportunity to grab dinner with Jevon McDonald, whom I had known for a few years. Nothing compares to talking to a local guru.
Jevon gave me the rundown of all the nuances I couldn’t find on Google search. But when I asked him to name one thing that he didn’t like about Halifax, this was our conversation:
Jevon: “I have a few employees in San Francisco. Going there is very painful as I have to catch a 5am flight to connect through Toronto first.”
Me: “So, there is no direct flight from Halifax to SF?”
“Nope.”
“Great!”
“What?!”
It’s a short flight between Toronto and Halifax. There are numerous daily flights between the two cities, so day trips are super easy. However, the lack of direct flights to the Valley means Valley-based companies won’t show up any time soon. An unfair disadvantage became my unfair advantage. The lack of direct flights became my talent moat.
The rest is history. Wattpad established its second HQ in Halifax. We hired a lot of fantastic people there. I have been the biggest champion of Atlantic Canada ever since, as I have encouraged other Toronto-based companies to do the same.
It was another contrarian bet that few people saw, but it was so obvious to me. It was the right call.
These are just a couple of examples. There were many more that Wattpad did, like establishing a movie studio or investing in something unproven called AI more than a decade ago.
Similarly, some of our best investments in Two Small Fish Ventures, such as Sheertex or BenchSci, had a very tough time raising capital early on because very few people saw what we saw.
Of course, I am not suggesting that one should be contrarian for the sake of being contrarian. But when a contrarian bet results in a first-mover advantage in a big opportunity that no one else saw, that will almost always generate an amazing outcome with outsized returns.
Don’t tell anyone.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
When Eva and I were on stage yesterday at Entrepreneurship Week at the University of Toronto, moderator Bianca Bharti from BetaKit asked us:
“Given we are celebrating women and raising awareness about related issues this week, what do you want to tell the audience here today?”
Here is what I said. When I was Wattpad’s CEO, we didn’t just talk about diversity or run flashy programs just to make us look good. Instead, we invested in it. We allocated real resources, dollars, and people’s time to create a truly diverse and inclusive culture at Wattpad.
The business reason was simple – half the world’s population is female. If we want to properly capture this market, do you really think a bunch of male guys in the room can figure this out?
The end result is that we achieved gender parity at BOTH the employee level and the leadership team level. However, the numbers don’t tell the whole story. Anyone who worked for Wattpad can testify that we have created a truly inclusive culture.
Personally, I would consider this one of our biggest achievements.
But that was only the first chapter of the story. At Two Small Fish Ventures, we carry the same DNA. It was mostly Eva’s work, as I only started to be more involved in recent years. Through inspiration, advocacy, and mentorship, we achieved 50% female founders in our portfolio. In fact, many of our rocket ships are female-led.
Our job is not done yet. Together, we can change how the world operates.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
A couple of months ago, I blogged about a report from the investment firm LetkoBrosseau, titled “Canada Has Cut Back on Investing in Its Greatest Asset—Itself.” This report highlights how minimally the Canadian pension system is investing in Canada. The blog post quickly became one of my most popular in recent times.
Shortly after, the founders of LetkoBrosseau reached out to me and asked if I would be interested in participating in an open letter addressed to our Minister of Finance of Canada and the Provincial Finance Ministers. After reading the draft, I replied with a resounding “yes” without much hesitation. Over 100 business leaders in Canada also agreed to participate. You can see the coverage on The Globe and Financial Post.
This is the slide from the original report that caught my attention and summarizes it well:
I believe that Canadian pension funds are among the best in the world. Our pension funds are adept at finding some of the best investment opportunities globally and generating the best “returns” for us. They are doing the job they were tasked with doing.
However, while they generate the best “returns” from their investments, they are not asked to consider the economic impact of the “feedback loop” highlighted in green. This feedback loop encompasses the second-order effects and its economic benefits from investing in Canada. In other words, “the best returns to Canadians (the pensioners)” are not necessarily the same as “the best investment returns.” More importantly, these two aren’t mutually exclusive. With some fine-tuning to the investment sourcing process, for instance, achieving the best returns for Canadians shouldn’t come at the expense of achieving the best investment returns.
To be clear, I am not in a position to tell pension funds where or what to invest in, let alone suggest they invest solely or primarily in Canada. They are the experts and have been performing outstandingly. However, we need to change how we evaluate investment returns to include the second-order effects of investing in Canada. This adjustment would encourage pension funds to seek out investments that serve pensioners best when these effects are considered in their evaluations. I believe no one would argue against this approach.
You can read the open letter here:
Dear Minister of Finance of Canada and Provincial Finance Ministers,
We are concerned with the decline in Canadian investments by pension funds and its impact on the Canadian economy. Millions of Canadians have contributed to their pensions with wages earned in Canada.
Pension funds represent approximately 37% of institutional savings in Canada, a size comparable to the banks. Contrary to the banks and insurance companies that focus mainly on debt, pension funds are unique in their ability to be patient long term equity investors, just what Canada needs to forge its future.
Canadian Pension Funds have reduced their holdings of publicly traded Canadian companies from 28% of total assets at the end of 2000 to less than 4% at the end of 2023. It is estimated that the eight largest pension funds in Canada have more invested in China (roughly $88B) than they do in Canadian public and private equities (roughly $81B). Their holdings of all Canadian based equity investments including public and private companies, real estate, and infrastructure is down to approximately 10% of total assets.
Why should we care?
Canada’s gross domestic product (GDP) per capita has fallen from 95% of US GDP per capita in 1980 to 75% in 2023. Non-residential investment per worker in Canada is less than half that of the United States. For every dollar Canadians invest in startups, the United States invests $40.
Canada benefits from enormous advantages. It is one of the most developed economies in the world and has been a wonderful place to invest. Over the last 25 years Canadian equity markets have topped the G7 countries and have consistently delivered very competitive returns.
Investment opportunities exist in many countries, and we believe pension funds should be able to invest anywhere in the world. However, investments made in Canada do not impact just pension portfolios; they also have a considerable impact on the country’s economy: generating jobs, improving incomes, and increasing contributions to retirement plans. Less investment in Canadian businesses increases their cost of capital, discounts their value, reduces their ability to grow, and makes Canada less attractive.
Pension funds should not fear but rather embrace with enthusiasm the challenge of investing in Canada. The positive impact these investments have on their member’s incomes and development should not be ignored.
Without government sponsorship and considerable tax assistance, pension funds would not exist. Government has the right, responsibility, and obligation to regulate how this savings regime operates.
Canada has great companies, true global champions These competitive businesses deserve our support, and we must create many more. Increasing investments in Canada should be a national priority.
Given their importance to the Canadian economy we, the undersigned, would support an effort by the Minister Finance of Canada and the Provincial Ministers of Finance to amend the rules governing pension funds to encourage them to invest in Canada. Consideration should also be given to incentivize other investors to allocate more capital to domestic investment.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Most of Two Small Fish Ventures’ portfolio companies are based in North America. However, we also invest globally, as we firmly believe that global companies can be built anywhere. To us, where founders and their teams sleep at night is irrelevant to their potential for greatness.
Consequently, we actively engage with many tech ecosystems, regardless of their size. A pervasive issue we’ve encountered across these ecosystems is the challenge entrepreneurs face in finding investors who provide not just capital but the right kind of support. This problem is more acute in less developed ecosystems, but even those that are more established are not exempt.
An investor from another ecosystem eloquently discussed this issue in an article. I couldn’t have said it better myself, so with her permission, I’m sharing her insights here, albeit anonymized to avoid casting any ecosystem in a negative light. After all, this challenge is universal:
There are plenty of rich people and “wantrepreneur” investors in our community, but most of them have made their fortune in real estate, finance, or other traditional sectors. They have great intentions, but unfortunately they do not have experience in investing in technology and innovations. Some of them would take too much equity ownership. Some of them have conflicts of interest pursuing their own agendas and push their founders to work on products or customers that they want. Some are so risk averse that they structure their startup investment as if it is a personal loan. We have seen our startup founders take money from these investors and almost always end in disaster.
What our community really needs are the startup investors who have “been there and done that.” Or we will continue to be stuck in this vortex of wrong investors investing in the wrong companies. We need investors who truly understand the startup founders’ blood, sweat and tears approach. Someone who knows how to be a guide and a coach. Someone who knows how to provide advice, connections, and funding only when the founder really needs it.
To achieve this goal, we need to invite investors from established ecosystems to teach local investors the best practices in venture investing. And we do believe these skills can be learned. The local investor community needs the knowledge and skills to make investment decisions that maximize the founders’ success therefore their chances of success.
Investing in innovation significantly differs from other forms of investment. For instance, real estate investments have established methods to evaluate rental yields, and traditional businesses use EBITDA to estimate enterprise values. However, early-stage startups, particularly those disrupting the status quo, cannot be evaluated using these metrics because of their lack of yields or EBITDA, or even clear business models!
Often, experienced investors from other sectors mistakenly apply the same approach when they invest in tech startups, leading to almost certain failures. This can result in many problems, such as a messy cap table, ensuring the startup unfundable in future funding rounds and potentially “die young” despite its potential. We’ve regrettably had to pass on numerous investment opportunities due to such issues.
As the quoted investor highlighted, learning the skills and best practices in tech investing is possible. Needless to say, the best way to do this is to learn from people who have “been there and done that.” It’s crucial to acknowledge that investing in tech startups – and innovations in general – is a different sport than other sectors.
After all, bringing a tennis racket to a hockey game is a recipe for disaster.
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
There’s an old saying that goes, “Know the rules of the game, and you’ll play better than anyone else.” Let’s take baseball as our example. Aiming for a home run often means accepting a higher number of strikeouts. Consider the legendary Babe Ruth: he was a leader in both home runs and strikeouts, a testament to the high-risk, high-reward strategy of swinging for the fences.
Yet, aiming solely for home runs isn’t always the best approach. After all, the game’s objective is to score the most runs, not just to hit the most home runs. Scoring involves hitting the ball, running the bases, and safely returning to home base. Sometimes, it’s more strategic to aim for a base hit, like a single, which offers a much higher chance of advancing runners on base and scoring.
The dynamics change entirely in a home run derby contest, where players have five minutes to hit as many home runs as possible. Here, only home runs count, so players focus on hitting just hard enough to clear the fence, rendering singles pointless.
Imagine if the derby rules also rewarded the home run’s distance, adding extra runs for every foot the ball travels beyond the fence. For context, the centre field is typically about 400 feet from home plate. So, a 420-foot home run, clearing the centre field by 20 feet, would count as a 20-run homer. This rule would drastically alter players’ strategies. Not only would they swing for the fences with every at-bat, but they would also hit as hard as possible, aiming for the longest possible home runs to maximize their scores, even if it reduced their overall chances of hitting a home run.
This scenario mirrors early-stage venture capital, where I liken it to a home run derby with uncapped runs. The potential upside of investments is enormous, offering returns of 100x, 1000x, or more, while the downside is limited to the initial investment. Unlike in a derby, where physical limits cap the maximum score, the VC world is truly without bounds, with numerous instances of investments yielding thousandfold returns.
This distinct dynamic makes assessing VCs fundamentally different from evaluating other asset classes, where protecting the downside is crucial. In the VC realm, the potential for nearly limitless returns makes losses inconsequential, provided VCs invest in early-stage companies with the potential for exponential growth. The risk-reward equation in venture capital is thus highly asymmetrical, favouring bold bets on moonshot startups.
For illustration, let’s consider two hypothetical venture capital firms: Moonshot Capital and PlayItSafe Capital.
Moonshot Capital approaches the game like a home run derby with uncapped runs. They aim for approximately 20 companies in their portfolio, expecting that around 20% will be their home runs—or “value drivers”—capable of generating returns from 10x to 100x or more.
Imagine they invest $1 in each of 20 companies. One yields a 100x return, three bring in 10x, and the remaining are strikeouts. The outcome would be:
(1 x 100 + 3 x 10 +16 x 0) x $1 = $130
Their $20 investment becomes $130 (or 6.5x), a gain of $110, despite 17 out of 20 companies being strikeouts. Yes, you are correct. 85% of the portfolio companies failed!
PlayItSafe Capital, on the other hand, prioritizes downside protection, ensuring none of the portfolio fails but also avoiding riskier bets. In the end, one company generates one “10x” return, five companies return 3x, and the remainder is equally split between breakeven and failing.
(1 x 10 + 5 x 3 + 7 x 1 + 7 x 0) x $1 = $32
Despite several “successes” and very few “losses,” the fund’s return of $12 pales in comparison to Moonshot Capital’s. Even increasing the number of companies generating a 3x return to 10 with no loss (which is almost impossible to achieve for early-stage VCs) only yields a $29 gain from a total investment of $20:
(1 x 10 + 10 x 3 + 9 x 1) x $1 = $49
No one should invest in the early-stage VC asset class with the expectation of such a paltry return.
As illustrated, success isn’t about minimizing failures, nor is it about the number of “3x” companies or even the number of “unicorn logos” in the portfolio, as how early when the investment was made to these unicorns is crucial as well. One needs to invest in a unicorn when it was a baby-unicorn, not after it became a unicorn.
In summary:
Venture funds live or die by one thing: the percentage of the portfolio that becomes “value drivers”, i.e. those capable of generating returns of 10x, 100x, or even 1000x.
At Two Small Fish Ventures, we are the IRL version of Moonshot Capital. Every investment is made with the belief that $1 could turn into $100. We know that, in the end, only about 20% of our portfolio will become significant value drivers. Yet, with each investment, we truly believe these early-stage companies have the potential to become world-class giants and category creators when we invest.
This is what venture capital is all about: not only is it exhilarating to be at the forefront of technology, but it’s also a great way to generate wealth and, more importantly, play a role in supporting moonshots that have a chance to change how the world operates.
P.S. This is Part 1 of this series. You can read Part 2, “Winning the Home Run Derby with Proper Portfolio Construction” here.
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Diversifying a portfolio across various asset classes is the first principle for enhancing returns without significantly increasing risk from an investment standpoint. Traditionally, the go-to formula has been a 60/40 split—60% in stocks and 40% in bonds, a practice primarily due to the limited accessibility of alternative asset classes. However, recent years have seen a democratization of access to a wider array of asset classes, including private equity, venture capital and numerous alternatives, opening doors for more investors to explore areas once reserved for the privileged few. This broadening of opportunities is undoubtedly beneficial to many.
Yet, it introduces a new challenge: How do we assess fund managers across different asset classes? This task can be daunting even for seasoned investment professionals, as investing encompasses a vast range of specialties. A common mistake is posing the wrong questions, as assessment criteria are not interchangeable across asset classes. It is akin to comparing athletes from different sports—evaluating NBA players is not the same as evaluating MLB players since each asset class is akin to a distinct sport. For instance, inquiring about the batting average of an Olympic gold medalist swimmer is as illogical as expecting an NBA MVP to be proficient with a baseball bat.
It’s also unwise to question a fish on its ability to skate!
This blog post is the first in a series designed to demystify this process. I do not claim expertise in all asset classes—no one can. However, I hope to share my experiences to help you sidestep common mistakes and empower you with the basics to evaluate investment opportunities in unfamiliar territories, especially early-stage venture capital, which is my swim lane and relatively few people have the experience to assess. Please note, this blog post does not constitute investment advice or a comprehensive guide across all asset classes as we only cover a handful for illustration purposes.
Here is a chart that highlights the key differences:
How should you interpret this chart? Let me use early-stage venture capital, or simply referred to as VC, as an example.
Assessing VC is more art than science and more qualitative than quantitative. It offers far higher return potential than almost any other asset class. On the other hand, the risk of losing money is also higher than in other asset classes, with the predictability of the potential target return being low and its variance high.
Individual investments within a fund portfolio have a very high failure rate, even for the best funds. This is by design because VC is a home run derby. Strikeouts, singles, or doubles don’t impact the return at all, as only the home runs count. This is unique to VC and counterintuitive to managers from other asset classes.
The dispersion among fund managers is also much higher, as the top decile funds generate significantly better returns than the rest. Vintages also make a far more significant influence, as market downturns have an outsized impact on fund returns, even for the best funds. However, the best funds still generate very good returns during bad years. These funds simply generate enormous returns during the good years!
VC takes a decade or more to generate returns. The first few years usually have nothing to show for because it takes a few years to find the startups to invest in, and they take time to grow and realize the gain. Because of this, VC funds are usually illiquid.
On the other extreme, fixed income is more science than art. It is number-driven, much more predictable, and has lower returns, but any default is a cardinal sin!
Each row on the chart deserves a separate blog post. Stay tuned for subsequent posts in this series, where we’ll dive deeper into these topics.
This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
One of the three things that CEOs only do is to “make sure there is enough cash in the bank” (see job #3 here). Although CFOs may be responsible for much of the heavy lifting, keep in mind that CEOs’ job #1 is to communicate vision and strategies to all stakeholders, which certainly includes potential and existing investors. It is very hard to raise capital to build a great company without great storytelling skills, something almost all great CEOs possess.
Clearly communicating a bold vision is especially important for early-stage venture-backed companies. These companies are usually pre-revenue, pre-product-market-fit, and definitely pre-scaling. From the VCs’ perspective, they invest not only in where the company is today, but also where the company would be, could be, and should be. In many cases, investors buy into the company’s second, third, and fourth acts in the future, as very few great companies are one-trick ponies.
SRTX is the perfect example. Last week, we went to the grand opening of their mega-factory in Montreal. To my knowledge, it is now the largest textile factory in Canada. The pictures and videos don’t do justice to the massive scale of this facility.
This is especially impressive when you know that 180 days ago, when they took over the facility, the roof was leaking, there were no walls, and there was no electricity. The SRTX team moved mountains, rock by rock and at lightning speed, to get the factory ready for production.
I wish I could share some pictures inside the factory. Unfortunately, I can’t share their secret sauce. If you really want to have an insider view, you have to become an investor 😉
It took 7 years from its inception for SRTX to begin evolving into a fully verticalized behemoth through innovations in advanced material, hardware, and software to deliver traceability, sustainability, durability, and cost advantages, which is now giving them an “unbreakable” advantage – pun fully intended!
Today, millions of Sheertex unbreakable pantyhose are sold. They became THE best-selling pantyhose, unbreakable or otherwise, in North America, not bad for a 15-person company based in Bracebridge, Ontario, a town with a 15,000 population and a 2-hour drive north of Toronto when Two Small Fish Ventures invested!
Now, they are ready to license the IPs of their rip-resistant technology to other textile companies. That’s their second act. Watertex, one of the world’s most hydrophobic polymers that is engineered for unparalleled water resistance for use in, say, swimwear, is their third act. There are other IPs that are in the works. I would call them their fourth act.
But please don’t use the word pivot here. Pivot implies ‘nothing works, let’s try something else.’ Since the early days, Katherine was very clear that selling pantyhose online was the necessary first act to give her the economy of scale before she could begin her second act, third act, and fourth act. What we see today is exactly how she articulated her bold vision when we invested in the seed round five years ago. We bought into her vision, joined the journey, and now, what she told us is becoming a reality. We wouldn’t have invested in a company that was merely selling pantyhose online, even if millions were being sold.
The power couple, Katherine Homuth and Zak Homuth, are not your typical founders. SRTX is rewriting the rules of textiles through innovations. I can’t wait to watch the second, third, and fourth acts unfold right before our eyes from my front-row seat.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Silicon Valley’s founder CEO worship definitely has its merits. As a CEO backed by many valley VCs, I have immersed myself in that view for decades (e.g., Ben Horowitz’s Why We Prefer Founding CEOs). I get it, I understand where it comes from, and I do mostly agree. That’s why TSFV backs founding CEOs almost 100% exclusively.
Great founding CEOs tend to have all three traits: 1) Comprehensive knowledge of the entire company (including knowledge of every employee, product, technology decision, customer data, and the strengths and weaknesses of both the code base and the organization), 2) moral authority, and 3) total commitment to the long-term, while professional CEOs often don’t.
On the other hand, being a great CEO is more than just starting a company. It’s a super stressful job that nobody can learn overnight, and running a company with hundreds or thousands of employees is definitely a different ball game than being a founding CEO of a five-person company. However, founders who can’t scale with the company can’t stay in the captain’s chair forever.
If the two jobs are so different, why do we still prefer founding CEOs, even though many are learning on the job? Because it gives the company the best chance to become ultra-successful.
Typically, a company goes through four stages of growth. I call it the “4S’s”:
Start: where everything begins, with just the co-founders and a tiny team.
Sprout: achieving product-market fit, with the CEO calling most of the shots in a mostly informal setting.
Scale: rapid growth, hiring functional leaders, building depth, and starting to establish business processes. This is often where founder CEOs, especially first-time founder CEOs, stumble as they might lack experience in hiring and leading large teams.
Success: achieving a major milestone like an IPO or a massive liquidity event.
But the growth of a company isn’t a waterfall. An innovation company can’t stop innovating once its (first!) product has achieved product-market fit and cannot simply switch gears overnight to focus on business optimization. The most successful companies aren’t one-trick ponies; they need second and third acts long after their first product takes off.
Based on my own experience and my observation of hundreds of CEOs’ personal growth, I can confidently say that it’s far easier for a founding CEO to learn leadership than for a professional hire to become innovative and visionary. When the company hits scale-up mode, a founding CEO’s leadership needs to be solid, but any gaps can be filled by hiring strong leaders. Most founders can successfully make this jump.
On the flip side, pushing someone to be innovative and visionary is much harder, as is finding a team of leaders who can fill that gap for a professional CEO. That’s why it’s tougher for professional CEOs to succeed, though it’s not impossible. It is also possible to hire an “entrepreneurial” professional CEO, although they are rare gems.
However, this is all pretty generalized. Generalization tends to default to pattern recognition without thoughtful consideration of the specificity of the company’s situation. The ideal scenario is a founding CEO leading all the way, but sometimes, if a professional CEO is the only option, that’s what we have to work with.
The good news for TSFV’s portfolio CEOs is that you’ve got a founding CEO who’s been through it all – me! These days, I spend a lot of time helping founding CEOs fast-track their learning to operate more effectively on the job. For our professional CEOs, I offer guidance to help them think and act more like founders. Helping our portfolio CEOs is the best use of my time to ensure our portfolio companies’ success. It is also extremely high-leveraged because sometimes, even a 30-minute conversation with me can help change the trajectory of a company. After all, if our CEOs aren’t successful, it’s nearly impossible for our portfolio companies to be successful, isn’t it?
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Last September, I had the honour of being the keynote speaker at the Lab2Market Deeptech Expo, where I discussed the current state of deep tech investments and commercialization. A key theme I emphasized is our growing excitement about deep tech. In fact, I would even argue that we are entering the golden age of deep tech.
Why this belief? Reflecting on the significant “platform shifts” over recent decades reveals a pattern: each shift has unleashed waves of innovation. Consider the PC revolution in the late 20th century, the widespread adoption of the internet and cloud computing in the 2000s, and the mobile era in the 2010s. These shifts didn’t just create new opportunities; they fundamentally altered user behaviour, democratized access, and unlocked unprecedented value.
It goes without saying that the primary beneficiaries of these shifts are the 5 billion internet users and relevant businesses. However, these shifts have also been the biggest enablers of what I term “shallow tech.”
Take, for example, the late 2000s. The App Store’s top charts were dominated by simplistic applications — remember those infamous fart apps?
This era marked the beginning of a trend where ease of creation and user experience overshadowed the depth of innovation. Recall Instagram’s initial release as a straightforward photo-sharing app with just a few attractive filters. Similarly, the first iteration of Wattpad on the Motorola RAZR was a simple Java app, supported by a basic LAMP stack backend.
Subsequent early iPhone, Android, and Blackberry versions were only marginally more complex. Over time, both Instagram and Wattpad evolved into deep tech companies, driven by the massive amounts of data they amassed. However, in both cases, it only took months from concept to launch, despite taking years to become substantial businesses.
In contrast, building deep tech companies from the ground up was far more challenging. Years could be spent developing the technology alone, even before considering market readiness or commercialization. This long cycle made it very hard to build companies and secure funding.
In recent years, however, the landscape has begun to shift. The playbook of developing minimal tech, amassing vast data pools, and then creating a defensible moat through network effects is becoming increasingly difficult. The entrenched network effects of incumbents in both consumer and enterprise spaces make it harder for “shallow tech” startups to achieve escape velocity.
Conversely, as we find ourselves in the midst of another significant platform shift – this time centred around AI – AI is revolutionizing how deep tech companies are started and scaled. For instance, robotic designs can now be developed through a few AI prompts. AI is also transforming chip development, allowing for significant acceleration before tape-out. In drug discovery, AI-assisted processes have condensed timelines from years to mere weeks. These are just a few examples. What once seemed like science fiction is now our reality.
While deep domain expertise in fields like robotics, chips, biotech, and other areas remains crucial, AI is now democratizing deep tech. It’s making it more accessible and is accelerating innovation across numerous sectors. We are on the cusp of a new era, one where the depth of technology plays a far bigger role in building successful companies that reshape our world.
The golden age of shallow tech is over. The golden age of deep tech is upon us!
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
It has been three years this month since Wattpad was at the centre of one of the largest tech acquisitions in Canadian history. At that time, as team captain, I celebrated an Olympic gold medal win along with the amazing Wattpad team.
Today, a year and a half has passed since I stepped aside from my CEO role, a position I held for 15 years since founding the company. Even a few years before the acquisition, I had already decided it would be my last stint as a CEO. As much as I loved my role, the idea of starting another company from scratch is not appealing to me, as I didn’t want to repeat the same journey over and over again. That’s why I said it’s the final curtain call of my career as a CEO. There was no ‘never say never’ in my decision.
But if you think I would simply sail into the sunset, you are mistaken. That is simply not who I am.
I am naturally a very curious person, always eager to understand how things work. My interests span a wide range of science and technology, from software to semiconductors, quantum to telecom, and everything in between. That’s my obsession.
To me, being ‘the coach’ of a winning team is far more fulfilling than being ‘the captain’ one more time. It is a different challenge, yet it fully utilizes my knowledge, skill, and experience in scaling from 0 to 100. Moreover, the timing couldn’t be better as we are experiencing a once-in-a-decade ‘platform shift’ in the midst of global AI disruption across all industries. Having pioneered AI-driven storytelling at Wattpad, AI is in fact one of my superpowers!
But why limit myself to just one team? Supporting multiple amazing teams simultaneously in building world-class, iconic tech giants and category creators is even better!
It’s a long-winded way of saying that after a year and a half in my post-CEO life, I can 110% confirm that being a venture capitalist is my dream vocation. I can do this forever!
The beast is now fully awakened. My burning desire for more wins has never been stronger. I feel like I am going to the Olympics again, only this time as an investor. Look forward to an amazing 2024, when TSFV and our portfolio companies bring home more gold medals.
Happy New Year, everyone!
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
I was reading a report from the investment firm LetkoBrosseau, which highlights how minimally the Canadian pension system is investing in Canada. Their headline caught my attention:
“Canada Has Cut Back On Investing In Its Greatest Asset – Itself.”
Canadian pension funds largely invest our money outside of Canada. Given Canada’s population size, it’s not unreasonable for our pension funds to look abroad, but the pendulum may have swung too far. That’s a topic for another day, however.
One particular slide, slide 4, jumped out at me, presenting several not-too-fun facts:
Canada’s GDP per capita has steadily declined to 75% of that of the United States, down from near parity 40 years ago. One of the main reasons is Canada invests substantially less in our own startups, R&D, and our workers.
In 2023, American investment per worker is 2.25x that in Canada. It was near parity 40 years ago.
In R&D intensity (the ratio of a country’s R&D expenditures to its GDP), the US is at 3.5, Japan at 3.3, Germany at 3.1, the G7 average at 2.6, France at 2.4. Canada lags at 1.9.
Canada is underinvesting in its own startups: For every dollar Canada invests in venture capital, Israel invests $2 (despite Israel’s economy being a quarter the size of Canada’s), and the US invests $39. This means that on a per capita basis, Israel invests 8 times more than Canada, and the US 4 times more.
Moreover, Canadians only provide about 33% of the funding for their own startups, with the remaining 66% coming from other countries. At Wattpad, we observed a similar ratio. Our largest investors were Union Square Ventures (NYC), Khosla Ventures (Silicon Valley), OMERS (Canada), August Capital (Silicon Valley), and Tencent (Asia). As you can see, most of them are not Canadian, highlighting a limited appetite for investing in our own innovative ventures.
But it’s not just about pension funds. The awareness and appetite to invest in venture capital as an asset class are significantly lower among family offices and endowments in Canada. For example, in the US, it’s not uncommon for university endowments to allocate over 20% to VC. In Canada, many are at zero or in the low single digits.
But it all depends on whether you’re a glass-half-full or glass-half-empty person.
I’m a glass-half-full person. This is clearly a market gap, and market gaps create opportunities.
A decade ago, when Wattpad began raising capital from Silicon Valley, Valley VCs didn’t ask me ‘if’ I would move the company there; they asked ‘when.’ I told them, ‘I won’t move.’ They were all surprised to hear from me that building the company in Canada would be far better due to less competition for talent, paradoxically allowing us to hire and retain top talent more easily. Wattpad was one of the first to commit to scaling our company in Canada, successfully proving (to them) that a world-class tech company could be built here (obvious to me). The Wattpad team played a part in reshaping the narrative of Canada’s innovation ecosystem.
I am very committed to doing it again. This time, I’m not convincing people in the Valley that Canada is great; I’m convincing Canadians that Canada is great! My goal is to encourage more attention towards VC as an asset class. As a VC myself, I’m putting my money where my mouth is, and I will let our results speak for themselves. For many decades, Americans and Israelis have known that investing in top-tier VCs can help create world-class, iconic companies, benefiting their local economies significantly while also generating consistent, outsized returns. Canada can undoubtedly do the same.
This is my last post of the year. I’ll be “off the grid” until the new year, recharging for what promises to be a super busy 2024. Happy holidays!
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Sets the overall vision and strategy of the company and communicates it to all stakeholders.
Recruits, hires, and retains the very best talent for the company.
Ensures there is always enough cash in the bank.
These responsibilities might seem straightforward, but they encompass a vast array of tasks and decisions.
For instance, ensuring there is always enough cash in the bank could imply that a CEO needs to double as a CFO, but clearly, CEOs should not be CFOs. Similarly, hiring the very best talent could include all people functions, but of course, it should not.
In other words, even with just three things, CEOs will never run out of things to do. So how should they prioritize?
One guiding principle is that CEOs should only do things that they can uniquely do. Let someone else take care of the heavy lifting.
When Wattpad started to scale, this mindset shift really helped me prioritize. This problem is much more common than you may think. Based on my observations, I would even say that at some point, most inexperienced CEOs spend too little time on things that they can uniquely do. Failing to do so, the problem could manifest itself as people in the company chronically waiting on you before they can take their next actions on projects. You lose all the leverage you have in hiring a team.
You already paid them so much money to do the job for you. Don’t do their job for them!!!!
Although this lesson is mostly for CEOs, the same principle also applies to other leaders and managers. There is a bucket called ‘only you can do.’ Note that this bucket is not called ‘I can do it better‘ because who can do a better job or who can do it faster is not the issue here. Resisting the temptation to take on a task when your team can (should!) handle it can greatly help you improve your productivity and turn you into a much more effective leader.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
I’m a 3x entrepreneur. I was the CTO of my first company, which failed. I was the CEO of my second one, which was acquired when it was still very tiny.
Wattpad was my third and last company, but it was my first one as a scale-up CEO. It was a very different beast. The learning curve for me was extremely steep.
Thankfully, I was very privileged to have many world-class VCs and their firms invested in Wattpad. Being surrounded by world-class investors and their network not only helped me surmount that learning curve but also helped TSFV become a much better VC firm. More on that in a different post.
One of these firms is Union Square Ventures. The first and most important thing I learned from USV’s Fred Wilson is, “What does a CEO do?”
A CEO does only three things:
Sets the overall vision and strategy of the company and communicates it to all stakeholders.
Recruits, hires, and retains the very best talent for the company.
Ensures there is always enough cash in the bank.
A CEO should delegate all other tasks to his or her team.
In my experience, it’s rare to find great CEOs and consequently, great companies, not getting these three things right. Conversely, dysfunctional companies usually get at least one of these three things really wrong.
I frequently talked about these three things with my team at Wattpad. My leadership team and all the employees knew what to expect and could hold me accountable. And they did.
So much is packed into these three things. They are deceptively simple, and yet they are extremely nuanced. There’s enough material here for a book! So, expect multiple blog posts in the future on this topic.
However, this post alone is already a great guiding post for any CEO whose company has achieved (or is beyond) product-market fit, or the team is ready to scale, say, roughly 10 people, and even for companies of much larger size.
This post is the foundation of CEOs’ leadership, and everything flows from here. I learned it, I lived it, and I can testify that this is the first thing that any CEO must get right and keep getting right throughout their tenure.
And that’s precisely why this is the inaugural post in the Two Small Fish Ventures Masterclass Series.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
One of the most unusual practices I used as CEO was writing an internal blog called “Allen’s Thoughts” on Wattpad every day. My preferred form of communication is the written word, a key reason behind co-founding Wattpad.
Although it might sound time-consuming – and it is – blogging helped me tremendously in clarifying my thinking. More importantly, context matters. The 30-60 minutes I spent each day aligned and interacted with hundreds of employees, arguably making it the most effective activity in terms of leveraging time. Here’s what I explained on Allen’s Thoughts about why I needed to do this:
“Wattpad is an incredibly complex company. We are a tech company, a media company, a book publisher, an advertising company, an influencer network, an AI company, a movie studio, a social network, a community, and also an entertainment company that makes people happy.
What links us together is our common vision, mission, values, and culture. Allen’s Thoughts is less about the numbers and company updates, which you can get on Slack, email, Google Docs, or other channels. This blog is more about sharing the context, the whys, and the intangibles in a narrative that helps you navigate that complexity so that you can make the best possible decisions and do your best job.
This blog is one of my unique superpowers that connects everyone.”
I started Allen’s Thoughts in 2013 and stopped daily blogging after stepping down in May 2022. My final post, “IT’S THE FINAL CURTAIN CALL. A NEW STORY BEGINS,” was shared publicly on allensthoughts.com.
Do I miss it? Absolutely, yes. However, after writing half a million words, I became too mentally exhausted.
After a long break, I am fully recharged and ready to reactivate my public blog. Although the Wattpad story is well-documented, many challenges and triumphs weren’t shared externally. These backstories are valuable case studies in business, leadership, entrepreneurship, venture capital and even time management. Re-reading my old posts, I realized they are a startup treasure trove, offering insights from scaling from two co-founders to a scaleup with hundreds of employees and 100 million users. I plan to share these lessons, along with many new topics.
Of course, I will also share my perspective on the startup investment landscape, our investment thesis, and our areas of focus – i.e., AI, protocols, and sustainable computing – among other topics.
This material will be part of our “School of Fish” Masterclass Series, more on this later.
I don’t plan to write daily. Frequency is not the most important aspect; it’s more about when inspiration strikes. My goal is to share high-quality, high-leverage, and impactful content. I will use Allen Thoughts to think things through “in public,” writing for my own enjoyment and hoping it benefits many others. After a hiatus, I’m eager, hungry, and excited to do it again!
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
Last week, I had the honour of chairing this year’s TechExit.io conference in Toronto, marking my first time in the role at a conference! Given my background as a 3x entrepreneur, with two of my companies having been acquired, I was thrilled to have the opportunity to share my insights and experiences. Now, as a venture capitalist, I actively support numerous entrepreneurs within the TSFV portfolio, guiding them toward outstanding outcomes.
In recent times, we’ve observed a shift in the landscape: funding has become more scarce, tech valuations more sensible, and consequently, M&A activity more appealing for both sellers and buyers. This is particularly true for traditional players, who now find themselves with greater purchasing power and are no longer priced out.
I was particularly heartened to witness the flourishing tech community in Canada. A decade ago, the focus was predominantly on selling, with most transactions below the $100 million mark. That landscape has transformed dramatically. Our ecosystem has expanded considerably, giving rise to a greater number of scaleups and facilitating larger deals. More importantly, Canadian companies are demonstrating a stronger appetite for acquisitions, with many scaleups actively pursuing growth through M&A, beyond organic means. The dialogue at TechExit.io underscored this shift.
While it’s impossible to capture all the rich content from the conference in a single post, I’d like to share my responses from a panel I had the pleasure of moderating, featuring Amar Varma, Monique Simair, and Mark Steele:
Q. If you had to choose just one thing, what would be the top learning or the biggest obstacle you wish you knew while you were building your company, that you know now?
A. Optionality! At the time of Wattpad‘s acquisition, we were in a great position, self-sustaining and with multiple paths forward, including raising another growth round or even considering an IPO. Ultimately, the decision was ours to make, and we opted for the path that we believed was in Wattpad’s best interest. The acquisition by Naver WEBTOON presented itself as the optimal choice, as it aligned with our strategic objectives and offered the unique opportunity to fully unlock Wattpad’s potential.
Q. Some investors love to ask, and some founders love to answer the following question: ‘What is your exit strategy?’ Were there things you built for an exit that went against building a great business?
A. We actually never did anything specific about the exit or formulated an exit strategy. For instance, we never created a product feature because we had potential acquirers in mind. Of course, we built relationships with them, but we didn’t do anything unnaturally in the hope of driving an acquisition. In other words, we only focused on building a great business.
Q. What did you miss the most after selling?
A. No doubt, my Wattpad team! We built an amazing all-star team. I missed my daily lunch with them in our kitchen!
It’s hard to convey the immense scale Sheertex has achieved in such a short time since its founding in 2017. Now going by SRTX, it will become one of Canada’s largest textile manufacturers with its upcoming 1,000,000-square-foot factory in Montreal.
Yet, the vast size of the factory, the quantity of pantyhose sold, and even their revenue only tell 1% of their story. If you think SRTX is “only” a direct-to-consumer company selling unbreakable pantyhose named Sheertex, think again.
The power couple, Katherine Homuth and Zak Homuth, are not your typical founders. Each has led their respective tech startups as CEO/founder. Together, they are building SRTX from the ground up as a software company and an advanced material company that is “disguised” as a textile company.
Check out the three products on SRTX Labs and you will understand.
Watertex – Their proprietary technical textile is crafted with one of the world’s most hydrophobic polymers that are engineered for unparalleled water resistance. Swimwear is an obvious use case. Clearly, there are more.
Cortex Software – Built to automate manufacturing operations, Cortex is a SaaS platform for running modern, connected, responsive and real-time aware soft goods and textiles factories. It enables factories to go paperless, generates meaningful insights into production and gives operators better work order control and reporting capabilities.
Sheertex – Its rip-resistant technology is already world-famous. Enough said.
STRX is rewriting the rules of textiles. This is another great example of our investment thesis:
Two Small Fish Ventures invests in early-stage products, platforms, and protocols that transform user behaviour and empower businesses and individuals to unlock new values.
As an engineer-turned-CEO-turned-investor, I’ve been involved in the AI space long enough that I can anticipate where the technology is headed and witnessed AI’s immense potential and its challenges. But remember, tech often solves its own hurdles. With AI, I see a future of superhuman abilities and new job horizons. Let’s embrace this future.
The piece is now available in full here:
Artificial intelligence has been dominating the headlines lately, and with good reason – AI is a transformative technology that can dramatically change how we live, work and play. Although many of the news stories focus on the potential risks and threats of AI, my intent is to present an alternative perspective.
For context, I was the chief executive officer for more than 15 years at Wattpad, an AI-driven storytelling company that was acquired by Naver in 2021. Now at Two Small Fish Ventures, I invest in many established AI companies, such as Ada and BenchSci, as well as emerging generative AI startups, such as Ideogram.
As an engineer-turned-CEO-turned-investor, I’ve been involved in the AI space long enough that I can anticipate where the technology is headed.
Yes, the technology will also create issues. Broadly, they cluster into three categories:
Security – from misinformation to autonomous weapons.
Job displacement – the replacement of human workers with machines.
Singularity – the point where AI might outwit and elude human control.
But I am confident that AI is a transformational technology that will be a net positive for society. Imposing heavy regulation or a pause today seems an unenforceable overreaction and even stifles creativity for potential solutions.
It’s a truism that novel technologies pose new challenges. Yet the remedy for these challenges is typically found within technology itself.
Take security. We’ve seen the narrative play out many times over. In the early days of the internet, people were (rightfully) very concerned about digitally sharing their credit card information. Over time, the widespread adoption of chip/PIN technology, stronger encryption and, ultimately, the birth of an entire cybersecurity industry addressed most of these challenges. Today, there are several technologies that can detect deep fake videos that would otherwise escape authentication systems. It is not hard to imagine that an uber-advanced cybersecurity industry can nullify emerging AI-related threats.
When it comes to the risk of job displacement, this is also something society has been challenged with time and time again. The Industrial Revolution ushered in both job elimination and creation. Yes, automation erases specific roles, but it concurrently births new ones. There is frictional pain and dislocation in the process, and sometimes, the new jobs go to different people in different places, but over time, the total number of jobs actually goes up substantially. Over all, society has thrived, and we’ve all become more prosperous.
AI will help turn humans into superhumans. Just like electronic spreadsheets didn’t sideline accountants but enhanced their efficiency, AI will supercharge worker productivity and output – a key element for economic growth. Plus, the fast pace of innovation will create new jobs that didn’t exist previously, like AI-prompt engineers – a job title that is less than a year old.
Among the outlined concerns, singularity looms largest, primarily because it’s an unknown frontier. But we’ve tread similar paths and crafted tools and innovations surpassing human abilities. And while some of these innovations had complete destructive potential for humanity (think missiles to bioweapons to nuclear arms), their potential for that has been mostly unrealized. In examining any threats from AI, we should be guided by evidence, not irrational fears born out of science fiction.
There will always be opposing forces and bad actors, but we can assume that humans, ironically with the help of AI, can come up with unprecedented solutions to unprecedented problems, just as we have done before.
From the agrarian age to the industrial age to the information age, society has always thrived and flourished amid disruptions. We shouldn’t expect anything different this time.
“Bags 2 Riches”, brought to you by Simplii Financial, is a docuseries that features the origins of seven notable immigrants’ journeys while highlighting their new lives in Canada. The series revisits the lows and celebrates the highs as each individual recounts the challenges they faced.
I am honoured to be featured alongside NBA star Chris Boucher, Syrian-born “refugee” chocolatier Tareq Hadhad, broadcast pioneer Shushma Datt, first 3-sport-Canadian-Olympian Georgia Simmerling, and a few others. We are all immigrants who call Canada home, and we all aim to contribute to this incredible country.
The docuseries was a massive success, so last evening the “Bags 2 Riches” team brought us together in real life to celebrate with a few hundred guests.
Back row, from left to right: Eva Lau, Allen Lau, Chris Boucher, Georgia Simmerling, Tareq Hadhad; Front row, from left to right: Shushma Datt, Sangita Patel
Tareq shared how the war destroyed his family’s chocolate business, which was one of the largest in the region at the time. As a refugee in Canada, he rebuilt everything from the ground up. Peace by Chocolate is now one of the largest chocolate companies in Canada.
If you think his inspirational story is like a Hollywood movie, you are not wrong. You can now watch “Peace by Chocolate” (the movie) on your favourite streaming service.
Chris revisited his early struggles. He occasionally needed to ride the overnight bus just to stay warm for the cost of a fare before achieving success, including helping the Raptors win the championship in 2019.
Shushma, Georgia, and I also revisited our own experiences, moderated by the amazing Sangita Patel. The takeaway? Follow your passion, lean into your strengths, work hard, don’t give up, and dream big.
Other important takeaways: 1) Chris is incredibly tall! 2) Like me, Sangita is an electrical engineer, which I didn’t know. She is now one of the most engaging media personalities in Canada.
Thanks again to Simplii Financial for giving us the platform to share our stories!
P.S. All 7 episodes of “Bags 2 Riches” can be viewed on YouTube. I know you’ve probably seen enough of me. But, if you’re curious, catch Eva and on episode 4 🙂
Yesterday at TIFF, in the world’s premiere of The Movie Emperor, one of the A Laus watched the other A Lau cheekily cast as a movie star, also named Lau, seeking relevance via a film festival–baiting art-house role in director Ning Hao’s sharp satire of movie industry pretension.
Equally importantly, it was an honour for me to witness the one and only Andy Lau receiving the prestigious TIFF Tribute Award live. 🏆
From left to right: Karina Lee, Rick Mak, Eva Lau, Allen LauFrom left to right: Maggie Mok, HKETO (Toronto) Director Emily Mo, Eva Lau, Karina Lee
I wasn’t in that many pictures as I was too busy taking pictures and enjoying the show. 📸🎥
While many associate Wattpad primarily with storytelling (and they’re not wrong – after all, I am on IMDb!), it is important to highlight that Wattpad has also been an AI-driven company for well over a decade, long before AI became cool! 😉 We built our own “Story DNA” AI technology to generate insights from the world’s largest and most diverse sets of stories and data. Without AI, managing our billions of story uploads would be impossible.
It is also worth noting that I am an electrical engineer, which means I know a thing or two about semiconductors, energy, telecommunication, etc. In fact, all three partners at Two Small Fish Ventures, i.e. Eva, Brandon and myself, are engineers with BOTH software and hardware experience. We’ve been backing commercialized AI, semiconductor and advanced material companies like Ideogram, Ada, BenchSci, Zinite, Sheertex and many more for years.
As an engineer-turn-CEO-turn-investor who has been involved in deep tech for a long time, I will share a broad perspective of where deep tech is heading. Look forward to it!
Earlier today, TSFV announced our latest investment: Story Protocol. In short, Story Protocol is “Git for creative IP.” We backed the founders in late 2022, when the company was operating in stealth mode. Now, we’re committing additional funding in Story Protocol’s latest round, led by Andreessen Horowitz. So far, the company raised over US$54 million in funding.
Being part of the founding team of Wattpad – the world’s largest storytelling platform – the Two Small Fish Ventures team is especially excited about Story Protocol and what it means for creators and the industry as a whole. The internet is a co-creation and remixing machine, and this trend will be supercharged by Generative AI. Story Procol is building the core infrastructure for this era.
On a more personal note, I am also super excited to work with its co-founder Seung-yoon Lee. We know S.Y. Lee well from our Wattpad days, as he was the co-founder and CEO of Radish, a direct Wattpad competitor. Although we were once competitors, we’re now partners ready to usher in a new era for IP together.
It feels like it’s been ages since we were last here! In 2011, Union Square Ventures’ Albert Wenger led Wattpad’s Series A, our first institutional round. throughout the subsequent decade, Ivan and I made frequent visits to the USV office, be it for board meetings, the CEO Summit, or just casual get-togethers whenever we were in NYC.
Yet, my last visit was just before the pandemic hit. And after Wattpad‘s acquisition in 2021, circumstances didn’t permit me to return.
Until now.
USV has backed many iconic companies that have become household names — Twitter, Tumblr, Zynga, Cloudflare, Twilio, MongoDB, Etsy, Duolingo, to name a few.
Becoming an investor in these companies at a mature stage, or post-IPO, is straightforward. But what sets USV apart is that this team has spotted these future giants before anybody else, time and again. Often, these companies were budding startups with just a few team members and pre-revenue. To illustrate, when USV placed their bet on Wattpad, we had fewer than 10 on the team. While we weren’t exactly pre-revenue, it would still be years before many of our current revenue streams took off.
Throughout this journey, our learnings haven’t just come from the USV team. We’ve peer-learned so much from the network of USV portfolio CEOs and founders. The speed, intensity, skills and tenacity needed to navigate these rocket ships are on another level. A single misstep can derail years of hard work. What is at stake is unbelievably high. Interacting with these founders was tremendously helpful to me. I can testify that being part of the USV network played a part in Wattpad’s eventual success.
Post-Wattpad, the Laus has re-entered the USV fold as an LP. We’re also thrilled to be collaborating with USV’s Andy Weissman on an exciting new investment. Stay tuned for more updates on this front!
I’ve long wanted to craft a steampunk story on Wattpad. The allure of this science fiction subgenre, which fuses futuristic tech with 19th-century steam-driven aesthetics, has always captivated me.
But the initial draft didn’t meet my expectations. I lacked the time for refining, and equally challenging was crafting an appealing steampunk cover.
Ideogram.ai empowers individuals with generative AI, enhancing their creative capabilities.
Here’s how simple it is: I just typed:
Text says: “My Steampunk Story”. A male and a female wearing steampunk style fashion in Europe, 4k, cyberpunk., 3d render, cinematic, photo, typography.
…and voila!
What sets Ideogram apart is its ability to address a longstanding issue among popular AI image generators: rendering text in a spectrum of colours, fonts, sizes, and styles within images. Whether it’s lettering on signs or crafting company logos, it’s all achievable with a few keystrokes or taps.
Previously, I’d spend hours attempting to create a passable cover using tools I was hardly proficient in. Now, I simply describe my vision, and a polished cover is instantly brought to life. The process couldn’t be more effortless.
Last week, Two Small Fish Ventures announced our most recent investment in Ideogram AI, a Toronto-based generative AI company. The company was founded by former Google Brain researchers and launched with $16.5 million USD ($22.3 million CAD) in seed funding led by Andreessen Horowitz and Index Ventures. The round was actually closed at the beginning of 2023. We can finally talk about it now, as the company was in stealth.
The founders of Ideogram – Mohammad Norouzi, William Chan, Chitwan Saharia and Jonathan Ho – are renowned scientists who pioneered research in generative AI text-to-image systems. They’re also “the brains” behind Google Brain’s Imagen (pun fully intended).
Ideogram’s new product is transformative as it has successfully addressed an issue that has plagued many popular AI image generators to date: producing reliable text in varying colours, fonts, sizes, and styles within an image – be it lettering on signs or company logos – with just a few clicks, words, or taps.
For instance, when I typed:
“Cartoonish happy animals with a big sign that says ‘animal kingdom’, vibrant, graffiti, typography.”
The result was excellent. I can already imagine so many new use cases that weren’t possible before.
The stories behind this picture we took in Muskoka a few weeks ago captured four incredible world-dominating startups.
From left to right: Sally Daub, Zak Homuth, Katherine Homuth, Eva Lau, Allen Lau, Dennis Bennie
Eva and I started our careers at Delrina in the ’90s. Delrina was a fledgling startup with a modest team of just over 20 when she joined. When I joined nine months later, it reached nearly 100 people. Less than four years later, when Dennis Bennie, the CEO and co-founder, brokered a half-a-billion-dollar deal with Symantec, the company employed just under 800 people and became one of the world’s top 10 PC software companies. With over 90% of the market share, Delrina’s products were so dominant that we crushed all our competitors. Truly legendary.
Post-acquisition, Eva went to work for ATI, where she crossed paths with Sally Daub, then served as its General Counsel. ATI and its chief rival Nvidia emerged as the two world’s leading graphics chip players. In 2006, ATI was acquired by AMD for $5.4 billion. The transaction is one of the largest Canadian tech acquisitions. Probably still in the top three to date.
I’ll be succinct about Wattpad—it’s a story many are familiar with. We pioneered mobile reading, user-generated fiction, AI-and-audience-backed movies and many areas that resulted in billions of story uploads in over 50 languages, numerous world’s most-watched movies and 100 million users in virtually every corner of this planet.
Katherine and Zak Homuth’s Sheertex needs no introduction. In seven short years since its founding in Muskoka, the company became a world-famous household name and synonymous with unbreakable pantyhose. Three years ago, it took over the largest hosiery factory in Canada. To keep up with the demand, it is now moving into a space in Montreal three times larger. There is still so much headroom for growth.
These four Canadian companies are all world-dominating category creators.
As a passenger on the rocket ship, being the captain of the rocket ship and funding the rocket ship are three different skills. And yet, they’re intertwined, each amplifying the other. If you have never been on a rocket ship, it would be hard to imagine what a rocket ship looks like and spot the next one.
Eva and I have been immensely fortunate to wear multiple hats as employees, founders, and investors in many rocket ships. The timeless adage rings true: Surround yourself with the best. If you aim to be the best, work for the best and work with the best will help you learn from the best.
I thoroughly enjoyed yesterday’s fireside chat between OpenAI’s CEO Sam Altman and Shopify’s CEO Tobi Lutke!
Despite the downturn, it is a super exciting time to be an entrepreneur and an investor in tech startups. We are in the midst of a “once-in-a-decade” paradigm shift as a number of new tech trends emerge. Generative AI is one of them. When these new transformative technologies achieved mass adoption, they changed behaviour, democratized access, and unlocked values that weren’t possible previously. New startups will more easily challenge the old guards. An exciting time indeed!
Specifically, Altman said: “It should be a big moment for Toronto,” which I couldn’t agree more. In the last decade, Toronto has become one of the world’s AI epic centres. TSFV has already invested in many Canadian AI companies. Look forward to seeing the proliferation of a new crop of moonshots born and raised in your home and native land!
Thanks Lisa Zarzeczny and team Elevate for organizing!
No doubt Grand Tourismo 7 is one of VR’s killer apps! Although my Thrustmaster setup already has a brake pedal with an adjustable spring, a seatbelt and a manual transmission with a clutch to maximize the immersiveness, PS VR2 brings it to another level. Watch the video if you don’t believe me!
For instance, creating game-ready 3D assets is very challenging and time-consuming. Using Masterpiece’s 3D Generative AI, one can now create 3D assets with just a few words, such as “blonde viking with a beard.”
Millions of people are already creating games. Unity, one of the most popular game engines used by 2 billion monthly gamers, already has over 1.6 million monthly creators. Platforms like Masterpiece will further democratize game creation and unlock creativity amongst millions who never thought they would become game creators.
Check out Masterpiece Studio’s 3D Generative AI here.
Episode 4 of Bags 2 Riches is live! The docuseries features the roots of seven notable immigrants’ journeys while sharing their new life in Canada. The series relives the lows and celebrates the highs as each individual recounts the tests they faced.
I am honoured to be featured alongside NBA star Chris Boucher, Syrian-born chocolatier Tareq Hadhad, broadcast pioneer Shushma Datt and a few others. We are all immigrants who call Canada home, and we all want to contribute to this amazing country.
Despite two (!) flight cancellations and catching two (!) snow storms in Toronto and Halifax, my trip to Halifax last week was a blast!
First, I hosted an oversubscribed “office hours” at Volta. For those who couldn’t book a time, there is always a next time.
After that, I hosted a tech ecosystem dinner, where we had terrific conversations with many investors and accelerators in the tech ecosystem, and of course, some good food too 🙂
From left: Malcolm Fraser, Andrew Ray, Jeff Larsen, Rhiannon Davies, Jevon MacDonald, Ted Graham, me, Jonathan Saari, Matt Cooper
Lastly, I participated as a judge at Saint Mary’s University in Canada’s only VCIC (Venture Capital Investment Competition), an educational competition that provides students real-world experience in venture capital by simulating the venture capital investment process. The student VCs from across the country (e.g. University of Waterloo, University of Alberta, University of Toronto – Rotman School of Management, Queen’s University, Schulich School of Business – York University, University of New Brunswick, etc.) listened to pitches from real entrepreneurs and defended their investment choices to a panel of senior partners (i.e. me and other real investors).
I was super impressed by the quality of the students’ analysis, the term sheets they put together and their explanations. Equally importantly, we had a lot of fun, including the celebration and the after-party networking chat. Congrats again to all the winners!
It was such a (snow) blast. I will be back! Since Wattpad opened its second HQ in Halifax a few years ago, I have been coming to Atlantic Canada regularly. It is like a second home to me. No doubt this tradition will continue for many years to come!
Today is a big day for Two Small Fish Ventures as we reach first close of $24M for Fund III that targets $40M!
With the new and bigger fund, TSFV will continue to back early-stage startups using game-changing technology to achieve global scale. That has not changed. The difference is that we’ll be writing bigger cheques and leading more rounds. It’s a great time to invest as tech touches everything. It creates previously unthinkable opportunities for massive disruption. We will back early-stage companies that shift paradigms.
It’s a wrap! The massively successful 47th edition of TIFF is in the history books. For lack of a better term, this is the first ‘fully in-person’ TIFF since the beginning of the pandemic. There were many ‘behind-the-scene’ challenges that might not be obvious to the public. Kudos to the TIFF team for pulling this off.
A massive success also meant a disappointment to some who couldn’t get tickets because many screenings were sold out. For those who couldn’t get tickets, make sure you become a member before the next TIFF 🙂 In addition to supporting this iconic charitable organization, membership will give you many year-round perks, including early-access.
P.S. Don’t forget to check out this wonderful wrap-video!
After spending 15 years at the helm of Wattpad, today I am starting a new role as Executive Advisor to the WEBTOON family of brands. That’s right, I’m stepping aside as CEO of Wattpad to apply my experience and skills to this new role alongside my other activities as an investor and board member.
As I reflect on the journey of building Wattpad over the years I am amazed at what I’ve accomplished together with my co-founder Ivan Yuen and the entire Wattpad team.
What started as a place to read and write stories on your mobile device, has grown into a product and community loved by close to 100 million people.
We pioneered storytelling technology, changed how people read, write and engage with fictional stories, and transformed the entertainment and publishing industries. Leveraging our massive built-in fandoms and data, we turned numerous top Wattpad stories into hit movies, TV shows, and bestselling books. These movies and shows have topped the box office and ‘most watched’ charts on streaming services, gone on to win Teen Choice Awards, a People’s Choice Award, and even received Emmy nominations, and all have changed the lives of a new generation of creators. It’s been an honour and privilege to democratize who gets to tell their story and redefine how the world reads and shares fiction.
We raised record amounts of capital at the time from top-tier investors in Canada, US, and Asia. We were one of the first to commit to scaling our company in Toronto and then successfully proved you could build a world-class tech company here. We played a part in re-shaping the overall narrative of the innovation ecosystem in Canada.
These are the things you simply don’t think about when you’re starting out, writing code, and bringing an idea to life. To say I am incredibly proud is an understatement.
The past year was record-breaking for Wattpad. Since the acquisition – one of the largest for a Canadian technology company – we have never grown faster. With the Grand Plan in place, it’s the perfect time to pass the baton to Wattpad President Jeanne Lam and Wattpad WEBTOON Studios’ President Aron Levitz in leading the team to achieve the vision. With such strong leaders, Wattpad is in great hands.
I’ve always been a natural builder and I will continue to help build the “next big thing” as Executive Advisor to WEBTOON, as a venture partner of Two Small Fish Ventures, and board member of two of Canada’s most important cultural and innovation organizations, the Toronto International Film Festival and MaRS.
It has been a life-changing 15-year journey for me, my family, the Wattpad team, and millions of Wattpadders around the world. Thanks for all your support. Thanks for sharing all the emotions. Thanks for all the wonderful times and good memories. Thanks for being here with me. I can’t say thank you enough.
Calling this a new chapter or the next season would be a misnomer – it’s the final curtain call of my career as a CEO. But I’m not done yet! I’m still at the top of my game. I’m still hungry for more wins. I still want to make an even bigger impact. My new story begins today.
Recently Eva and I were able to take in the iconic Toronto skyline, hear the roaring of Niagara Falls, see stunning fireworks display against the backdrop of Parliament Hill, and visit the cobblestone streets and charming architecture of Quebec City — all in under an hour.
How? We visited Little Canada, an exhibit that takes you on a journey of discovery through the sights and sounds of our great country in miniature scale. A scale of 1:87 to be exact.
The Laus personally invested in Little Canada a few years ago, and one that’s been incredible to see come to life. We remember visiting the workshop in January 2018 and seeing the skill and dedication of Jean-Louis Brenninkmeijer and his team in creating the beauty of Canada’s vistas, its famous landmarks, and iconic cityscapes in miniature form. Now that the exhibit is open, it’s jaw-dropping to see the level of detail involved: every time we looked there was something new to discover.
As part of the Little Canada experience, Eva and I also got to try out the Littlization Station. We were scanned and our likeness will be 3D printed into our very own Little Me figurine that will get placed inside Little Canada. Way cooler than a bobblehead!
But perhaps the coolest thing about visiting Little Canada was this:
Can’t see it? Hang on, let’s get closer:
That’s right: Wattpad HQ exists in Little Canada, too. It was so fun to see our logo on a miniature building in the miniature St. Lawrence Market area of miniature downtown Toronto.
Here are a few more pictures from our visit. I hope you have a chance to explore Little Canada soon and see for yourself how this tiny experience delivers a big wow factor.
Last evening the Laus hosted an intimate dinner with a dozen of fellow C100 members in our backyard. After locking down for 18 months, we all appreciate what in-person gatherings can bring while pixels cannot. We had meaningful conversations about how the fantastic Canadian tech ecosystem can win in style on the global stage even more and many other topics. Thanks C100’s Lauren Howe for organizing and Andre Perey from Osler for co-hosting.
Look forward to more in-person gatherings as we are slowly but surely winning over the virus!
In honour of Asian Heritage Month, BenchSci hosted Showing Up, a discussion that delved into the experiences of four Asian panelists: Kepler’s CTO and co-founder Wen Cheng Chong, Wealthsimple Foundation’s CEO Leen Li, Backbase’s Regional VP of Customer Success Yuko Naka and me.
It was a wonderful conversation. You can find the summary on BenchSci’s blog or watch the whole panel on YouTube.
One thing I said that I would like to highlight: ‘You are the CEO of your own career.’
Culturally, many Asian parents have a strong influence on their children’s careers. Of course, it is great to listen to parents’ experiences and leverage their wisdom. However, your career decision is all yours. You are not your parents. Your interest is not the same as your parents’ interest. Most importantly, your career aspiration should not be a projection of your parents’ career aspiration. You are accountable for your career. Listen and learn, but chart your own path.
Last week, Naver, the South Korean internet conglomerate, announced the acquisition of Wattpad in a transaction valued at more than an estimated USD $600 million. The acquisition is expected to close in Q2 2021.
It has been an incredible roller coaster ride. So grateful that we have a fantastic outcome for everyone involved in this action-packed thriller!
The acquisition is all about accelerating Wattpad’s growth and taking our business to the next level. It is a match made in heaven because it aligns Wattpad and Naver’s WEBTOON, a leading digital comic publisher, under the same umbrella. Wattpad’s multi-platform stories are already available across audio, book, TV, and film formats. By joining forces with WEBTOON, our combined audience has almost doubled to 160 million people overnight. In one stroke, we also gain expertise in new formats like digital comics and animation. As a result, our entertainment ecosystem has greatly expanded. The synergy is so obvious.
The last few days certainly feel like winning the Oscar. The next step is to win the real one! Yesterday was the Season 1 finale of The Wattpad Story. Today is the first episode of Season 2.
The pandemic has forced many people to work from home. This can pose a challenge for people like me who are running a global business as travel is no longer possible. Well, the impact on me is less than you might think. Many people assume that I must be a globetrotter. This is anything but true. In the past few years, I have made a conscious decision to travel only when it is absolutely necessary. Even before the pandemic, airlines do not consider me as a top-tier frequent traveler anymore because I have already been using phone or video calls whenever I could to do my part to save the planet.
However, the unintended consequence is that I am glued to my electronic devices all the time. Although this is only natural as I run a digital business, if I could, I would always try to escape from the screens and be close to nature for a few minutes during a break.
This is one of the advantages of living in Toronto. Despite being the largest city in Canada, the large amount of green space has led to some people describing the city as a ‘city within a park.’ For us to continue to enjoy nature, I believe it is our collective responsibility to protect the environment and live a sustainable lifestyle. Not only do we have to battle with global warming, we also have to choose between planet or plastic. For example, I try to avoid single-use plastic whenever possible. The coffee that I drink is mostly fair trade, organic and it is filled in a reusable cup.
When choosing my investments, I would also like to invest my savings in a sustainable way. I believe companies should be held accountable for good management and sustainable business practices. That’s why I am excited to know that BMO has launched seven ESG (environmental, social and governance) ETFs, including the first balanced ESG ETF (ZESG) in Canada, to empower its customers to invest their savings in a sustainable way. These seven funds include:
BMO Balanced ESG ETF (ZESG): The first ESG asset allocation ETF in Canada, providing a one ticket low cost solution that includes both major equity markets and fixed income securities through a balanced asset allocation of 60 per cent equity and 40 per cent fixed income exposure.
BMO MSCI Global ESG Leaders Index ETF (ESGG)
BMO MSCI Canada ESG Leaders Index ETF (ESGA)
BMO MSCI EAFE ESG Leaders Index ETF (ESGE)
BMO MSCI USA ESG Leaders Index ETF (ESGY): These ETFs deliver ESG exposure by following the best in class approach of the MSCI ESG Leaders Indexes, while capturing market returns, by targeting the top 50 per cent ESG rated equities within sectors and industries, while excluding severe controversies and industries such as alcohol, gambling, tobacco, and weapons.
BMO ESG Corporate Bond Index ETF (ESGB)
BMO ESG US Corporate Bond Hedged to CAD Index ETF (ESGF): These ETFs invest in investment grade corporate bond fixed income issuers that have the highest MSCI ESG Ratings.
Every individual’s situation is different and hence the risk profile is different. These seven ESG ETFs deliver a full range of investment solutions across broad markets. From Canadian to global markets, from bond to equity, BMO has it all covered, which means we should be able to find one or more ETFs that align with both our financial and social values.
Note: This blog post was originally shared with Wattpad employees in early April. The following is the modified version for external consumption.
Quite a few people asked me what these previous crises looked like. I am fortunate enough to experience all four crises as a leader. I say I am fortunate because these experiences will help Wattpad navigate through the rough sea this time. Yes, this COVID-19 crisis is different because of its astonishing speed and magnitude. That said, crises always have an end date. This post will tell you how it was in previous crises and the lessons learned.
TLDR:
Don’t panic, but we need to be vigilant. We will get through this, but I need your full cooperation.
In late 1999, I was about to leave my job at Symantec. At that time, I was a young engineering leader building Windows products. But I was fascinated by the potential of internet products. In 1999, the most trafficked internet company was Yahoo. Amazon was a startup. Google was one year old. It would take another 2 years before Wikipedia was born. 5 more years before Facebook was born. That’s how early it was.
In March 2000, I joined Brightspark Labs, an internet incubator (somewhat similar to today’s Techstars and Y-Combinator). At any given point in time, there were about 10 different internet companies under the same roof, and I would be assigned to a couple of companies at a time to help them start or scale. It was fun. It also gave me the visibility of multiple companies.
March 2000 was also the peak of the dot-com bubble. Look at the peak in 2000 in the following chart. That was me standing there! It took another 15 years before NASDAQ to reach this level again.
You might also notice that the market didn’t crash overnight. Nasdaq lost about 80% of its value over a period of two years. When Nasdaq started to fall in April 2000, most companies actually kept hiring people. One of the Brightspark portfolio companies that I worked closely with (as their acting Head of Engineering) grew from 3 co-founders in March to over 50 people by summer. It was wild!
As the tech-laden NASDAQ continued the downward trend, investors started to panic. Funding started to dry up. All of a sudden, companies that were heavily relied on raising more capital to fund their operation discovered that the well had gone dry. When high profile companies like Webvan (the largest online grocery company, the Instacart at the time) and Excite@Home (the largest broadband internet portal and service provider in North America at the time) went bankrupt, the negative sentiment started to snowball.
Lesson 1: Never assume you can find investors to fund you.
As NASDAQ continued to fall, the negative sentiment started to spill over to other sectors. More and more consumer targeted dot-com companies started to lay off people or shut down. The aforementioned company that I worked for shrank from 50 to 3 in multiple rounds of layoffs (also within just a few short months). It was even wilder! When there was no investor and the revenue or profit couldn’t support the operation, layoffs were the only option.
Lesson 2: Revenue and profit do matter. A lot.
Initially, many of the backend focused tech companies, such as Nortel – at one point the most valuable Canadian company that employed 100,000 people – believed that they could be immune from the meltdown because they were suppliers to dot-coms but not one of the dot-coms. Wrong.
Then two planes flew into the World Trade Center in NYC on Sept 11, 2001. Good luck if you are hoping for a speedy recovery.
Lesson 3: If your customers are in trouble, you are in trouble too.
Exodus (the AWS before AWS) was another high profile causality. The following was quoted from Ben Horowitz’s The Hard Thing About Hard Things. I can’t say it better than him:
I got another sign when our largest competitor, Exodus, filed for bankruptcy on September 26, 2011. It was a truly incredible bankruptcy in that the company had been valued at $50 billion a little more than a year earlier. It was also remarkable because Exodus had raised $800 million on a “fully funded plan” just nine months earlier. An Exodus executive later joked to me: “When we drove off a cliff, we left no skid marks.” If Exodus could lose $50 billion in market capitalization and $800 million in cash that fast, I needed a backup plan.
Lesson 4: When your expenses are out of control, no one can save you. Don’t run out of cash. Just don’t. (note: this lesson may sound obvious but history is telling us that it is not that obvious to many people)
Even Amazon was reportedly close to running out of cash.
Lesson 5: If you could stay alive during the darkest moment, you would come out on the other end much stronger because your competitors are battered and bruised.
There were numerous high profile bankruptcies in the Silicon Valley and outside of the Valley. In the Valley, the office vacancy rate was sky high – rising to 20% from 0.6% percent only 18 months earlier – because so many companies disappeared. Unemployment rate in the Valley hit 10% (note: as a comparison in Feb 2020, US unemployment rate was 3.5%). I have a friend in the Valley who spent over a year looking for a job without success. He eventually decided to change career and moved elsewhere. He was not alone.
It is worth mentioning that despite these major shocks, the collapse was mainly contained in the tech sector. Yes, the spillover caused a recession in the broader market but it was relatively brief and shallow.
Around that time, I co-founded my first company Tira Wireless within Brightspark. Fortunately, Brightspark seeded the company so we didn’t have to worry too much about fundraising initially. My Wattpad co-founder Ivan joined Tira as one of the early employees after his last employer Delano turned off the light. Delano was another high profile bankruptcy in Toronto. It employed hundreds of people at one point but it went from boom (went public in early 2000) to bust in exactly 2 years.
Anyway, Tira was nimble, scrappy and resourceful. With just a handful of people in the company (I think seven), we moved fast, found a clear opportunity in the rapidly evolving market and built something that was good enough to attract an investor in late 2002. It was really tough to raise money at the bottom of the market. Terms were crappy. But at least we could continue to build the company.
Lesson 6: Keep hustling and be nimble. Crisis and market disruption always create new opportunities. Always.
With some additional capital in the bank, we had an ambitious plan ahead of us.
Then a new virus called SARS arrived in early 2003.
Fortunately, the virus disappeared quickly. It was mostly contained in Asia. That said, the recovery momentum was slowed substantially but there was no major shock. The US didn’t even enter a recession.
Between 2004 to 2007, a new crop of internet companies – collectively called Web 2.0 companies – started to emerge. These companies include many household names such as YouTube and Facebook. Of course, Wattpad started during this era as well. It was a great time to start a company because the competition wasn’t as fierce. Tech investors became active again. Tech experienced a Renaissance. Towards the end of this era, great and not-so-great companies all get funded. Valuation became a bit out of control (in the last decade’s standard). By the end of 2007 the unemployment rate in the Valley fell back to the dot-com bubble level.
At the same time, trouble signs began to emerge in the financial sector. Multiple financial giants faced liquidity problems. Lehman Brothers collapsed in Sept 2008 and the world officially entered the Great Recession. Tech unemployment rate went up to the post-dot-com record level as many tech companies went through rounds of layoffs or bankruptcies. Consider this as the dot-com bubble 2.0. Fortunately, other ailing financial giants were all bailed out by the governments. There was a spill over to many other sectors, like auto manufacturing, which the governments promptly bailed out as well. Thanks to the bailouts, the 18-month recession was deep but given the magnitude of the problem, it wasn’t painfully long. Around that time, Apple App Store emerged. Together with Android, the smartphone era officially began. After bootstrapping Wattpad for more than three years, we raised our first round of seed funding towards the end of 2009. 2009 also marked the beginning of the longest bull run of tech and the broader market in history until it ended abruptly last month.
This COVID-19 crisis is different in so many ways. It arrived at astonishing speed – in early March most of the world was still business as usual. Four weeks later, more than half the world is now locked down. COVID-19 is a pandemic while SARS was not. The magnitude of this current crisis is also unprecedented – it is a global, extremely severe, cross-sector recession. The following two charts clearly illustrate the magnitude of the fallout. According to NY Times, the weekly unemployment number was only capped at 6.6 million because the unemployment offices have been overwhelmed by the volume and couldn’t keep up! BTW, I now know the negative impact can be more than 100%. Please read the fine print on the second chart. I never knew it’s even mathematically possible!
Based on these numbers, it is not wrong to say:
dot-com bubble + Sept 11 + SAR + the Great Recession = COVID-19 x 10%
Therefore, we have to assume that this recession is going to be prolonged and severe. If it bounced back quickly, that’s great! But there is a good chance that it is not going to be a speedy recovery.
When things look black, there’s always a silver lining that we can learn from the survivors and the casualties. The former has cash. The latter ran out of cash. As simple as that.
And there are only two ways to improve the cash position: earn more and spend less. And we have to play both offense (i.e. seize the new opportunities) and defense (i.e. conserve cash) simultaneously.
To recap: these are the six lessons I learned from previous crises that are also applicable now:
Lesson 1: Never assume you can find investors to fund you.
Lesson 2: Revenue and profit do matter. A lot.
Lesson 3: If your customers are in trouble, you are in trouble too.
Lesson 4: When your expenses are out of control, no one can save you. Don’t run out of cash. Just don’t.
Lesson 5: If you could stay alive during the darkest moment, you would come out on the other end much stronger because your competitors are battered and bruised.
Lesson 6: Keep hustling and be nimble. Crisis and market disruption always create new opportunities. Always.
Allow me to drive home the point one more time: earn more, spend less and we will survive the storm stronger than ever.
As we enter the final hours of the 2010s, to reflect and look forward I would like to share a couple of very contrasting collages. One was taken this year. The other was taken exactly 10 years ago.
Wattpad grew ~100x in virtually every single dimension – number of employees, the size of the office, number of users, number of stories shared but more importantly the positive impact on the Wattpad communities, our employees, our city and millions of lives we touched.
Two Small Fish Ventures grew from a side project to a VC firm with tens of rocket ships in the portfolio.
Most importantly, although the size of my family has not grown 100x (thank God!), my two little girls + an amazing lady has become two amazing young ladies + an even more amazing lady. They are the most influential on the most influential. They are the best and unquantifiable.
Look forward to 100x our impact on 100x more people in the 2020s!
It’s a situation founders know well: the agonizing wait to see if the product/service they’ve launched will take off. The reality is, it takes months and even years to find product-market-fit. And once that happens, the struggle doesn’t really end because there’s always another, more complex problem to solve. It can begin with product-market-fit then morph into customer/user acquisition and engagement and then shift to monetization. For entrepreneurs, building a business can feel like a never-ending cycle of wait-and-see.
When we launched Wattpad 13 years ago, my co-founder Ivan and I immediately started monetizing with ads. And when I say we “immediately monetized” the site, I really mean we earned $2 in monthly ad revenue a full year later. A minuscule amount.
When we first launched our Android app, we saw about 10 downloads in the first month. Even in 2011 when Android really started to take off our download numbers were still puny.
Today, we see more than 60,000 Android users sign up every day and half of our daily usage comes from Android users. Our monthly advertising revenue is in the hundreds of thousands of dollars. We’re no longer talking about trivial amounts. It’s been a long road that had to start somewhere.
‘Everything starts small’ is a valuable mantra for any entrepreneur. Look at Spotify: When it first launched in the US in 2010 it had 100,000 paid subscribers. Today, Spotify’s number of paid subscribers is about to cross the 100 million mark.
Not too long ago, we launched Paid Stories and we also introduced a subscription model called Premium at Wattpad. The numbers are still small. But they won’t stay that way forever (especially since we’ve rolled out these programs globally). As long as we keep improving, keep optimizing and keep promoting — basically, if we continue to hustle and grind as all great entrepreneurs do — the numbers will go up.
But we can’t expect a silver bullet. No single feature or no single promo or no single country launch will 10x these numbers overnight. While it’s not impossible to find a 10x growth hack, the reality is that it’s probably better to find 100 little things to grow 10%.
My fellow entrepreneurs, please remember: Tomorrow will be better than today. The day after tomorrow will be better than tomorrow. Everything starts small.
A few months ago, Wattpad announced a partnership with Anvil Publishing in the Philippines. Together, we’re launching Bliss Books, a new Young Adult imprint that’ll bring some of the biggest Wattpad stories and authors to bookshelves across the country.
The news means Wattpad can realize the vision I laid out in the Master Plan much, much faster. But really, speed is just one of the values a strategic partner brings to the table.
Anvil also has deeper insights into local purchasing habits and consumer behaviour than we do. The first part of the Master Plan is to “Discover more great stories,” and we do this by leveraging our Story DNA machine learning technology and a passionate community to find unique voices and amazing stories that are validated in Tagalog. With their local insights, Anvil can corroborate our insights using their local knowledge to guarantee a successful adaptation.
The best strategic partners also have a reputation you can piggy-back off of. Another element of the Master Plan is ‘Turn these stories into great movies, TV shows, print books, etc.,” Anvil has a reputation for publishing high-quality books, and that’s exactly what we want to do.
Anvil is the publishing arm of the National Book Store with hundreds of bookstores. It’s established presence means we – through NBS – have the ability to distribute Wattpad books to every practically every part of the country tying into another key part of the Master Plan to “Distribute and monetize content on and off Wattpad and earn money for storytellers.”
The Philippines is one of Wattpad’s largest markets and a very important one since its home to some of our most passionate users. Plus, when you factor in the expertise and reach of Anvil, it was an easy decision to partner with this local company who can help us continue to celebrate and reward Filipino authors and their fans.
Entrepreneurs: if you have the ability to form a partnership with another complementary company, seize it. The strategic upside is great and may help you realize your vision faster than you ever could alone.
Collision is the fastest-growing tech conference in North America, and for the first time ever, this past may the event was held in Toronto. I had the opportunity to join a panel on what it takes to scale companies and ecosystems. Check out the video:
Managing unprecedented growth from Web Summit on Vimeo.
Earlier today Eva announced on Two Small Fish Ventures’ blog that she has raised $9 million in the first close of TSFV’s Fund II. It is exciting to see her transformation from an entrepreneur to an angel investor and now a VC.
TSFV’s investment thesis remains the same. Fund II will continue to invest globally in early-stage tech companies with strong network effects. The goal is to help nurture them into global tech giants. She has made investments from the new fund already, including Printify and several more about to close.
There is no doubt Canada’s tech ecosystem is thriving. Access to capital is no longer the biggest roadblock for startup successes as we now have a lot of great investors in Canada. That being said, there is still one big gap in the Canadian venture capital ecosystem: very few venture funds are actually co-founded by internet entrepreneurs and product creators who have massive successes. In contrast, in Silicon Valley, there are numerous successful internet entrepreneurs turned VCs. They can recycle their experience and knowledge of building and scaling a product to reach millions of users. This is exactly what we would like to do and why TSFV is special: we will recycle our unique knowledge in building and scaling internet-scale companies to help other entrepreneurs to be successful.
It is also worth noting that TSFV is not just providing capital. Through Creator Circle, a group of successful entrepreneurs and product creators who are investors in Fund II, we are providing a mini ecosystem of like-minded, entrepreneurial people who are also recycling their invaluable expertise to help TSFV portfolio companies achieve escape velocity. When TSFV invests in a company, all these creators are part of the team because the success of the company directly affects their investment. They have skin in the game.
Expect more announcements in the coming months as the final target for Fund II is $15 million. There will also be more investment announcements as TSFV can now write more cheques (and bigger cheques!) with follow on investments too.
About a year ago I read an article about Jeff Bezos’ approach to meetings at Amazon that really resonated with me. Specifically, there were three things that make meetings more effective and efficient that really stood out to me.
The Two-Pizza Team Rule – According to Jeff Bezos, Amazon tries to “create teams that are no larger than can be fed by two pizzas”
No PowerPoint – “No PowerPoints are used inside of Amazon,” Bezos proudly declares. “Somebody for the meeting has prepared a six-page…narratively structured memo. It has real sentences, and topic sentences, and verbs, and nouns–it’s not just bullet points.”
Start with Silence – “We read those memos, silently, during the meeting,” says Bezos. “It’s like a study hall. Everybody sits around the table, and we read silently, for usually about half an hour, however long it takes us to read the document. And then we discuss it.”
Like Bezos, I’m a big believer in small group meetings. Based on my experience, it’s too difficult to have a conversation that’s relevant to most if there are more than eight people in the room.
I don’t necessarily 100% agree with no PowerPoint, though. Yes, there are times when having a narrative works better, but in some cases, bullet points can be more effective. One can’t replace the other. Use the right tool at the right time for the right people.
What I found really interesting is the study hall format. Since learning about, I’ve tried it out in multiple meetings by allocating the first 5-10 minutes (not 30 minutes as Bezos suggests) so everyone can go through the document or deck and add their questions and comments in advance of the discussion. Here’s what I observed:
The Pros
It ensures everyone has read the materials and the context is fresh in people’s mind (and yes, I know meeting organizers can always send materials in advance as pre-reading, but people still have to carve out time in their schedule to get it done. This is especially difficult for people who attend lots of back-to-back meetings).
It provides dedicated time for pre-reading that is already built into the meeting (similar to the point above)
It helps reduce the amount of context switching so the quality of the conversation goes up noticeably because the context is so fresh in everyone’s mind.
The quality of the questions improves because people don’t have to multi-task in the meeting, i.e. listen, read, absorb AND ask at the same time.
The Cons
It means less time to talk, especially when meetings are only 30 minutes long (but IMO, we get this time back in a way because we might have wasted those 5-10 minutes getting attendees up to speed anyway).
As you can tell, I become a fan of the study hall format, and while I recognize it doesn’t work for every type of meeting, it’s helpful when teams need to be on the same page with specific background information. That’s when spending 5-10 minutes to make sure everyone is “in the zone” is well worth it.
Incorporating the Study Hall format to your next meeting gives you time: Time for understanding; Time for extended reflection; Time for focused thinking; All of which leads to better and more effective meetings.
The Wattpad team is growing and we’re hiring for many roles. Recently, the team was in the position of having to choose between two highly qualified candidates for a single role (a great problem to have). One applicant had more experience or skill but the other one had a better attitude.
So who did we pick? Well here’s what I told the team:
“All things equal, always choose attitude over skill and experience. Skills can be learned, but it is hard to change one’s attitude.”
Of course, all candidates need to meet certain skill-based criteria, whatever that may be. It’s hard to hire someone in finance if ‘spreadsheet’ is an unfamiliar term. It doesn’t make sense to hire an engineer who has never written a line of code before. These are somewhat facetious examples and IRL the bar would be set much, much higher, but you get the point.
Hiring a person who may be less experienced but possess the right attitude can be a worthwhile investment and a risk worth taking if you believe you can get the candidate 80% up to speed in 3 months and 100% up to speed in 6 months.
With the right attitude one can overcome any obstacles, but when people have the wrong attitude, getting them to fit into the company can be mission impossible because of the inevitable cultural clashes and teamwork disruption. It can drag down the performance of the entire team. People with positive attitudes can solve problems proactively rather than reactively. While it’s hard to quantify, they can greatly increase business velocity and team performance.
Choosing attitude over skill is a guiding principle that I have been using for many years and has served me really well!
The next time a candidate walks through your door and doesn’t exactly have the right skills or experience, ask yourself if they have the right attitude.
For any entrepreneur launching an app finding product-market fit is a lot like finding the Golden Ticket; it’s rare, but when it happens it’s life-changing.
Unlike an enterprise business, when you build a consumer app your end-user can’t easily tell you what they want (vs. enterprise apps that are focused on solving a known problem or a pain point for clients). Think about it this way: Before the iPhone launched, no consumer research would point out the need for a touchscreen, keyboardless device. Before Snapchat, no consumer would say they wanted the ability to send ephemeral messages.
Consumers aren’t able to tell you what they want; this makes consumer products a shot in the dark. There is no guarantee if or when product-market fit can be found. It’s usually a long journey of continuous iteration.
And ongoing iteration is what gets you to product-market fit. Each iteration gives you one extra at-bat. Hitting a home run is easy if you can strike out 10o times instead of 3. Y Combinator’s Sam Altman said it best in this tweet:
Finding product-market fit is hard. Look at how many consumer products Facebook and Google shut down even with their massive resources (remember FB Paper, FB Groups app, Google+ app?) Massive resources can help, but it’s not the most critical.
In the early days of Wattpad, despite only having a handful of employees, every day the product looked a bit different. We implemented new concepts in the morning, checked in the afternoon, measured overnight and killed it the next morning if it didn’t work out. That’s how we found product-market fit in many things. And that’s how we left our competitors in the dust.
Although finding product-market fit is freaking hard, it is also very fun and rewarding once you have figured it out.
When you work at a startup, seeking advice and gaining buy-in from the broader team can help you move faster … until it becomes a crutch.
Recently, I bumped into an entrepreneur I invested in. He’s making some changes to the direction of his company, and after explaining them to me, I pointed out some of the potential issues. He immediately asked me: “So, do you want me to revert to the old plan?”
It was the wrong question to ask.
I explained to him that it doesn’t matter what I want. As CEO, with all the context, he’s the only one who can make that decision. As an investor, I’m not thinking about his business 24/7, but he is. It’s his company, and it’s his decision what he does with it (and only his decision). Investors should share their experiences and opinions, but they shouldn’t make decisions that affect the business.
Not long after, I had an investor friend contact me about one of his portfolio companies that’s going through a pretty rough patch. My friend said: “The CEO now blames the board of directors for making the wrong decision.” My ears perked up. This was a red flag and I told my friend as such.
A company’s board of directors only has one decision to make: Hire and fire the CEO. Inexperienced CEOs have a tendency to defer difficult decisions to the board or even other people in the company. It’s not uncommon to hear a newbie (or unconfident) CEO say something like “My recommendation to the board is …” This isn’t helpful. All this does is enable inexperienced board members to jump in and make decisions out of context. It’s tragic, really.
Obviously, I’m not suggesting that there is no value to be gained from consulting with your board: Every CEO has blind spots and can benefit from another perspective. But in the end, what happens in the business is always the CEOs call.
And it doesn’t always have to be the CEO who holds the ultimate decision-making ability (nor should it). I remember speaking with a senior leader at Wattpad, and the person said: “I would advise we do this …” I quickly reminded this person that they are the head of the business unit and the only person accountable for it. It was an important decision with huge implications across the company, so of course, I expected this person would engage with the broader team to think through the different scenarios and make sure all the bases were covered, but at the end of the day, the person was the leader, not an advisor.
These three conversations illustrate one critical point. Whether you’re a co-founder, CEO, technical lead, department manager or even individual contributor, you are the presumed expert in your role, so don’t dodge making tough decisions. Remember: You are not an advisor to your own job.
I spoke with an entrepreneur whose company is building a new, disruptive product for the education sector. One of the challenges he’s facing is that none of the company’s co-founders have worked in the education sector before. He wondered if he should hire someone with some relevant experience.
Another entrepreneur friend of mine is building a tool that is catered to the public sector. The company is struggling to scale as a business. The sales process is too slow. The product is becoming too specific for one sector.
In both cases when these entrepreneurs asked for my advice, I told them: Don’t be a parasite if you want to be a disruptor.
There are so many verticals out there that still have not been fully transformed by the Internet — education, public sector, book publishing, the list goes one. But it’s extremely hard to transform any industry if you have a lot of dependencies with the old systems. You can’t think out of the box. Your sales cycle is too long. And often you end up with a product or a service that is incremental at best rather than revolutionary.
Now, there’s nothing wrong with that. In fact, a lot of people have built great businesses by providing incremental solutions like consulting services to the government. But, if you want to build something truly transformative and net-native, then you have to stay as far away from the traditional systems as possible and draw closer to your end users or customers.
If you want to create something truly game-changing and be a disruptor, you can’t begin the journey as a parasite.
As a startup scales, it’s natural for tension to creep up among different teams who are working on disparate objectives. Either of these conversations sound familiar?
“Showing users more ads can help generate more revenue, but it could also hurt engagement. Do we optimize for revenue or engagement?”
“We have a limited budget. If we spend it on A, B, and C we won’t be able to pay for X, Y, Z. What should we choose?”
The best way entrepreneurs can embrace and then ease tension among their teams is to establish a set of principles. Principles can help teams avoid indecision and move fast.
In the example above about serving ads at the expense of user engagement for instance, if the team has previously established that ad experiments can’t impact engagement by more than X%, it becomes easier for them to test different combinations of ads to drive the most revenue without negatively impacting engagement.
Establishing principles streamlines decision making, eliminates unnecessary meetings and propels the company forward. Everyone knows what to do and understands how much (or how little) leeway the team has.
Of course, there will be times when you may not have a principle to fall back on. That’s when the teams representing the conflicting priorities need to escalate the matter further and involve an arbitrator. Most times decisions are reversible and having an arbitrator can resolve issues quickly. In the world of startups, a quick decision always trumps a slow decision (or worse, no decision at all).
Tension is natural and a sign your company is growing. But as your business grows and becomes more complex, decisions aren’t as straightforward as they used to. Creating a set of ground rules that inform your team’s priorities and outcomes can help avoid unnecessary confusion and conflict.
When I first became a manager, one thing that was extremely difficult for me to get used to was delegation. When an employee gets promoted to manager, and even after they realize they now have a different and distinct role, it can be hard to let go of the day-to-day work.
Why? In many cases, the person who gets promoted to a leadership or a manager position is someone who is an awesome individual contributor. To be an awesome IC, you need to be very good at getting stuff done.
But as a leader or a manager, you need to focus on asking other people to get stuff done.
You need to make sure your team is working on the right stuff to achieve desired outcomes. As a manager, you can’t do the work of other ICs – it no longer in your job description.
This is counter-intuitive and crazy hard because it is the polar opposite of what awesome ICs know so well.
Speaking from experience, when a leader does the work of an IC it can be very demotivating and become counterproductive. On the other hand, when a manager delegates the work and trusts individuals to get the job done it can be very motivating.
As a leader, you should remember that it is far better for you to focus on figuring out what your ICs should do (and why), and let the ICs figure out how to get the job done (and then, do it).
I first started managing people when I was 26. Four years later, I was managing a team of 30 developers. On paper, I was fantastically successful; in reality I should have fired myself.
At the time, I thought that in order to lead a team of awesome developers, I had to be an even more awesome developer. I worked frantically to write more code than anyone else not realizing that I accepted a new job the moment I was promoted – and writing code wasn’t it.
It’s something that almost all new managers forget. Being a manager isn’t a glorified version of your old job: it’s a brand new and completely different role. It requires a different skill set and attitude. As a manager, your responsibility is to ensure your team works on the right things at the right pace to deliver the right outcomes.
In my 30s, without any management or leadership training under my belt, I didn’t have a clue how to direct such a sizeable team. As a newbie manager I made mistakes and added further complexity to an already chaotic organization. It was only years later when I truly realized how my lack of leadership contributed to the chaos. I still cringe thinking about it.
I’m not proud of those mistakes, but I learned a lot from them. My biggest takeaway was that being a manager isn’t about rolling up your sleeves and working alongside your team (although there are times when this matters); it’s about understanding where your organization wants to go and deploying your team and resources to get you there.
If you’re a new manager who’s still doing the same work as before, step back and delegate. And, congratulations on your new job.
The new year means a fresh start. With that in mind, I urge product managers, designers, engineers and developers – anyone who helps develop a product, really – to think critically about the features they are designing. Have you thought about what features you’ll say goodbye to in January? Becausekilling features now means better business velocity for the rest of 2019.
As a product and its codebase grows, it is not uncommon to see an increase in technical debt. This debt may be because usage of a feature has scaled beyond its original design (you can’t expect a Toyota Corolla to reach 300 km/h no matter how many turbochargers you add) or because a feature, and subsequently it’s code, is used in more ways than originally intended (like a lawn mower turned into a snow blower – it works, but it shouldn’t). Often, technical debt accumulates because old or infrequently-used features aren’t retired.
There is a cost of removing these old features, of course, but removing features is significantly cheaper in the long-run than maintaining relic code. When you support outdated or unused features you’re also allowing security, performance and backwards compatibility issues to arise.
I remember reading an article about Evernote that claimed 90% of their features (and they have thousands of them) are used by less than 1% of their users. Eventually, the company’s velocity grounded to a halt because every simple feature update required numerous discussions across the company before the change could be implemented.
So make no mistake, it is desirable and even essential to purge old product features. Here’s how in three steps:
First identify a feature that you think should be retired. Then measure the usage of that feature. The data won’t lie. If usage is low, proceed to step two.
The numbers may not tell you the whole story. Talk to some of the old-timers who have more context than you and understand why the feature existed in the first place. In many cases, you’ll be surprised by the reasons.
Decide to purge, modernize or maintain the status quo. Make a decision and then execute your action plan.
Years ago, I was part of a team that dedicated six months to find bugs and purge unused features. On the surface, it seemed we were spending an inordinate amount of time and effort ‘looking in the rear-view mirror’ and not working on things that took the product forward. In reality though, those six months pushed the product much, much further ahead. By the end of it the product ran faster, the UI was cleaner because many unused features were gone, and annoying glitches were finally addressed. The app went from 1-star to 5-star in a few months without adding anything new.
It’s a good reminder: Less is more. Simple is good.
Before we rung in the new year, Wattpad released its Year in Review, highlighting the trends and community movements that defined the year on the global entertainment platform. In a year when people around the world were pushing for progressive social change, Wattpad’s community of 70 million users broke new ground in literary representation and created a safe space online for marginalized voices and their stories.
From #MuslimRomance to Mental Health Awareness, Wattpad stories celebrate inclusivity across characters and genres. Check out the full Year in Review below:
A slew of international tech companies – Google, Uber, Samsung, Microsoft, Amazon – have committed to or expressed interest in setting up shop in Toronto. If you’re a homegrown startup or scaleup you can’t help but think about the implications of having these giants in your backyard.
Companies often expand their footprint to lower costs, access specialized talent or for a host of other reasons. It’s not new. They aren’t the first international companies who want to set up shop in Toronto, and won’t be the last.
And why not? Toronto is a world-class city with some of the best universities in the world producing some of the finest technical and business talents. We’re home to an incredibly diverse community who have the perspective and understanding to solve global issues and build products and services that work for the world.
Colleagues and friends have recently been asking me for my take on these moves. Are they helpful or harmful to the city and the local tech ecosystem?
In my opinion, we should welcome these moves – but be wary of them.
When a few foreign companies decide to move to a burgeoning city, they can help build a critical mass that directly supports homegrown companies by spurring interest in the region. They attract high caliber talent and then provide opportunities for these employees to hone their skills and learn new ones so they can further develop into well-rounded and in-demand workers.
But too many foreign companies in a single locale can make it seem like they’ve colonized the area, leaving little room for local businesses. It gets too difficult to compete, too expensive to stay in your backyard. Think about this: If data is the new oil, do you really want all the ‘oil companies’ to be foreign-owned?
So it’s not a choice of either-or. Having zero international companies who operate locally won’t stimulate the ecosystem. With too many foreign companies, locals lose the ability to control their our own destiny, and eventually, ideas and innovation become stifled.
For now, I welcome these new companies into our backyard but make no mistake, it can never replace building our own homegrown giants. I’m certain that the incredible Toronto tech ecosystem will continue to make waves regardless of who moves next door.
Over the years I’ve attended thousands of meetings. The best ones respected my time and input. They kept me engaged – and often excited – throughout the meeting. And the worst ones … well, I’m pretty sure we’ve all attended at least a few terrible meetings and know what that’s like.
Having seen the good and the bad, I wanted to share some simple tips that anyone, at any level, can implement for more effective meetings.
Go beyond the agenda Yes, circulating a clear agenda prior to the meeting is important, but also consider explicitly spelling out the objective and the outcome of the meeting. It gives participants the right context to prepare for and be fully engaged during the meeting (or decline the meeting if they can’t help meet the objectives/outcomes).
Nominate a facilitator This person makes sure the agenda is followed and desired outcomes are met. They empower all participants to contribute and get the group back on track if the conversation goes awry. Facilitating meetings is a special skill and not everyone is good at it but if you find the right person, you are practically guaranteed a great meeting. Keep in mind that the meeting organizer doesn’t have to be the facilitator.
Limit participants Keep meetings participants to 4-7 people maximum. In my experience this really is the sweet spot. Beyond 8 participants, the introverts in the group tend to shy away from voicing their opinions (a good facilitator, though, can help draw out their perspectives and ensure introverts have a voice).
Forget the update Don’t use a meeting to provide or ask for updates. Save it for email, or better still a collaborative Google Doc. Share these updates in advance of the meeting as pre-reading material so you can focus the discussion on healthy debates and decision making.
Save 10 Use the last 10 minutes of the meeting to recap the discussion. This is crucial. You’ve just spent the last hour having a productive discussion, it would be a shame for it to fall apart in the follow-up. Make note of the essence of the discussion, key decisions made and actions to take. Be sure to share these notes with all attendees and other stakeholders who couldn’t join.
Slight tweaks to the way organize your meetings can have a profound impact. Know of any other hacks to make meetings more effective? Let me know in the comments.
At some point in your career, someone you know will a) ask for an introduction to someone else in your network, or b) offer to make an introduction to someone they feel you should know.
Email introductions can be a double-edged sword. On one hand, obviously, they can be incredibly useful. On the other hand, they can suck up a lot of time if not done properly.
The very worst email introductions automatically assume that the connection being made is appropriate and beneficial for the involved parties. But the truth is, unless you’ve explicitly asked in advance, this is just an assumption.
Here’s an example of an email I recently received:
Hey Allen,
I would like to introduce you to Cindy Lou (cc’ed). Cindy Lou is an expert in X, which you will find useful. I’m sure you would enjoy the meeting. I’ll let you two find the best time to meet next week!
Cheers, Horton
The problem is, while Cindy Lou might be an expert in X, I don’t really care about X; it’s just not my thing. Naturally, I don’t want to spend even more time feigning interest in X. And I definitely don’t want to waste Cindy Lou’s time either. The other problem: Despite what Horton thinks, I’m mostly out of the office next month, so I can’t find a time to meet without a lot of calendar shuffling.
I used to accept blind introductions (and subsequent meetings) like these out of politeness. It was an ineffective use of my time – and theirs. Even when I dared to say no, I had to spend time crafting a firm yet polite email to decline the opportunity. Drafting the email didn’t take up nearly as much time as a meeting would, but it still took time out of my day that could be better spent on other challenges. Eventually, it became too much.
Nowadays, when people ask me to connect them with someone in my network, I make sure I have a double opt-in. This means I’ve asked for—and received—the permission of both parties before I send a note. Here’s what it looks like:
Pavel would like me to connect him with John.
I’ll ask Pavel to send me a new, well-written email with the request (Pavel should NOT include our previous conversation i.e., the original request). It could look something like this.
Hey Allen,
As discussed, it would be great if you could introduce me to John. Here is a summary of my ask: <insert awesome summary here>
Thanks in advance for your help.
Live long and prosper, Pavel
Then, I would add a sentence or two before forwarding the note to John (without including Pavel). My addition would provide further context and could be something along the lines of: “I don’t know Pavel well, and I haven’t tried his products, but the elevator pitch sounds relevant to you” or “Pavel is brilliant and working on a super interesting project you might be interested in.” This context setting is important, but should only take 30 seconds of your time.
If John agrees to the introduction, then I add Pavel to the thread. If he says no, I’ll let Pavel know that as well.
Double opt-in email introductions work well for a number of reasons.
The onus is on the person requesting the introduction to write an awesome email detailing why the connection is valuable. It’s not the facilitator’s responsibility to make the case.
It avoids putting people in an awkward position of accepting a connection or meeting when there is zero interest in the product/service/pitch.
It encourages frank dialogue. If a person wants to decline an introduction, chances are he/she is more likely to provide a candid reason in a private one-on-one email with a trusted connection. It allows the facilitator to filter the information appropriately while still providing a truthful explanation to the requester.
It allows for brevity without sounding cold. Since the facilitator has established relationships with both parties, a to-the-point email doesn’t come off as arrogant or rude.
One more thing—please don’t write the email as though it came from me. Each person has a unique writing style and voice, and I have mine, too. You won’t be able to capture my voice exactly.
I make lots of introductions, and I am more than happy to do so. It’s great for community building. I hope the double opt-in method helps make introductions faster and a better experience for everyone!
Both my parents used to work for a bank. For them, the work day started at nine in the morning and ended at 5:00 pm sharp. Day in and day out, this was their routine. They never understood the concept of flexible hours. They questioned why I would bring “work” home. On the other hand, they were always amused that I never needed to take time off work to see the doctor or get the car fixed during office hours.
“Am I expected to work an 8-hour day?” I get this question from employees from time to time, but I believe this is the wrong question to ask. Employees are expected to get their work done, deliver on OKRs and contribute to a positive workplace culture. For the most part, I don’t (and neither should their direct manager) care where or how the work gets done. Of course, it goes without saying (but I’ll still say it), flexible work hours should never impact collaboration or attendance at critical meetings.
Startups are fast-paced, ever-changing environments filled with bright employees. They’re solving complex and fascinating problems and it’s all very exciting. Being a disruptor and part of a paradigm shift is thrilling and the work itself should compel employees to give 100%. Offering flexible hours instills trust in your team and gives employees a sense of ownership to execute on projects in the way that works for them.
That’s not to say there will be no instances when burning the midnight oil for a specific project or tight deadline is required. Make no mistake, there will be times when a critical security issue needs to be addressed after-hours or a client has an urgent need on the weekend. But there should also be opportunities to take it easy and spend a few weeks out of the country or deal with a family or health issue. It’s about flexibility.
Most startups offer flexible hours, and it makes sense. After all, tech is a creative industry unlike working at a bank or factory. As people head back to work after their relaxing summer vacations, my advice to founders and startup execs? Measure productivity by outcomes and results, not timecards.
I wholeheartedly believe that diversity is a strength. Entrepreneurs can’t build a global product without understanding and embracing the spectrum of identity, gender, ethnicity and language found all around the world. Building a diverse team that reflects the people you serve is crucial to long-term success. It’s easy to say diversity is important, but how do you measure it?
Today’s post is from Wattpad’s Head of Product and Head of Wattpad Labs Seema Lakhani. Like me, Seema is a huge champion of inclusion and diversity. Her post outlines the results of Wattpad’s 2018 Diversity and Inclusion survey that aims to understand how employees self-identify and tracks how empowered they feel within the company.
I strongly encourage all companies – startups, scaleups and corporate giants – to track and share results of their diversity and inclusion efforts. The first step in creating a diverse and inclusive tech industry for the future is to understand where you are right now.
Here’s the full post:
2018 has been a year of challenge and (some) change for the diversity movement in tech. The struggles of minority groups in the industry are finally a mainstream conversation, even as real change lags for many.
At Wattpad, we’ve long recognized that diversity is our strength. Our company culture, our teams, our ability to innovate, and ultimately our product, are all made stronger by the variety of perspectives, experiences, and voices that make up Wattpad.
Wattpad’s commitment to diversity has been established since Day 1. The fact that we were founded by two people of colour (one of whom is an immigrant), in Canada (one of the most diverse countries in the world), has helped us maintain a more diverse perspective than most technology companies. Early in Wattpad’s existence, we made the decision to make Wattpad community safety a top priority. This ethos deeply informs how we approach our platform and how we build our teams. As a result, Wattpad has always been a safe and diverse place for both users and employees.
WHERE WE ARE TODAY
It’s been a year since we released the results of our 2017 Diversity & Inclusion Survey. Our goal is to be a leader in transparency around these issues, showing exactly what we’ve done to create an inclusive workplace.
We’ve now completed our 2018 Diversity & Inclusion Survey.* This year, we’ve expanded the survey for a better understanding both the representation and sentiment for different groups across Wattpad. We know that building a diverse workplace isn’t just a matter of numbers; it’s equally important to understand that people will have different experiences of a workplace. This year’s Diversity & Inclusion Survey attempts to understand how people feel about diversity at Wattpad and if our efforts towards inclusivity account for how marginalized people experience life here.
DIVERSITY AT WATTPAD
Today, we’re proud to say that a majority–56%–of Wattpad employees are women. That strong representation is reflected across most teams: women make up 50% of our Leadership Team, 50% of our User Experience and Design Team, and 100% of our Product Team.
We’re incredibly proud of those numbers, but know there is still work to do. For example, less than a quarter of our Engineering team are women, so that will be a continued area of focus for us in the coming year.
For a more intersectional look at our team composition, we’re proud to say that People of Colour make up close to half (45%) of all Wattpad employees and 41% of our Leadership Team. Company-wide, 21% of Wattpad employees are Women of Colour, 15% are non-native English speakers, 8% identify as having a disability, 13% identify as LGBTQ+, and 3% are transgender.
Diversity at Wattpad – Highlights
INCLUSION AT WATTPAD
Sentiment questions help us better understand how marginalized people feel about working at Wattpad. We know the experiences of a workplace–its communication styles, and organizational structures and processes–can be different for men, women, people of colour, and LGBTQ+ folks. So, it’s important that we create a space in our survey for people to express those experiences, helping us understand if we’re headed in the right direction.
We were happy to hear that, in most instances, there were no large gaps in sentiment among the diverse groups and identities that make up the team at Wattpad. While there is room for improvement, there were no major disparities between how different groups experience life at Wattpad. All areas saw an increase in sentiment from 2017.
When asked if they agree that “People from all backgrounds have equal opportunities to succeed at my company,” 75% of women and 77% of People of Colour agreed. At Wattpad as a whole, 80% agreed.
Similarly, when asked if they agree that “My Company Values Diversity,” 92% of women and 91% of People of Colour agreed. Company-wide, 94% agreed with this statement in 2018, up from 85% in 2017 and a true testament to our Diversity & Inclusions Committee’s hard work throughout the year. When asked if they agree that “I can be my authentic self at work,” 82% of women and 77% of People of Colour agreed. Eighty-one per cent of Wattpad employees overall agreed. When we dug even deeper into the intersectional data for this question, we found that while 88% of white men and 85% of white women agreed they can be their authentic self at work, only 80% of men of colour and 75% of women of colour agreed.
When it comes to voice, 79% of employees and 75% of women agreed that “When I speak up my opinion is valued.” This number was lower for People of Colour (68%) and Non-Native English speakers (58%). While both of these were improvements from last year, they still highlight the work we need to do to ensure all employees feel safe and valued when contributing at Wattpad.
Inclusion at Wattpad – Highlights
WHAT’S NEXT?
2018 has been a year of growth and expansion at Wattpad. We’ve grown our team, expanded our work in entertainment around the world, continued to lead the future of interactive storytelling, and deepened the learnings and applications from Machine Learning to the more than 500 million story uploads on Wattpad. Our community is growing every day. This means new voices coming to Wattpad from all over the world. A diverse and inclusive company culture means more voices and experiences to challenge assumptions. It means broader perspective and fewer blind spots. It means better products for users everywhere, built by happy, safe employees, who can truly be themselves and thrive.
Our Diversity & Inclusion Survey is the result of a team of people who have worked hard to better understand and improve our workplace. These results show what is possible when a company empowers employees with the financial and people resources to research, listen, and take action on diversity and inclusion initiatives. But they also demonstrate areas for improvement.
Diversity at Wattpad is about creating more diversity in tech overall. We’ve taken a leadership position in transparency, holding ourselves accountable to continually do better and making sure our stakeholders are aware of our efforts to create a more diverse company. Our team should match our community, which is why we’ll keep listening, learning, and pushing ourselves to do better, until we get there.
*Results for our 2018 Diversity & Inclusion Survey are based on participation from 84% of employees.
Building a global product requires intent and sustained commitment. From launch day, entrepreneurs need to think globally and take international users, their interests and habits into account. When Wattpad launched over a decade ago, some of our very first users were based in Asia. our international community has thrived since then, and now we have 65 million users in nearly every country of the world and support over 50 languages.
Today is a huge milestone for Toronto-based Wattpad: We announced a landmark production deal with Indonesian-based iflix, the world’s leading entertainment service for emerging markets, to bring Wattpad stories to millions of iflix users across Asia, the Middle East, and Africa. Over the next year, iflix and Wattpad will co-produce dozens of original movies based on Wattpad stories from Indonesia. You can read all about it in the official blog post here.
Wattpad has more than 17 million users in Southeast Asia, and Indonesia is one of our fastest-growing markets. Fans of the six million original Indonesian stories on Wattpad will soon be able to enjoy them in a completely new format.
Wattpad adaptations can be massively successful (Netflix’s The Kissing Booth, anyone?) Stories that are adapted into other formats already have a built-in audience that love and follow the story on and off the Wattpad platform. Our proprietary data gives producers insights into the story they can’t find anywhere else. We can tell production teams what characters resonate with the audience, what plot points generate the most intense reaction from fans and more. These detailed insights lead to more awesome adaptations. Then, when an adaptation is ready, Wattpad has the ability to promote the book/movie/series to a global audience of over 65 million people, including targeted marketing to the story’s original fans.
This iflix partnership is one more step towards cementing Wattpad as a global entertainment powerhouse. We know that Wattpad can dramatically improve the success of traditional entertainment projects, and the industry is catching on.
I love gadgets. They surround me everywhere – in the office, in the car, at home. I’m always connected … except when I go completely off the grid.
Twice a year I unplug for 2-3 weeks. I turn off my data. I don’t reply to email. I stay off social media. I take a break from being an entrepreneur and focus on being a husband and a dad.
It’s during these weeks when I’m unplugged that I have an opportunity to reflect on the past challenges and think about future opportunities. Going off the grid gives me a sense of clarity and enables a freedom of thinking I can’t achieve when I’m constantly pulled in multiple digital directions.
Case in point: I recently spent three weeks in Asia with my family. While I’ve traveled throughout the region extensively for work, this was the first time I could experience cities like Taipei and Shanghai as a tourist. I got to enjoy a ride on the fastest train in the world, eat the most delicious food, and shop like the locals do. I observed, indulged and enjoyed without the need to constantly check my devices. And while I was technically off-the-grid and not working, my offline experiences provided me with inspirations I will take back to the office.
Building a business is hard. Entrepreneurs have infinite to-do lists. They are constantly pushing ahead through one challenge to seize the next opportunity. While the line between work and personal life is becoming more blurry (especially when you’re scaling a startup), it’s critical that entrepreneurs carve time out of their hectic schedules and go offline. A digital detox – even for a short period of time – yields tremendous business and personal benefits.
If you still have a summer vacation planned, I challenge you to use your time to explore, discover and connect IRL.
Years ago, a summer job gave me one of the most valuable lessons in entrepreneurship.
I needed tuition money for university so I got a job at a factory printing t-shirts. I witnessed firsthand how the owner juggled multiple and often diverse tasks in order to operate a successful business. Looking back, I was naive to think that a t-shirt printing company was just about printing t-shirts.
If you look at the journey of an entrepreneur, it all starts with an idea. But an idea is just that – a thought. Without execution, an idea is as good as yesterday’s newspaper. Only when execution follows an idea, can you determine if there’s product-market fit. If you achieve product-market fit – congratulations, that’s a major accomplishment! You can start a company to further iterate on the idea and cement your place in the market. But once you start a company, you have to turn it into a business.
I’ve personally gone through this journey three times. My first business failed, I sold the second one, and the third has become one of Canada’s most successful startups. My experiences failing and succeeding as an entrepreneur reinforced the lesson I learned that summer many years ago: As an entrepreneur, the best product you can build is yourself.
You will wear many hats throughout the entrepreneur journey. As your company grows, you play different roles in the company and you can expect to change ‘jobs’ every few months. Each new job requires a different skill set. You may start as the product designer, but soon you’ll lead a team as a manager, and then eventually you transition into a leadership role. I have yet to meet a single person who, at the launch of their company, has every required skill. So welcome continuous learning and crave self-improvement.
Taking the time to build yourself as a well-rounded entrepreneur will pay dividends.
I’m Allen and I’m a serial entrepreneur, angel investor and a champion of the Canadian startup ecosystem. Welcome to my new blog where I plan to share my ideas, insights and inspirations.
I like to write. Over the years I’ve probably shared in excess of 300,000 words. I’ve contributed to media outlets like Inc. and Entrepreneur. My previous blog, Making Things Out of Nothing, covered technology trends, my latest investments and company milestones. For several years, I’ve also maintained an internal blog to communicate with 100+ employees around the world. This private blog encompasses everything from company strategy to technology shifts to management advice. Through my internal blog, I created a lot of content that’s applicable to many people, but discoverable by few.
My hope is that this new blog changes that and becomes a central place for me to share the things I’m passionate about more broadly. And yes, of course, there will be a ton of new content as well. I know there is no shortage of business and tech insights available on the internet, but I believe I can offer a different perspective – from a scale-up or Canadian lens, for example – that sometimes can be difficult to find.
So what am I passionate about?
I’m passionate about entrepreneurship. I’ve launched three companies; the first one failed, I sold the second one, and the third, Wattpad, has grown from a reading and writing app, to a global entertainment powerhouse with a vision to entertain and connect the world through stories (and is well on its way). Both failures and successes have taught me valuable lessons and I’m excited to share these lessons with others – it’s my way to pay it forward so others can avoid (and learn from) the mistakes I’ve made.
I’m a believer in the power of the innovation economy to transform the world by creating a virtuous cycle of disruption and innovation. As both an entrepreneur and investor, I’ve seen some incredible ideas that will dramatically change the way we work, live and play.
As a proud Canadian and as an immigrant myself, I am certain that diversity is a strength, especially in the workplace. It’s no vanity metric either, I can cite numerous examples where diversity powered progress and drove real business results.
So what can you expect from this new blog? In a nutshell, I’ll share my experiences, ideas and even advice about the things that matter to me – entrepreneurship, startups, tech and innovation, leadership, diversity and a whole lot more.
Welcome to Allen’s Thoughts. I’m excited to have you here!
Note: This blog post was originally shared on BetaKit, Canada’s startup and tech innovation publication of record.
This weekend, while celebrating Canada Day with family and friends, and in the midst of a constant stream of news about a growing trade war with the US, I had a chance to reflect on the future of this country and our economy.
Canada’s economy is the 10th largest in the world, of which a massive 70.7 percent comes from services. We are unusual among developed countries in that some of our largest industries are oil and forestry, natural—and finite—resources that contribute huge amounts to Canada’s economy. Canada has the world’s third-largest proven petroleum reserves and is the fourth largest exporter of petroleum. We are also the fourth largest exporter of natural gas.
While the oil industry helped propel Canada to the top 10 in the world, the good times won’t last forever. Why? This price history of solar cells says it all: since the 1970s the per-watt cost of solar energy has fallen from more than $76 to less than 74 cents.
The genie is already out of the bottle. Renewable energy will create a dramatic shift in demand for oil and gas. In the next decade, the energy sector will see more change than it has in the past century.
Canada also has a sizable manufacturing sector, particularly in the automobile industry. However, more often than not, Canadian plants are merely branches to foreign companies. Unfortunately, Canada has no ownership in the brands and the intellectual properties that are very valuable and have lasting value.
Entertainment is another major sector for Canada, employing hundreds of thousands of people and representing close to 2.8 percent of our GDP. While many Hollywood TV and movies projects are produced in Canada, we capture few of the upsides; even if a locally-produced project is a mega-hit, we’re still providing a service to the Hollywood studios. Studios based in Los Angeles can easily choose to make their next movie somewhere else if Canadian locations aren’t price-competitive. Unlike Hollywood, Canada’s rich and creative entertainment industry heavily relies on government subsidies and remains transactional.
Energy and entertainment create many jobs in Canada, but we all know that industries can turn on a dime. Case in point: the ongoing trade war with the US. Canada can’t solely rely on oil and providing services to foreign companies to sustain our growth in the future.
Canada’s economy needs a second act. Fast.
The good news is that we have all the raw material to pull it off. How? Canada has already emerged as one of the world’s leaders in artificial intelligence and blockchain. Ethereum-one of the most important blockchain-based technologies-was born in Toronto. As such, the city has a disproportionate number of blockchain experts. AI and blockchain are two great examples of why Canada is leading the pack in the new data-driven economies. At the moment, the top 10 most valuable companies in the world are data-driven tech companies. This includes the likes of Amazon, Apple, Microsoft, Tencent, Alibaba, Alphabet and Facebook. Data is clearly the new oil.
With a thriving tech ecosystem and abundance of experts in leading fields like AI and blockchain, Canada has the potential to create the next generation of tech giants.
Canada’s leadership has led to many foreign companies to set up their AI research labs here. But you’d be right to point out that this just recycles a problematic model, in which foreign companies control these important jobs and retain intellectual properties generated by publicly funded research.
These are valid concerns. At the same time, we see a virtuous cycle emerge from this situation, in which (often) foreign companies help attract and retaining talent in Canada, benefiting the country in the long term. That said, if all of the new jobs created by these data-driven companies are all foreign-owned, it will be a missed opportunity for Canada. We’ll be reproducing what we now see in the auto and the entertainment industries. Canada could have created a Ford or a Warner Brothers decades ago.
The solution is not to prevent foreign companies from setting up shops here. Tariffs and walls are not the solutions. Just look at the Valley. Many foreign companies open up branch offices there, but the domestic firms are all thriving at the same time. If Canada produces many billion dollar companies, who cares if Amazon opens up an office here or not?
What Canada really needs is an environment where many—not just one or two—domestic world-class tech giants can emerge. The kind of companies that make a lasting impact on the Canadian economy. Fortunately, the seed has been sowed. For the first time, the environment has been created for domestic data-driven tech firms to thrive and succeed. I know because I’m the CEO & co-founder of Wattpad, one such company. In Canada’s technology sector, the wind is at our back. It is up to us to pull this off.
I am absolutely grateful for the opportunity to lead one of the rocket ships that is helping Canada pull off its second act.
INCLUSION AT WATTPAD 
WHAT’S NEXT? 
