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.
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 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.
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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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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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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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 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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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 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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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 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.
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 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.
P.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 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.
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.
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.
“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.
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.
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.
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.
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.
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.
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.
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!
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.
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.
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.
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 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!
