investing

The AI Bubble That Is Not When Everyone Is All In

At the beginning of this year, I wrote an op-ed for The Globe about what many were already calling the AI bubble. Nearly a year later, almost all of what I said remains true. The piece was always meant to be a largely evergreen, long term view rather than a knee jerk reaction.

The only difference today is that the forces I described back then have only intensified.

We are in a market where Big Tech, venture capital, private equity, and the public markets are all pouring unprecedented capital into AI. But to understand what is actually happening, and how to invest intelligently, we need to separate noise from fundamentals. Here are the five key points:

Why Big Tech Is Going All In while Taking Minimal Risk.
The Demand Side Is Real and Growing.
Not All AI Investments Are Created Equal.
Picking Winners Matters.
Remember, Dot Com Was a Bubble. The Internet Was Not.

1. Why Big Tech Is Going All In while Taking Minimal Risk

The motivations of the large technology companies driving this wave are very different from those of startups and other investors.

For Big Tech, AI is existential. If they underinvest, they risk becoming the next Blockbuster. If they overinvest, they can afford the losses. In practice, they are buying trillions of dollars worth of call options, and very few players in the world can afford to do that.

The asymmetry is obvious. If I were their CEOs, I would do the same.

But being able to absorb risk does not mean they want to absorb all of it. This is why they are using creative financing structures to shift risk off their balance sheets while remaining all in. At the same time, they strengthen their ecosystems by keeping developers, enterprises, and consumers firmly inside their platforms.

This is not classical corporate investing. Their objective is not just profitability. It is long term dominance.

For everyone outside Big Tech, meaning most of us, understanding these incentives is essential. It helps you place your bets intelligently without becoming roadkill when Big Tech transfers risk into the ecosystem.

2. The Demand Side Is Real

AI usage is not slowing. It is accelerating.

The numbers do not lie. Almost every metric, including model inference, GPU utilization, developer adoption, enterprise pilot activity, and startup formation, is rising. You can validate this across numerous public datasets. Directionally, people are using AI more, not less. And unlike previous hype cycles, this wave has real usage, real dollars, and real infrastructure behind it.

Yes, there is froth. But there are also fundamentals.

3. Not All AI Investments Are Created Equal

A common mistake is treating AI investing as a single category.

It is not.

Investing in a public market, commoditized AI business is very different from investing in a frontier technology startup with a decade long horizon. The former may come with thin margins, weak moats, and hidden exposure to Big Tech’s risk shifting. The latter is where transformational returns come from if you know how to evaluate whether a company is truly world class, differentiated, and defensible.

Lumping all AI investments together is as nonsensical as treating all public stocks as the same.

4. Picking Winners Matters

In public markets, you can buy the S&P 500 and call it a day. But that index is not random. Someone selected those 500 winners for you.

In venture, picking winners matters even more. It is a power law business. Spray and pray does not work. Most startups will not survive, and only the strongest will break out, especially in an environment as competitive as today.

Thanks to AI, we are in the middle of a massive platform shift. Venture scale outcomes depend on understanding technology deeply enough to see a decade ahead and identify breakout successes before others do. Long term vision beats short term noise. Daily or quarterly fluctuations are simply noise to be ignored.

5. Dot Com Was a Bubble. The Internet Was Not.

The dot com era had dramatic overvaluation and a painful crash, but the underlying technology still reshaped the world. The problem was not the internet. It was timing, lack of infrastructure, and indiscriminate investing in ideas that were either too early or simply bad.

Looking back, the early internet lacked essential components such as high speed access, mobile connectivity, smartphones, and internet payments. Although some elements of the AI stack may still be evolving, many of the major building blocks, including commercialization, are already in place. AI does not suffer from the same foundational gaps the early internet did.

Calling this a bubble as a blanket statement misses the nuance. AI itself is not a bubble. With a decade long view, it is already reshaping almost every industry at an unprecedented pace. Corrections, consolidations, and failures are normal. The underlying technological shift is as real as the internet was in the 1990s.

There is speculation. There are frothy areas. And yet, there are many areas that are underfunded. That is where the opportunities are.

⸻

History shows that great venture funds invest through cycles. They invest in areas that will be transformative in the next decade, not the next quarter.

For us, the five areas we focus on, including Vertical AI platforms, physical AI, AI infrastructure, advanced computing hardware, and smart energy, are the critical elements of AI. Beyond being our expertise, there is another important reason why these categories matter: Bubble or not, they will thrive.

We are not investing in hype, nor in capital intensive businesses where capital is the only moat, nor in companies where technology defensibility is low. As long as we stay disciplined and visionary, and continue to back founders building a decade ahead, we will do well, bubble or not.

After all, there may be multiple macro cycles across a decade. Embrace the bubble.

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.

Quantum: From Sci-Fi to Investable Frontier

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.

P.S. If you enjoyed this blog post, please take a minute to like, comment, subscribe and share. Thank you for reading!

Five Areas Shaping the Next Frontier

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.

P.S. If you enjoyed this blog post, please take a minute to like, comment, subscribe and share. Thank you for reading!

Backing the Scientists Who Helped Invent Blockchain with SureMark Digital

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.

P.S. If you enjoyed this blog post, please take a minute to like, comment, subscribe and share. Thank you for reading!

Quantum Isn’t Next. It’s Now.

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.

At Two Small Fish, our thesis is centred around the next frontier of computing and its applications.

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!

Wattpad Was My Regular Season. TSF Is My Playoff Hockey

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.

Back in the Trenches in a Different Role

Now at Two Small Fish Ventures as an operating partner, I work with founders across our portfolio. I am no longer the operator inside the company, but I get to be their sounding board — helping them tackle some of the biggest challenges they face.

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.

P.S. Go Oilers!!

Gensee AI

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.

Written by Brandon

Investing in Fibra: Revolutionizing Women’s Health with Smart Underwear

At Two Small Fish Ventures, we love backing founders who are not only transforming user behaviour but also unlocking new and impactful value. That’s why we’re excited to announce our investment in Fibra, a pioneering company redefining wearable technology to improve women’s health. We are proud to be the lead investor in this round, and I will be joining as a board observer.

The Vision Behind Fibra

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.

Announcing Our Investment in Hepzibah AI

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. 🙂

Contrarian Series: Your TAM is Zero? We love it!

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.

Just before New Year, I was speaking at the TBDC Venture Day Conference together with BetaKit CEO Siri Agrell and Serial Entrepreneur and former MP Frank Baylis.

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!

P.S. Don’t forget, if you have an “exit strategy” slide in your pitch deck, please remove it before pitching to us. TYSM!

How We Built a Truly Global Powerhouse with 100 Million Users

Most people don’t realize just how global Wattpad’s business is. Here are a few fun facts:

• Only 25% of our 100 million users are from North America, while 25% come from LATAM, 25% from Europe, and 25% from Asia.

• Of the 50 languages on Wattpad, the most popular isn’t English—it’s Spanish. Other widely used languages include Bahasa Indonesia (10 million users) and Tagalog (6 million users), with millions more reading and writing in Italian, French, German, Portuguese, Vietnamese, and many others.

• Not only have our print books (yes, we’re a book publisher too) been New York Times bestsellers, but they’ve also hit #1 in multiple countries, including Germany and Colombia.

• #1 on Netflix globally and other streaming platforms? We’ve done that many times—including the Spanish smash hit A Través De Mi Ventana (Through My Window), which we co-produced with Netflix. Many #1-rated TV shows worldwide are based on Wattpad stories—and we co-produce them.

• #1 at the box office? We’ve achieved that in multiple countries as well.

How did we build this?

A lot of things made this happen, but I’ll highlight a few. It started on day one. Here’s a screenshot of our website when we launched in 2006.

Notice that we already supported many key languages worldwide. Why? Because only about 400 million people speak English as their first language—that’s less than 5% of the world’s population.

And we were right! The first language that took off wasn’t something we predicted—it was Vietnamese. We couldn’t have guessed that!

When the first Android phone came out (the T-Mobile G1), we were one of the first to support it. At that time, the iPhone was primarily a high-GDP country phenomenon, while low-GDP countries were dominated by $30 Android phones. When I travelled to these regions, I frequently brought back bags of inexpensive phones so our team could test and ensure our app worked on low-end devices. This allowed us to dominate globally.

When we raised growth capital, we didn’t just seek funding from Silicon Valley investors—we broadened our investor base to include backers from other countries. This helped us learn the nuances of international expansion while gaining support from investors who understood these markets.

When we launched subscriptions, we recognized that a one-size-fits-all model wouldn’t work. Some countries preferred à la carte purchases over all-you-can-read models. So, we introduced our own virtual currency, allowing users to buy content à la carte.

When we expanded into movies and TV shows, we didn’t just partner with Hollywood studios—we forged partnerships with entertainment companies across five continents. This ensured Wattpad story adaptations could be seen everywhere.

And the list goes on.

None of this happened automagically. It took years of conscious, deliberate effort. But once we built the foundation, expanding into new countries became incremental. There’s no free lunch, but it’s also not rocket science—it got easier and easier as we grew.

We built a truly global powerhouse with 100 million users.

If we could do it, you can too.

Choosing between the U.S. and international expansion is a false dichotomy—you can do both. As the world shifts toward intangible assets, building a global business is easier than ever.

Keep in mind that while the U.S. is the largest economy, it only accounts for approximately 26% of the world’s GDP. To create true optionality, not expanding globally—especially beyond the U.S.—is not an option.

Our experience in building a successful global business also allows us to help our portfolio companies scale internationally. We’ve been through the challenges of global expansion firsthand, and we actively share these insights to support the next generation of world-changing companies. Reach out to us if you want to be part of it!

P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.

Contrarian Series: Best Exit Strategy? Not Having One

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.

The Three Phases of Building a Great Tech Company: Technology, Product, and Commercialization

There are three distinct phases in the journey of building a great tech company: technology, product, and commercialization. These phases are sequential yet interconnected and sometimes overlap. Needless to say, mastering each is critical to the company’s eventual success. However, it’s important to recognize their differences.

• Building technology is about founders creating what they love. It’s driven by passion and expertise and often leads to groundbreaking innovations.

• Building a product is about creating something others love to use. This is where usability and solving real problems come into focus.

• Commercialization is about building something people will pay for and driving revenue. This phase transforms users into paying customers or finds someone else to pay for it, such as advertisers.

These phases are related but distinct. Great technology doesn’t guarantee anyone will use it, and a widely-used product doesn’t always lead to revenue. I’ve seen many technologists create incredible technologies no one adopts, as well as popular products that fail to commercialize effectively (though it’s rare for a product with tens of millions of users to fail entirely).

For deep tech companies, these phases often have minimal overlap and unfold sequentially. The technology might take years to develop before a usable product emerges, and commercialization may come even later.

In contrast, shallow tech B2B SaaS products often see complete overlap between the phases. For example, a subscription model is typically apparent from the outset, and the tech, product, and commercialization phases blend seamlessly.

Wattpad is also a good example of how these phases can play out differently. Initially, we built our technology and product hand in hand, creating a platform loved by millions of users. However, its commercialization—whether through ads, subscriptions, or movies, the three revenue models we had—was deliberately delayed. Many people assumed we didn’t know how to make money without understanding this counterintuitive approach (but of course, we purposely kept some of our strategies under wraps). This approach allowed us to use “free” as a potent weapon to dominate—and eliminate—our competitors in a winner-takes-all strategy. Operating for years with minimal revenue was clearly the right decision for the market dynamics and our long-term goals. More on this in a separate blog post.

Given this variability, asking, “What is your revenue?” must be thoughtful and context-specific. For some companies, the absence of revenue may be an intentional and brilliant strategy. For others, insufficient revenue could signal serious trouble. It all depends on the company’s stage, strategy, and goals. Understanding the sequence, timing, and specific needs of a business model is crucial for both investors and entrepreneurs. Zero revenue could be a blessing in the right context. On the other hand, pushing for revenue growth—let alone the wrong type of revenue growth—can be fatal, a scenario we’ve seen many times.

At Two Small Fish Ventures, we are very thoughtful and experienced investors. We understand that starting to generate revenue—or choosing not to generate revenue—at the right time is one of the secrets to success that very few people have mastered. We practise what we preach. Over the past two years, all but one of TSF’s investments have been pre-revenue.

No revenue? No problem. In fact, that’s great. Bring them on!

Our Secret to Finding 100x Opportunities

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.

Bridge Technologies are Rarely Great Investments

More than two decades ago, I co-founded my first company, Tira Wireless. The business went through several iterations, and eventually, we landed on building a mobile content delivery product. We raised roughly $30M in funding, which was a significant amount at the time. We even ranked as Canada’s Third Fastest Growing Technology Company in the Deloitte Technology Fast 50.

We had a good run, but eventually, Tira had to shut its doors.

We made numerous strategic mistakes, and I learned a lot—lessons that, quite frankly, helped me make far better decisions when I later started Wattpad.

One of the most important mistakes we made was falling into the “bridge technology” trap.

What is the “bridge technology” trap?

Reflecting on significant “platform shifts” over recent decades reveals a pattern: each shift unleashes waves of innovation. Consider the PC revolution in the late 20th century, the widespread adoption of the internet and cloud computing in the 2000s, and the mobile era in the 2010s. These shifts didn’t just create new opportunities; they also created significant pain points as the world tried to leap from one technology to another. Many companies emerged to solve problems arising from these changes.

Tira started when the world began its transition from web to mobile. Initially, there were countless mobile platforms and operating systems. These idiosyncrasies created a huge pain point, and Tira capitalized on that. But in a few short years, mobile consolidated into just two major players—iOS and Android. The pain point rapidly disappeared, and so did Tira’s business.

Similarly, most of these “bridge technology” companies perform very well during the transition because they solve a critical, short-term pain point. However, as the world completes the transition, their business disappears. For instance, numerous companies focused on converting websites into iPhone apps when the App Store launched. Where are they now?

Some companies try to leverage what they’ve built and pivot into something new. But building something new is challenging enough, and maintaining a soon-to-be-declining bridge business while transitioning into a new one is even harder. This is akin to the innovator’s dilemma: successful companies often struggle with disruptive innovation, torn between innovating (and risking profitable products) or maintaining the status quo (and risking obsolescence).

As an investor, it makes no sense to invest in a “bridge” company that is fully expected to pivot within a few years. A pivot should be a Plan B, not Plan A. It’s extremely rare for bridge technology companies to become great, venture-scale investments. In fact, I can’t think of any off the top of my head.

We are currently in the midst of a tectonic AI platform shift. We’re seeing a huge volume of pitches, which is incredibly exciting. Many of these startups built great technologies and products. However, a significant number of these pitches also represent bridge technologies. As the current AI platform shift matures, these bridge technologies will lose relevance. Sometimes, it’s obvious they’re bridge technologies; other times, it requires significant thought to identify them. This challenge is intellectually stimulating, and I enjoy every moment of it. Each analysis informs us of what the future looks like, and just as importantly, what it will not look like. With each passing day, we gain stronger conviction about where the world is heading. It’s further strengthening our “seeing the future is our superpower” muscle, and that’s the most exciting part.

Canada risks losing out on the GREATEST prize: ownership of industry-disrupting companies and technologies

Thank you to The Globe for publishing my op-ed about the recent capital gains tax increase last week. The piece is now available here.

Once again, to summarize, as the world shifts to intangible assets, the consequences go far beyond brain drain and job loss. We risk losing out on the GREATEST prize: ownership of industry-disrupting, IP-based companies and technologies. This aspect, often overlooked, is illustrated with real-world numbers.

Not having significant ownership of these assets in the information age is equivalent to not having electricity and oil in the industrial age. This would have a devastating and long-term impact on our economy and reputation on the world stage. Canada would be left behind with digital breadcrumbs, selling our next generation short.

The policy change clearly didn’t take this into consideration. Saying that it impacts only 0.13% of the population is so wrong on many fronts. It is abundantly clear that it will impact EVERYONE.

Don’t forget to tell them.

Here is the full copy of my op-ed:

The Liberal government is increasing taxes on investment. Anyone experienced in entrepreneurship and investment knows this will stifle growth. We are at tremendous risk of losing our brightest entrepreneurs – along with the high-skilled jobs they create – to other countries.

This is evidenced by a new survey conducted after the capital-gains tax changes: Just 5.3 per cent of Canadian founders believe Canada is the best place to grow a company.

As the world shifts to intangible assets, the consequences go beyond brain drain and job loss. We will lose out on the greatest prize of the innovation economy: ownership of industry-disrupting companies and technologies. This would have a devastating and long-term impact on our economy and reputation on the world stage.

I will admit that this latest change to taxation has an immaterial impact on me personally. Wattpad, the company I co-founded, was acquired by Korean internet giant Naver for $840-million in 2021 so I’ve already paid my dues as stipulated under the budget at the time. But my experience illustrates how this tax change is detrimental to Canada and future generations.

Because I raised most of the capital from outside of Canada, only half of the company was owned by Canadians, including founders, employees and investors. In other words, when Wattpad was acquired, $420-million of the economic value left our country.

Before the tax hike, it was reported that when our tech startups become scaleups, about 75 cents out of every invested dollar comes from outside of Canada. This means many of these fast-growing companies are already majority-owned by foreigners.

As a venture capitalist, I see this trend play out all the time. The firm I co-founded, Two Small Fish Ventures, has a portfolio of 50 early-stage tech companies. We are the only Canadian investor in many of our recent investments. Foreign investors, especially U.S. investors, are aggressively writing cheques to own a significant portion of these early promising Canadian startups when they are relatively inexpensive.

The tax increase will only exacerbate this problem.

When a company’s assets are purely intangible, and its biggest investors and markets exist outside Canada, it’s natural and far easier for the company to move outside Canada or be acquired by foreigners, such as Wattpad. Needless to say, the economic value creation postacquisition is also captured outside of Canada.

One might argue that these companies create many jobs in Canada, so we still captured some value, right? Well, again, when a company’s assets are mostly intangible, the majority of the economic value created is captured by its IP, not the jobs created. As an example, Wattpad’s payroll was about $30-million per year, not small, but it is a minuscule number compared to the nearly billion dollars that the company was valued at.

There’s also a tectonic shift under way across the innovation economy. The rise of AI and related fields such as semiconductors in particular is an order of magnitude more capital-intensive than previous generations of tech companies. Canada has produced some of the best AI researchers in the world, but when 40 of Forbes’ 2024 AI 50 List are in the U.S. (and more than 30 of them in Silicon Valley) while only two are in Canada, we could have and should have owned a much bigger piece of the pie.

The best example is OpenAI, which was co-founded by Ilya Sutskever, a Canadian. The company is based in San Francisco. The majority of its employees are not in Canada. All the major investors are U.S.-based. Canada only has the bragging rights.

And, do I have to remind everyone that Elon Musk is also Canadian?

In the post-pandemic world, capital and talent are more mobile than ever. The pull to move to other countries is also stronger than ever. Canada is already becoming the best training ground for other countries to capture the value created by these companies outside of Canada.

I want Canada to win. I really do. What motivates me now as an investor is to help create more homegrown Canadian tech giants – and to keep them in Canada. My job just got much harder.

Higher taxes mean less capital, reduced investment, diminished ownership and fewer economic benefits. Period.

At a time when we need more capital to own a meaningful piece of the IP-based economy, our country is going backward. As the economy increasingly shifts toward intangible assets, we will be left behind with digital bread crumbs, selling our next generation short.