Stop Supplying. Start Owning.

Canada has a paradox that I have been talking about for a long time.

We are home to most of the world’s AI godfathers. We have Nobel Prize winners, world-class researchers, and some of the most respected engineering schools on the planet. Those institutions attract exceptional students from around the world. And in turn, Canada trains some of the best engineering talent anywhere.

Yet an increasing number of those graduates — now approaching 80% — leave after convocation.

With them go the startups they might have built, the economic value they might have created, and the wealth that could have stayed here. We all know the largest and most valuable companies are technology companies, and they are based in the United States. Many of them were co-founded or led by Canadians.

It is a story of could have been, would have been, and should have been.

I was recently invited to speak at the Deans of Engineering Conference in Winnipeg. I want to share the core of what I said, because I think this conversation matters well beyond that room.

The root cause is not what most people think

The easy explanations are talent, capital, and policy. We hear them constantly. They are not wrong, but they are not the root cause.

The root cause is a mindset.

Clearly, we do not have a shortage of ambition or ability. One fundamental issue stands out — yet very few people talk about it, let alone address it. We have collectively learned to think like suppliers, not owners.

Without the owner mindset, we unintentionally and subconsciously optimize for producing great talent for other countries, rather than building a stake in where that talent goes and what it creates.

This is the supplier mindset made visible.

Let me illustrate with a banana

I use a banana analogy in my talks because it makes the concept concrete.

If you put money and a banana in front of a monkey, the monkey takes the banana. It does not know that money can buy many bananas. That insight comes from Jack Ma, who used this analogy to compare the mindset of someone who grabs a job versus someone who builds a company.

Jobs are bananas. They are real, they matter, and they feed people. A banana feeds you once. Cash feeds you many times.

But the lessons go further.

A banana tree is better than a banana because it can feed you forever. Ownership compounds; wages do not. A banana farm is better than a tree — because participation as a supplier is not enough; ownership of the platform is the real prize. And a store is better than a farm, because the store owns the customer relationship and captures the value that flows through the entire chain.

This is the progression from employee thinking to owner thinking. From banana to store. From grabbing to owning.

Canada has been grabbing bananas

Let me make this concrete with two examples — one personal, one national.

The Wattpad calculation. When Wattpad was acquired for US$660 million, the headline was a Canadian success story. And in many ways, it was. But here is the number nobody talks about. By the time of the acquisition, roughly half of the company was owned by Canadians. When the deal closed, about US$330 million in economic value left the country — because we had raised capital from outside Canada to build it.

Wattpad’s annual payroll was roughly US$30 million. Not small. But compared to the acquisition price, it is a fraction. Ownership creates far more value than employment. Jobs matter. Entrepreneurship matters. But nothing compares to owning world-class companies.

The auto industry analogy. Many people say Canada has a strong auto industry. We do not. We have a strong auto supplier industry. That is not the same thing. Our auto suppliers — collectively — are worth a fraction of GM, Ford, or Toyota. They build the factories, employ the workers, and take on the operational risk. When the EV transition stalled, the suppliers’ brand new facilities went quiet. When the majors slowed production, the layoffs rippled through.

The supplier bears the downside. The owner captures the upside and sets the rules.

And when the Canadian government went to attract EV investment, what did we do? We signed deals to become suppliers again — subsidized by Canadian taxpayers, while the ownership, brand, and margin stayed elsewhere. We took the risk but not the profit.

This is the supplier mindset at a national scale.

The question nobody asks clearly enough

Here is the hinge question: what does winning actually look like?

The supplier mindset and the owner mindset do not just lead to different outcomes. They lead to completely different definitions of winning.

If you are a supplier, sending your best researchers to OpenAI is a win. You produced world-class talent. Mission accomplished. That belongs in the annual report.

If you are an owner, that is a loss. You invested in that person for years, and you ended up owning nothing. The outcome looks identical from the outside — a brilliant Canadian thriving on the world stage — but the two mindsets score it completely differently.

Until we agree on what winning actually means, we will keep celebrating losses as victories.

Where the mindset gets formed

Here is what I have come to believe: the supplier mindset is not learned on the job. It is learned in school.

The mental model a student builds about what success looks like — a FAANG job offer, a US grad school acceptance, a signing bonus from a company they can brag about — is set before they ever enter the workforce.

In the US, building a unicorn startup is Plan A. Getting a job at Google is Plan B. In Canada, getting a job at Google — or going to the US — is Plan A. Building a startup, let alone a unicorn, is often not even in the equation.

That quote is from a world-class Canadian AI scientist who is now at a US company. It landed hard when I first heard it, because it is accurate.

The deans are the front line

I said something direct to the room in Winnipeg that I want to say here too.

The founders of most of Canada’s future tech giants are sitting in engineering classrooms right now. The deans who lead those schools are the single most underleveraged force in Canada’s innovation economy.

Here is why this is also in the deans’ own interest. If their students build world-class companies and keep them here, those companies will forever be associated with that school. That is a legacy that compounds for decades. The next crop of students is inspired by the tech giants that exist. Right now, leading universities outside of Canada are winning that recruitment battle — not because their engineering programs are better, but because the companies their graduates built are more visible, more celebrated, and more aspirational.

Think about OpenAI. It was co-founded by a University of Toronto alumnus. Most people associate it with Silicon Valley.

That association is not fixed. It is a choice, made one graduating class at a time.

This is not only about encouraging entrepreneurship

I want to be precise here, because there is a version of this argument that deans hear all the time and that I think misses the point.

Many engineering schools already encourage entrepreneurship. Hackathons. Incubators. Pitch competitions. These are necessary. But they do not define what success looks like. And in a strange way, encouraging entrepreneurship is still a supplier mindset — we are producing entrepreneurs for the ecosystem and hoping something sticks.

The real call to action is different. It is to start and scale world-class companies here in Canada.

That is a higher bar. A different ambition. A fundamentally different culture to build. It means celebrating the founder who builds a billion-dollar Canadian company with the same institutional pride as the researcher who wins a Nobel Prize. It means changing what the school defines as a win — not only placements, publications, and patents, but also companies that stay, scale, and own their category.

The window is now

I have saved the most important point for last.

We lost Game 1. Canada invented modern AI. The most important AI companies are almost all based in the US. That window has closed.

But Game 2 is underway. Quantum computing. Robotics. Physical AI. Space. Advanced manufacturing. Smart energy. Just to name a few. Canada has deep roots in all of these — world-class labs, exceptional researchers, and early-stage companies that are genuinely competitive.

Here is what is different about Game 2: you cannot pack up a quantum computing facility or a robotics lab and move it to San Francisco. Unlike software, the physical infrastructure is sticky. The talent clusters around it. The companies that emerge will be rooted where the labs are.

And the ground-level signal I am seeing is genuinely encouraging. I have never met more professors and researchers who want to start companies — and who want to do it in Canada. That is new. That is meaningful.

The conditions are finally aligned to address the root problem, not just the symptoms. But the only trophy that ultimately matters is homegrown, world-class companies. And we can only win Game 2 — and ultimately the championship — if we build the owner mindset now, starting with the people who shape how the next generation of engineers think about what success looks like.

Addressing the supplier mindset and turning it into an owner mindset can create the domino effect that turns Canada’s bragging rights into lasting economic wins.

That is the game we can win.

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!

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.

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!

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 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!

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.