From long nights in cleanrooms to cutting checks: Albert Chen on building (and backing) deep tech in Canada

If you have ever looked at your classmates’ LinkedIn pages and thought, “Wait, how does everyone already have a five-year plan?” Chen is proof that real careers are usually built in the messy middle. Lots of curiosity, a bunch of experiments, and a surprising number of moments where you have no idea what you are doing until it suddenly clicks.

Chen is a Partner at Two Small Fish Ventures, a Toronto-based early-stage deep tech VC. We sat down with him to talk about what his firm looks for in founders, where AI is actually heading next, and why Canada’s deep tech scene is starting to feel way more interesting than people give it credit for.

What Two Small Fish does, and why “early stage deep tech” is not just a buzzword

Two Small Fish invests early, usually at pre seed and seed. Chen described their role as being one of the first institutional checks for founders, then sticking around as the company grows.

Their focus is on the frontier of computing and its applications. That sounds broad, but it is actually a really good umbrella for the kinds of companies they get excited about: frontier AI, domain-specific AI, robotics and physical AI, advanced computing hardware like chips and semiconductors, and smart energy.

Chen’s personal sweet spot leans more “physical.” Think robotics, sensors, semiconductors, and energy. The stuff where you cannot fake it with a landing page. It tends to take longer, it is harder to build, and when it works, it can be insanely defensible.

Chen’s path into VC was basically a highlight reel of curiosity

Chen studied Systems Design Engineering at the University of Waterloo, which is basically a built in permission slip to explore. He used the co-op program as an opportunity to bounce across disciplines like finance, mechanical design, energy markets, startups, and research labs because he wanted to understand how wide engineering can really go.

After that, he did a PhD in MEMS (microelectromechanical systems), which is one of those fields that feels like engineering’s ultimate crossover episode. Mechanical, electrical, and software all meeting in the same tiny place. From there, he worked across things like optics, robotics, sensing, and energy.

For a long time, he worried that being a generalist was a weakness.

Then VC happened.

He told us that a venture is basically a full-time “learn something new right now” job. Every day you are looking at a totally different technology, market, or product, and your job is to ramp up fast enough to ask the right questions. For someone who likes variety and deep dives, it is a pretty perfect fit.

His move into Two Small Fish also happened in a very human way, not a “career ladder” way. He was talking about startups with a former classmate, advising, consulting, and spending time around founders. After going through fundraising from the technical side, he kept thinking about how often deep tech founders are stuck explaining complex work to investors who cannot really meet them where they are.

At a certain point, he basically got asked: if you think it can be better, do you want to help make it better?

He said yes.

What they look for early, before anything looks “obvious.”

At pre-seed and seed, nobody has perfect traction charts. So what does a deep tech VC actually look for?

Chen kept coming back to two signals.

1) Builders who love building and build well
Not “perfect founders.” Builders. People who move quickly, make smart tradeoffs, and keep shipping without duct taping the whole product together. Chen said the passion should be palpable. You should be able to feel that the team is obsessed with making the thing real.

2) Ambition beyond a “hot dog stand.”

One of his best filters, a phrase he credits to his partner Eva, is simple: you do not want to be a hot dog stand. He is not insulting small businesses. He is describing venture scale. VC is built around the idea that a few companies become truly massive. So the teams they back need a vision that can grow into something huge, even if the first version looks small. Early on, it is less about having everything nailed and more about having a direction that is worth running at for years.

A founder trap that shows up everywhere

Chen dropped a line we immediately wanted to tape above every startup desk.

Founders often fall in love with the problem, but then accidentally fall in love with the first solution they build.

The better move is to stay loyal to the problem and stay flexible about the solution. Your first product is usually not the final product. It is the start of the learning loop. The faster you learn, the faster you get to the real wedge that makes your company hard to copy.

AI is crowded, but the next wave is getting way more real

We had to ask him about AI, because it is everywhere right now.

Chen was very honest: oversaturation is real. He sees it across software and even across robotics. A lot of products can get you to the first 80 percent, and then everyone gets stuck on the last 20 percent. That last 20 percent is usually where the real differentiation lives, and it is very rarely solved by large language models alone.

What is exciting is where things are going next: edge AI.

Edge AI matters because people do not live inside a browser tab all day. Real world AI has to run on devices like phones, wearables, robots, and embedded hardware. Cloud compute is expensive, power hungry, and introduces latency. If something needs to respond in real time, it cannot always wait for a server across the internet.

So now the hard and interesting problems show up. How do you make models smaller without making them useless? How do you run them efficiently with limited memory and power? How do you design experiences that actually work in the real world? This is where deep tech starts to feel like deep tech again.

Canada’s deep tech moment, and the flywheel Chen is betting on

Chen is optimistic about Canadian venture over the next decade, and his reasoning is simple: he expects more technical people to become investors.

Deep tech needs “smart money.” Investors who can understand technical risk, support ambitious roadmaps, and stay patient when timelines are longer. As more engineers and technical builders move into investing, Chen thinks Canada will get better at backing the kinds of companies it is already capable of producing.

He described it as a flywheel. More smart money leads to more deep tech investment, which leads to more great companies, which leads to more strong roles and better compensation, which helps keep talent here, which leads to even more companies getting built.

He also pointed out something that does not get enough airtime: quality of life matters. Safety, stability, and the kind of society you want to live in long term all shape where people choose to build their careers, not just salary numbers.

Chen’s student playbook for getting into deep tech

His advice was practical, and honestly kind of energizing.

Build things early and often. With modern tools, he believes there are fewer excuses to not build. Go to hackathons, even if you are just there to watch how teams move. Join a strong research lab to see what deep technology actually looks like up close. Try enough roles that you learn what you are bad at, because that is not failure, it is signal.

He also believes startups are one of the fastest learning environments you can find. You get responsibility, exposure, and feedback loops that are hard to match in bigger companies.

The moment that shaped him most: cleanroom tears, then a breakthrough

One of the most memorable parts of our conversation was Chen describing his proudest moment.

During his PhD, he spent months stuck on semiconductor packaging work that kept failing. It got so bad that he ended up crying in a cleanroom. Then, late one night, he found a new technique that fixed the process, and it later became something others used too.

The takeaway is not “be a genius.” It is what repeated failure does to you as a builder.

Once you have pushed through that kind of wall, you do not flinch as easily. And that calm matters when you are leading through uncertainty, because deep tech and startups are basically uncertainty with a to do list.

Closing thoughts

At the end of our interview, Chen told us he is aligned with The Maple Draft’s mission, and he is excited about supporting more builders across the Canadian engineering ecosystem.

If you are a student reading this and feeling pressure to pick the perfect path, we will say it the same way we heard it throughout this conversation: lean into building. Try things. Learn fast. Your path can look chaotic up close and still turn into something that makes perfect sense later.