10 Commandments for Deep Tech Founders

After witnessing many scientists and engineers make the transition to CEOs or founders, including myself, I have noticed the following.

Successful transitions tend to do these 10 things well. Of course, they are not a guarantee of success. Nothing in startup-building is. But when the transition fails, it is almost always because one or more of these broke down.

The transition from scientist or engineer to entrepreneur is particularly interesting because many of the skills that made you successful in research remain incredibly valuable. But some of the instincts you developed along the way need to change.

You are moving from a world of proof and evidence to one of uncertainty. From building technology to building products and companies. From solving technical problems yourself to leading extraordinary people who can solve them with you.

I have summarized them and called them the 10 Commandments for Deep Tech Founders:

1. Deep tech operates on proof and evidence. Startups operate in uncertainty.

Scientists and engineers are trained to seek proof, evidence, and certainty before reaching conclusions. That is exactly what makes them great scientists and engineers.

But startups don’t give you that luxury.

Customers, markets, competitors, timing, and human behaviour cannot be proven in advance. You have to make consequential decisions with incomplete information and sometimes very little data.

That does not mean taking stupid risks. Understand the downside. Know your edge. Look for asymmetric upside. Then make the best decision you can with incomplete information, act before certainty arrives, and learn fast enough to change course when you are wrong.

2. Nobody else runs the company. You do.

Researchers love the word “propose.” You propose an approach, an experiment, or a next step. But when you are running a company, you don’t propose to yourself.

Seek mentors. Learn from people who have seen the movie before. Listen carefully to your board, investors, team, and others you trust. The board can challenge you, support you, and help you think. But the board does not run the company. You do.

Others can help you think through the decision. They cannot own it for you.

Make the call. Execute. Own the outcome.

3. In the spirit of fast iteration and outcome-driven execution, good enough is perfect.

In research, perfect is often not good enough. In a startup, good enough can produce a better outcome because it lets you move faster, learn earlier, and iterate more.

Company-building is a race against time and competitors. The window of opportunity is finite and usually small. Seize it. More iterations give you more shots on goal. More shots lead to more goals, more goals lead to more wins, and more wins give you a shot at the world championship.

This is not about lowering the bar. It is about being outcome-driven about where you set the bar. When perfection materially improves the outcome, pursue it. When good enough produces the better outcome, don’t let perfect be the enemy of good. Ship, learn, and iterate.

4. Master all three: technology, product, and commercialization.

Building technology is about creating what you love. Building a product is about creating something others love to use. Commercialization is about creating something people will pay for.

These are three very different things.

For technical founders, business skill is learnable. The bigger barriers are often a lack of desire and the tendency to avoid what feels unfamiliar or uncomfortable. Get past that discomfort and you can learn the business side.

The reverse is much harder. It is far more difficult for someone without the technical foundation to become world-class at the technology. And in deep tech, that technical depth is usually required to set the right vision and strategy.

That is an unusual advantage for technical founders, but only if you are willing to stretch beyond the invention.

Building a great tech company is a triathlon of technology, product, and commercialization. To win the world championship, the CEO needs to master all three.

5. Be unrecognizable every two years.

Your job keeps changing. First, you are building the technology. Then you are building the product. Eventually, you are building the company.

What worked with 3 people will not work with 10. What worked with 10 will not work with 30. What worked with 30 will break again at 100.

The company must keep reinventing itself, and so must you.

The most important product you are building is not the technology, the product, or even the company. It is you. If you are not almost unrecognizable from your former self every two years, you are not growing fast enough. Eventually, your fast-growing company will leave you behind.

6. A CEO has only three jobs.

Set the vision and strategy and communicate them clearly to all stakeholders. Recruit, hire, and retain the very best people. Make sure there is always enough cash in the bank.

No great company can be built without getting these three things right.

Of course, entrepreneurs end up doing a million other things. You don’t have to love everything, but you need enough curiosity to find the interesting angle in anything important to the company.

As the company scales, delegate everything you can. Do what only you can do, not what you think you can do better than everyone else. Otherwise, you become the bottleneck.

7. Startup-building is a team sport of both IQ and EQ.

Deep tech has no shortage of IQ. But building a great company takes much more than being the most intelligent person in the room.

EQ matters just as much, and in startup-building, a big part of EQ is street smarts.

You need judgment, empathy, communication, resourcefulness, and the ability to read people and situations. You need to know when to push, when to listen, when to change course, and how to bring people along with you.

As the company grows, your job becomes less about having all the answers and more about building a team that can find the answers together.

IQ can help you invent the technology. IQ plus EQ helps you build the company.

8. Surround yourself with extraordinary people, and keep raising the bar.

The gap between good and great is huge. The gap between great and extraordinary is equally huge.

Extraordinary people are rare, but they exist. Once you have worked with truly extraordinary people, you cannot unsee what extraordinary looks like. They operate at a completely different level. More importantly, much of what makes them extraordinary is learnable and achievable. Extraordinary people reset your understanding of what is possible.

Always hire the very best people you can afford, then keep raising the bar. A players want to work with A+ players because they want to be challenged and surrounded by people they can learn from. B players often hire C players because they are insecure and don’t want to be outshone. C players then hire D players.

Before you know it, your company is littered with X, Y, and Z players, and the decline becomes extremely difficult to reverse.

Talent compounds. Unfortunately, mediocrity compounds too.

9. Culture is how you attract extraordinary people and why they stay.

Great people have choices. Compensation and titles can get their attention, but they are not enough to keep the very best people.

Culture determines not only what decisions get made, but how they get made. The “what” drives the business. The “how” determines what it feels like to build that business together every day.

This matters even more in deep tech, where the specialized talent you need can be incredibly scarce.

Culture is how you attract extraordinary people, align them, and give them a reason to stay.

10. Be the phoenix. Keep rising, and keep flying.

Building a great company is not a sprint. It is not even a marathon. It can easily take a decade or more. That requires total commitment for the long term.

Setbacks are not occasional events in startup-building. They happen all the time. Somewhere along the journey, most great companies will face existential threats, often more than once.

Don’t let a crisis go to waste. Learn from it. Adapt. Rise from the ashes stronger than before. Then keep flying, because another setback will eventually come.

Be the phoenix. Rise every time you fall, fly higher every time you rise, and keep flying for the long term.

The transition

None of these commandments guarantees success. Startups don’t work that way.

But I have seen enough scientist-to-entrepreneur transitions, including my own, to believe that getting these things wrong can dramatically reduce your odds.

The technology may be where the company starts, but eventually you have to build the product, the business, the team, the culture, and ultimately the company.

And somewhere along that journey, you have to build a very different version of yourself.

This post is the short version of each commandment. Over time, I plan to expand each of the 10 into an individual post, with more context, examples, and lessons learned from building, investing in, and working with deep-tech companies.

As each individual post is published, I will add the link to it here.

Consider this the table of contents.

EE Has Always Been Cool

A few weeks ago, we hosted our Legends of Semiconductor dinner, bringing together some of the people who helped build Canada’s semiconductor industry and the next generation of founders and engineers.

One of the legends was Professor Emeritus Adel Sedra, former Dean of Engineering at the University of Waterloo. For many electrical engineering students, Sedra needs no introduction. Microelectronic Circuits, the textbook he co-authored with the late Kenneth Smith, has shaped generations of electrical engineers and, by some estimates, has been used by 75% of electrical engineering students around the world.

At the dinner, the conversation turned to the textbook and which edition each of us had used. Mine was the second edition.

There was only one problem: I had lost my copy.

I was privileged not only to learn from Sedra’s textbook, but also to be one of the students in his classroom when he was a professor of electrical engineering at the University of Toronto. That second edition was the textbook I used as his student more than 30 years ago.

I suspect I lost it during one of our moves. I looked again after the dinner, but couldn’t find it. So I did the next best thing. I found a used copy of the second edition. Same edition, probably similar age, definitely not my copy. I bought it anyway.

This time, I wanted Professor Sedra to autograph it. So I brought the book to Waterloo, where Sedra was meeting with EE students at Williams Cafe. I crashed the party and hijacked their meeting for a few minutes to get my textbook signed.

While I was there, I started chatting with the students and sharing some of my experience as an electrical engineer. One student asked whether I thought EE was getting the spotlight again, after software had taken centre stage for the past couple of decades.

I told them EE is cool again!

Think about what is happening with AI. Everyone talks about the models. But underneath them are GPUs, memory, networking, semiconductors and an enormous amount of computing hardware. All of that hardware needs electricity. Lots of electricity. The entire AI stack, from the chips doing the computation to the power infrastructure keeping data centres running, is bringing electrical engineering back to centre stage.

Sedra immediately corrected me: “EE has always been cool!”

The whole table had a good laugh. And, of course, he was right.

The technologies may be different, but many of the fundamentals are the same. More importantly, so is the way of thinking.

I may never find my original textbook, but I now have the same second edition on my bookshelf again.

This time, signed by my professor!

The Underwater FishCam Livestream That Brought Our Family Together

Two weeks ago, I shared a short note about a fun side project I could only work on at the cottage.

I can now pull back the curtain: it is my underwater livestreaming FishCam. At first glance, it sounds simple: put an underwater camera in the lake and livestream it to YouTube.

Well, not quite.

I deliberately designed the system with a constraint. Instead of putting a powerful computer beside the camera, I chose a tiny, low-powered computer at the cottage to do the minimum, while my “data centre”—an old iMac at my Toronto home—does the heavy lifting.

Why?

For those of us who spend most of our time building in the cloud, abundant compute, memory, bandwidth, and reliable networking are easy to take for granted. Constraints are a forcing function. Running a live HD video stream on a resource-constrained edge device forced me to rethink almost every design decision.

Building at the edge presents a different set of technical challenges.
Who would have thought that streaming HD video could overwhelm the Raspberry Pi’s Wi-Fi subsystem and crash it? Those crashes then corrupted the microSD card, causing even more crashes.

Or that keeping a Raspberry Pi consuming roughly two watts—less power than many LED light bulbs—streaming smoothly would require tuning memory, processing power, and bandwidth?

Given those constraints, today is the first day the entire system has run for more than 24 hours without crashing. I’ll write a separate post about these technical challenges, all relevant to my professional world. As the world moves toward Physical AI, these constraints are important. We cannot assume abundant compute, high-speed networks, low latency, or unlimited power will always be available.

Imagine the vision system of an untethered robot operating at home, on a farm, underwater, or in space. The edge has very different constraints from the cloud.

Ironically, the biggest surprise was not technical. It was how much fun the project created for our family and friends.

The underwater camera has a built-in LED light that turns on after dark. It attracts mayfly nymphs and other small aquatic organisms, which in turn attract fish. Nighttime quickly became the most exciting time to watch.
One evening, some of us were at the cottage with friends, some were in Toronto, and some were travelling overseas. We all watched the same YouTube livestream together.

My mom, who turns 80 next year, and I held our phones up to the TV, waiting for a big fish to swim by.

When one appeared, we both burst with joy and shouted, “Wow, here is a big one!”

It felt like a modern version of fishing.

This is version 1.0. Fish detection, species identification, and other features are coming.


Sometimes the best way to understand where technology is going is to build something completely unnecessary.

More to come. Here is the live YouTube stream from the cottage.

P.S. Don’t forget to come back after dark. We have a party down there every night!