John Wu

I can't leave a black box closed. My free time goes to trying new technologies, falling into YouTube rabbit holes about business, economics, and history, or listening to podcasts at slightly unreasonable speeds. I just genuinely want to know how things work.

That habit is what keeps me ahead of the curve at work. I still build things myself on nights and weekends, so my product instincts come from having my hands in it, not just from reading about it.

I try to see the world from where other people are standing: my family and closest friends, someone I met five minutes ago, the engineer across the table, and most of all the customer. Very rarely can I ever dislike someone, because I'm always looking at things from their perspective.

That takes patience. It means asking one more question and sitting with someone's frustration a little longer before jumping to a solution. The best product decisions I've made came from that patience, because they solved the problem people actually had instead of the one I assumed they had.

I've been in the AI space for a decade, since back when getting a model to tell a cat from a dog was considered groundbreaking. I learned the fundamentals from the ground up — the math, the models, the mistakes — and I've had a front-row seat to the field ever since: from linear regression to basic neural networks, all the way to modern LLMs.

That depth goes with me into every product conversation. I've spent years focused exclusively in the AI space, so I can go deep with researchers and engineers and still translate it into what matters for customers and the business.

I was born in Carbonear, Newfoundland, a town of about 4,000 people on Canada's Atlantic coast, where my parents first settled after immigrating from China. We were the token Asian family in town, and for a few years I even had the Newfie accent to prove it.

I grew up in Surrey, BC, and like most Canadians I'm apologetically nice, friendly, and generally pretty chill. But growing up in a lower-class immigrant family taught me something the laid-back exterior doesn't show: how to work hard, with real intensity. My parents sacrificed everything so I'd have opportunities they never did, and I don't take that lightly.

I spent most of those years on a court or a field: basketball first, plus volleyball, rugby, wrestling, and track. That's where I first learned to apply the intensity and discipline that would later be useful in my education and career.

I studied Computer Engineering at McGill from 2014 to 2019, the first time I lived away from home. It's where I first dabbled in AI, and where I got hooked.

I also co-ran McGill's AI Society, building a 12-week ML bootcamp and the university's first AI hackathon, and won the McGill Engineering Competition twice.

My first internship took me to Ottawa, where I built airline maintenance software at IFS Technologies. My second internship took me to Tokyo, where I built computer vision at a startup called Flicfit. In between the internships, I also got hooked on hackathons (attended 17 hackathons and counting).

I moved to Seattle in 2019, straight out of McGill, for a product job at Microsoft. The plan was simple: stay two years, then head back home to Canada.

I'm still here. The opportunities never stopped coming, and the next interesting problem is always one conversation away. I now have a green card, a house, a dog, and a career I couldn't have built anywhere else.

I protect one to two hours of exercise every day: cardio, weightlifting, or a pickup game. And to make sure I actually have a social life, you'll usually find me at a Seattle craft brewery with friends, hazy IPA in hand.