One of the things I’ve learned from building software over the years—at startups, banks, GitHub—is that the faster you move, the more important it is to understand the fundamentals. So last year, I paused. And went back to study Computer Science as a Master’s.
Not to get a job. I already had those.
Not to “start over.” I never stopped building.
But to solidify what I knew, fill in the cracks, and get back into something I’d missed for a while: research.
I got in and got a distinction which wasn’t my goal but it felt good anyway.
The Project That Lit the Fire
My Master’s thesis was on Explainable AI (XAI). I dove deep into how machine learning systems can be made interpretable, especially when deployed in high-stakes environments.
It was academic work, sure—but it felt unusually timely because AI today is no longer a lab toy. It’s infrastructure. And if we can’t explain how these systems make decisions, we can’t trust them at scale. That’s not just a research problem. It’s a product problem. A leadership problem. A civilization-scale problem.
And I knew: I wanted back in.
AI x Me = 10x Builder
Since graduating, I’ve been stunned at how quickly AI is changing my own work. What used to take 2 hours of boilerplate now takes 10 minutes. Code reviews feel like pair programming. UI concepts become live components before coffee’s even cold.
It’s not about AI replacing me. It’s about removing friction, so I can focus on the parts that matter—product decisions, architecture, interface, experience.
This has made me even more certain about what’s next: leading my own product. I’m still as entrepreneurial as ever. But now I’m equipped with a sharper lens—one grounded in both systems thinking and real-world velocity.
What’s Next
In the wraps. I will speak on it soon.