I build and study systems for better judgment under uncertainty — across AI, autonomy, product strategy, human cognition, and scientific evidence. What ties the work together is one question: how do people and machines decide what to trust, what to measure, and what to do next? I'm drawn to the places where someone is running on a bad model of reality, and I try to build, test, or explain a better one.
That instinct is why this site exists. I started it after reading yet another news article that misunderstood and misrepresented a scientific study — a small, everyday failure of judgment dressed up as reporting and optimized for web traffic. Writing became the way I work these problems out: how to read evidence, how to weigh tradeoffs, how to tell a real signal from a flattering one.
The same question follows me away from the keyboard. I like to go in circles — there is something clarifying about endless laps on a running track or a race track, anywhere from 15 km/h to 150, where stray thoughts get drowned out in a flow state. Then I get to analyze the data endlessly afterwards, which I also did as a day job for many years: turning messy, high-stakes situations into something measurable.
The racing was no accident either. When I turned 25 I bought a sports car and took it to a track, where I met some awesome people with the same obsession. Things escalated. We ended up running a race team for a few years, before I moved to the UK, where I reside now. Autonomy, evaluation, decisions made under pressure — I'd been circling the same questions for years before I thought to connect them.