Lifting weights got me in the gym. Nutrition is what kept me there — and made me care about understanding systems in a completely different way.
I started lifting seriously a few years ago. The first six months I made decent progress just by showing up consistently. Then I plateaued, and I started digging into why. That's when I fell into the nutrition rabbit hole and haven't fully climbed out.
What surprised me is how much of it is just systems thinking. Calories in, calories out is the simplest model — but then you start layering in protein synthesis, micronutrient timing, sleep quality, cortisol response, and suddenly you're managing something that has real feedback loops. It scratches the same itch as working on a data pipeline.
I'm not extreme about it. I don't track every gram of food or cut out entire food groups. But I do think carefully about what I eat and why. I've learned a lot about how different foods affect my energy levels, focus, and recovery — and that knowledge has genuinely made me feel better day to day.
The overlap between this and my interest in data is pretty direct. Everything is measurable if you want it to be. The question is always: what's worth measuring, and what's just noise? That's a question I ask in my code and in my kitchen.