I'm Evan Stachowiak, and I build things. I grew up between two worlds: a mother with a doctorate in nursing education and a father who ran manufacturing companies. One side gave me a deep respect for understanding how things actually work; the other gave me an early, hands-on feel for how a business runs on the floor. My childhood was split between the suburbs and a horse rescue in Wisconsin, which mostly meant manual labor and weekends building and fixing things next to my dad.

One of those projects was a horse shelter. We built it by measuring the old one, working out every material and how the pieces fit, and turning that into a plan we could actually execute. That loop, understand the inputs, understand how it works, then build it, has never left me. A few years later, at 13, I watched my dad run gutters in a way that made no sense to me, suggested a cleaner method, and it worked. That was when I realized I had a knack for seeing how things should work, as long as I understood why they work first.

That curiosity runs through everything, not just code. I started college on a vocal performance scholarship, which is where I learned to drill a hard skill until it becomes automatic, before the build instinct won and I moved into tech. I learn the same way regardless of the subject: break it down to fundamentals, build a working understanding from the bottom up, then get hands on and learn the rest by making mistakes fast. It is how I taught myself to ski and snowboard in a day each and ended up instructing, and how I taught myself the stack for my EV Trainer and shipped it in under a week.

My edge is where that curiosity meets discipline. I came up through quality and operations work in manufacturing, which made me genuinely analytical and critical about how things get built. Pair that with a real passion for statistics, the kind that has me thinking in expected value at the poker table as readily as in my work, and my information-management coursework, and you get what I actually do well: build with AI and keep it reliable. As a data science intern I put that to work right away, catching several errors in a costing model in my first week and automating documentation that would have cost a small team a week of manual effort.