I got into AI because the problems never get boring.

I've worked across SaaS, energy, ecology, go-to-market. Different industries, different data, same conversation every time: the last AI project didn't land, and now they need someone who'll actually own it.

The gap between a demo and a system that actually runs is where most AI projects die. I build systems designed to get better. Feedback loops, clear metrics, and enough visibility that the team can keep improving it long after I'm gone.

The hard part isn't building it. It's picking the approach that still makes sense in six months. Models improve, tooling shifts, and best practice from last quarter is already outdated. I stay close to the edge so my clients don't have to.