Most AI never ships.

And almost never because of the technology. The models work. What breaks is everything around them: a clear spec, honest testing, and the judgment to know what to ship and what to leave alone. That is where I work. I build AI that actually reaches production and takes real cost out of the work, whether it faces your customers or runs inside your team.

Spec-driven, not vibe coding.

I start with a precise spec, build it with AI tooling like Claude Code, and test each version against real cases before it ships. The result is production software that holds up in the real world, not a demo that looks good once and falls apart the first time someone relies on it.

The hard part is judgment: knowing where it is safe to move fast, where it has to be exact before anything ships, and when to bring in a dedicated technical owner. That judgment is what keeps a project out of the majority that never make it to production.

A new kind of builder.

I ship production software without hand writing most of the code. I do it with systems thinking, AI orchestration, and constant testing. That is where the work is heading, and it is how everything here was built.

Before this was a category, I trained the data behind today's frontier AI models. At Pareto.ai I mentored prompt engineering and ranked in the top 0.1 percent across more than 2,000 contributors. I know how these systems are built, so I know where they break.

Open to the right hard problem.

I am looking to bring this operating capability inside one team solving frontier problems. Open to AI deployment, implementation, and solutions advisory at AI-native companies. Regulated or high-stakes environments welcome. Remote primary, Tucson hybrid is fine.

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