Production AI engineer and consultant.

I've spent most of my career building software under real constraints: deadlines, regulated environments, production incidents, team growth, and the usual mismatch between how systems are supposed to work and how they actually behave. Earlier on, at thoughtbot, I co-taught a cohort of the Metis Ruby on Rails bootcamp — a 12-week intensive that produced production-ready engineers — which is where I learned how to compress engineering intuition into something a builder can actually use.

I was CTO at Buoy Software, where I helped grow the engineering team from 0 to 50+ and shipped FDA-cleared medical device software (510(k) BK231004). My background also includes time as a Staff Engineer at Shopify. Today I consult with teams shipping production AI while keeping my hands in the work as a senior engineer at August Health, building August Intelligence — the AI platform for better care and operations in senior living communities — and teaching what I learn in public.

That combination matters. A lot of AI advice is either theoretically smart or practically battle-tested. I care about the second category. My AI-native engineering patterns, MCP servers, and skills are open-sourced on GitHub — including claude-code-workflows, my public collection of patterns built from daily use.

These days a lot of that work takes the shape of an agent-augmented Fractional CTO engagement: CTO-level architecture, technical direction, and shipped code, augmented by agents that extend what one person can deliver. The judgment stays human; the agents extend the reach.