Over the past 27 years I've built products with companies of every size — scrappy startups to established enterprises — shipping things that actually scale. For the last few years that work has centered on AI: not the demo-ware kind, but systems that hold up in production and earn their place in a real business.
As an AI Product Engineer, I work backwards from what the product should be, then build it end to end — frontend, backend, infrastructure, and the AI layer woven through all of it. I'm at my best when handed a rough idea and asked to make it real. That means knowing where AI creates genuine leverage and, just as importantly, where it doesn't.
In practice, that shows up as AI automation — integrating AI into the parts of a business where it compounds: lead generation, internal tooling, content pipelines, and the workflows that quietly eat a team's time. My stack here includes Claude, ChatGPT, Cursor, Hermes, MCP servers, n8n, and LangChain, among others.
And as a Fractional CTO, I step into the technical leadership gap — working with founders and leadership teams to set engineering direction, make the architectural calls, and build the systems and teams that let a company scale without a full-time hire. Defining your stack, leading a migration, hiring your first engineers, or translating business goals into technical reality: the same hands-on approach, one level up.
On the technical side: JavaScript across the board (Astro, React, Datastar, Remix, Next.js, Vue, Nuxt), plus PHP, Rust, Go, and Python — with deep experience in headless architecture (Directus, Strapi, Sanity, WordPress, Shopify) and infrastructure from greenfield to legacy migration.