AI engineering, built with a designer's craft.

My work sits at the intersection of design and development. I studied at the Rhode Island School of Design (RISD), where I developed a deep appreciation for typography, visual systems, and the craftsmanship that comes from understanding materials — whether those materials are ink on paper or code on screens.

Over two decades, I've worked across the full spectrum of web production: designing interfaces, building component libraries, architecting full-stack applications, setting up deployment pipelines, and establishing the kind of technical foundations that let teams move fast without accumulating debt.

Today that foundation powers my work in AI. I've architected and shipped a portfolio of production AI systems: multi-agent pipelines where fifteen specialized Claude agents turn raw documents into cited, compliant reports; a live, monetized diagnostics SaaS with LLM-powered recommendations; a safety-first medical diagnosis platform routing across five specialist agents; and conversational tools that generate real CAD geometry from plain language. This is AI engineering as a production discipline — anti-hallucination sourcing, prompt caching and cost controls, circuit breakers, and honest fallbacks — not demos.

I care deeply about typography, accessibility, and performance — not as abstract ideals, but as practical disciplines that make real differences in how people experience the web. That same conviction shapes how I build with AI: the best intelligent products come from people who understand the design intent, the technical implementation, and the model behavior in between.

Currently, I'm focused on building AI-native products and working with select clients on projects where design quality, technical excellence, and long-term thinking are valued.