About
I’ve spent twenty years building systems that help people and organizations make better decisions with the information they have. The thread running through my career isn’t a job title. It’s a question: how do you get the right information to the right person at the moment they need to decide?
That question has taken me from targeted political campaigns across the country to building enterprise AI platforms, and it’s led me to what I work on now: the architecture of context in AI systems — the five-step process (curate, synthesize, consolidate, prioritize, store) that most AI products skip entirely.
But I didn’t arrive here through AI. I arrived here through behavioral economics, information architecture, growing up around community organizers and educators, reading Western literature in elementary school, and a lot of building.
The quick version.
How do you turn raw information into something a person — or a system — can use to make a good decision?
From politics to digital strategy to product management to AI context architecture. Each step was about the same problem. AI has made the architecture of context a product problem, not just an academic one. And product problems are what I solve.
Brooklyn, with family.
I live in Brooklyn with my wife and two young children. When I’m not building, I’m strength training, photographing street scenes, or reading sci-fi.
I speak about context, product, and AI.
Practitioner-focused: specific decisions, real trade-offs, frameworks the audience can apply Monday morning.
The Five Steps Most AI Systems Skip
Why most AI products treat data as context and what happens when you build the generation layer they’re missing. The five-step architecture grounded in cognitive science and demonstrated in production.
RAG Is Not Enough
RAG is a retrieval pattern, not a context strategy. What the next generation of AI products needs beyond chunking and embedding — and how to think about it differently.
From Zero to Revenue: AI Products Without Code
The practical guide to building production SaaS using AI coding tools. Architecture decisions, costly mistakes, and workflows that actually scale.
The Product Leader’s Guide to AI Architecture
When to build vs. buy. How to evaluate context systems. Whether your product actually needs a context layer. A decision framework from someone who’s made these calls.