Thinking in Public
Essays, frameworks, and observations on context architecture, AI product strategy, and building what matters.
Data Is Not Context
The AI industry is obsessed with retrieval — how to get the right chunks into the context window. But retrieval is downstream. If what you're retrieving was never curated, synthesized, consolidated, prioritized, or stored intelligently, your RAG pipeline is just efficiently delivering noise. This essay defines the five-step architecture that turns raw data into decision-ready context.
8 min read
Building My Own Context Layer: Week 1
What happens when you try to build context architecture in the real world? This is what I learned in the first week of building my own implementation.
Your AI Has a Three-Phase Problem
Most AI systems fail not because they lack intelligence, but because they lack diagnosis. Why context collapse happens in three distinct phases and how to prevent each one.
What Expert Cardiologists Teach Us About AI Context
The diagnostic process that cardiologists use — pattern recognition, differential diagnosis, synthesis — is exactly what we should be engineering into AI memory systems.
How I Grew Grandstage 300% at $0 CAC
Product-led growth isn't just a tactic. It's a framework for understanding how products compound through quality, trust, and network effects. Here's what I learned.
The Product Leader's Framework for AI Architecture Decisions
Not all AI architecture decisions are created equal. A framework for evaluating tradeoffs between latency, cost, accuracy, and maintainability when designing AI features.
The Interview Where the Hiring Manager Watched CNN
A story about attention, context, and what it means to actually listen. Why the best interviews are the ones where the interviewer fully shows up.
The Context Layer
A newsletter on the architecture behind AI memory, context synthesis, and building products that think. Launching Q3 2026.
Want to discuss these ideas?
Get in touch →