Design Patterns for Startup Engineering
Four frameworks for building products that survive contact with reality
After spending the past year validating and building a dozen product ideas, I've distilled what actually matters into four interconnected frameworks. Each addresses a different phase of the journey from concept to scale.
Stack 01
The Validation Stack
Product Ideation & Validation
How to identify problems worth solving, validate demand before building, and design experiments that give you real signal in weeks, not months.
Coming SoonStack 02
The Neural Stack
Data & Indexing
The unsexy infrastructure that determines whether your AI product is magical or mediocre. Embeddings, retrieval, knowledge graphs, and the art of semantic search.
Coming SoonStack 03
The Engineering Stack
AI Development
Prompt engineering that scales, evaluation frameworks that catch regressions, and deployment patterns for systems where "it works on my machine" means nothing.
Coming SoonStack 04
The GTM Stack
Sales & Marketing
Distribution strategies for AI products, pricing models that capture value, and the counterintuitive truth about selling technology that feels like magic.
Coming Soon