Practical books for the founder who shipped first and asked questions later. Two are out now with free chapters. The other two are being written in public as blog series you can read today.
A practical guide to data architecture for small teams
You added AI features and got told you need a vector database, a graph database, and three new systems to run them. You don't. Start with one relational database, add pgvector, and stay on the short path.
The founder's guide to deploying AI-coded apps
No DevOps background required. A simple, repeatable workflow that gets your AI-coded app from a Replit prototype to real users on AWS, without the Kubernetes detour.
A field guide to AI security for founders and builders
Prompt injection, leaked credentials, rogue automations, and model drift are product risks now. Practical controls that fit the speed a startup actually ships at.
Building and scaling startups with AI in the loop
AI compresses the work of building a startup. It does not remove the work. How to use it across product, measurement, and growth while keeping the judgment human.