Build AI Governance Into Your Solo Dev Stack: A Practical Workshop

What We Are Building By the end of this workshop, you will have a working AI governance layer you can drop into any project shipping AI features. No compliance team required. No enterprise tooling. Just four patterns that will save you from a painful rewrite the moment a regulated customer shows up. Let me show you a pattern I use in every project — and it starts before your first AI inference ever reaches a user. Prerequisites A project making API calls to any LLM (OpenAI, Anthropic, etc.) A PostgreSQL database (or any append-only store) Basic familiarity with YAML and structured logging About 15-20% more patience during your initial build (it pays back 4-8x) Step 1: Decision Logging as Infrastructure Every AI call your app makes should produce a structured record before the response hits the user. This is not console.log . This is an immutable audit trail. Here is the minimal setup to get this working: CREATE TABLE ai_decisions ( decision_id TEXT PRIMARY KEY , model TEXT NOT NULL , i