Thinking on product truth, behavior specs, and building software teams can reason about.
Subscribe via RSSAs engineers take on more product ownership and AI accelerates shipping, product decisions vanish into Slack and PRs. Behavior specs hold the intent.
AI makes rebuilding cheap. But product decisions are expensive to recreate from memory. Here's how a behavior spec makes 'start fresh' a feature, not a failure.
Paste a prompt into Claude or ChatGPT, describe your product module briefly, and get a .pbc.md behavior spec you can view, edit, and commit to your repo.
CLAUDE.md and AGENTS.md tell agents how to work in your repo. They don't tell agents what your product promises. That's a different artifact — the PBC layer.
A step-by-step guide to writing a .pbc.md file for your product's most critical module. Start with plain Markdown; add structured blocks agents can read.
Shipping fast with AI agents feels productive. But the costliest mistake isn't bad code — it's building confidently when nobody wrote down what was decided.
PRDs capture intent. Tests verify assertions. Between them, there's no artifact tracking what the product promises — grounded in code, confirmed by humans.
AI agents have AGENTS.md, memory banks, harnesses, and monitors. They still lack the product context layer — what the product promises and what must hold.
When an outsourcing engagement wraps up, product knowledge walks out the door. A living behavior spec keeps it in the codebase — not in someone's head.
AI can extract product logic from your codebase. Stewie builds a living behavior spec your whole team can read — no code, no docs, no waiting on engineers.
