Tablekeeper: AI-Built Restaurant Reservations

Tablekeeper is a restaurant reservation system with one hard rule: a table is never double-booked. It was built entirely by a "dark factory" of three AI coding agents sharing one BAND room, using Claude Code with the claude-sonnet-5 model. No human wrote any application code. The Planner reads the task and spec, writes a requirements checklist and assigns work items. The Implementer writes the code and tests, builds the Docker image, runs the official harness and posts evidence. The Reviewer writes no application code: it rebuilds the container and re-runs every check itself, attacking the service with replayed idempotency keys, double-booking attempts and daylight-saving changes, then accepts or rejects. Stage 1 is a JSON API for restaurants, tables, availability and reservations. Stage 2 adds a browser website (search by restaurant, date and party size, book, look up by reference code, cancel) and combinable tables for bigger parties. Both stages pass the official harness in isolated mode (stage 1: 120/120, stage 2: 25/25 shipped checks), our own suite of 282 tests passes, and each image starts in a fresh container with no network. The repository includes the agent mandates, FACTORY.md describing how the factory works and catches bad work, and the full BAND room export. We are honest about limits: no per-seat git history, no visual inspection of the site, and stages 3 and 4 were not attempted.