An open-source checklist (MIT) for testing AI and LLM features before customers do. Five steps: define "good" as a number with an eval set, write a "never" list held to zero failures, run the evals in CI on every prompt and model change, put a budget on cost per request, and watch production with a rollback switch. Includes an example eval-cases.yaml you can copy and start with ten cases.