A curated set of (input, expected output) pairs that must pass before any prompt or model change is deployed.

A curated set of (input, expected output) pairs that must pass before any prompt or model change is deployed. Store in version-controlled eval dataset. Run on every PR via CI/CD. Flag any drop in pass rate > threshold. Include: happy path examples, previously-failed edge cases, adversarial inputs. Set temperature=0 for eval, or use LLM-judge with a tolerance threshold for non-deterministic outputs.