Eval Harness

An eval harness is an automated test suite for model outputs — the machine-learning equivalent of unit tests. It pairs a fixed dataset of inputs with scoring logic: exact-match checks, regex or schema validation, rubric grading, or an LLM-as-judge that rates each response. Run the harness on every prompt tweak, model upgrade, or fine-tune, and you get a comparable score instead of a gut feeling. For SaaS builders shipping AI features this is the difference between confident iteration and praying nothing broke. Without a harness you eyeball five examples, ship, and discover the regression from an angry customer. With one, a prompt change that quietly worsens 12% of cases shows up as a red number in CI. Tools include promptfoo, OpenAI Evals, LangSmith, and Braintrust. Practical note: start small with twenty to fifty real cases you actually care about, mix cheap deterministic checks with a few judge-based scores, and grow the set every time a bug escapes to production.