Defined term
Evaluation harness
A test framework that scores model or prompt output against a labelled set of expected outputs.
An evaluation harness runs candidate models or prompts against a curated set of real examples with known correct answers (or human-rated answers) and reports accuracy, recall, format compliance, latency, and cost. The harness is the production gate: nothing reaches production traffic without passing a defined threshold. Without an eval harness, AI workflows degrade silently when prompts, models, or data shift.
When it matters
When you cannot afford to ship a prompt change blind. Required for any AI workflow that touches money, customers, or compliance. Optional but valuable for internal-only tooling.
Real example
A claims-extraction harness that scores 500 labelled cases on accuracy, hallucination rate, and policy-citation precision before any prompt promotes to production. Runs in under 4 minutes, blocks promotion below 92% accuracy.
KPIs to watch
Test set size (>200 cases minimum), eval pass rate gate (typical: 90-95%), eval runtime (<10 min for daily use).
Related terms
Labelled test set
A frozen, hand-curated set of real input examples with expected outputs, used to score model behavior.
Prompt versioning
Treating prompts as code: stored, diffed, reviewed, and rolled back like any production artifact.
AI governance
Policies, processes, and controls that make an AI system auditable and accountable.
Confidence score
A scalar that estimates how reliable a model's output is for a given input.
See it in action
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