A benchmark score is only useful if it drives a decision. The evaluation loop makes that explicit: state the claim, build an instrument that can falsify it, measure, diagnose the failure, change exactly one thing, and re-measure under the identical protocol.
Attach every score to a decision
Ship, fix, or investigate. If no action follows from a metric, you have built a dashboard — not an evaluation.
Change one variable
Model, prompt, decoding, and data all move the score. Change one at a time or the result is unattributable.
Freeze the protocol
Prompt format, few-shot count, sampling temperature, and the item set are part of the measurement. Changing any of them invalidates the comparison.
MATHEMATICAL FORMULATION · SIGNAL VS NOISE
Δ_observed = Δ_true + ε_protocol + ε_sampling
An observed improvement mixes the true change with protocol drift and sampling noise. A 1-point gain on 200 items has a 95% half-width of ±6.3 points — larger than the effect it claims to show.
REAL-WORLD PRODUCTION ENGINEERING
Eval-driven teams keep a small 'north star' suite stable for months so year-over-year comparisons remain valid.
Releases are blocked on regressions in the north star, while exploratory suites iterate freely.