Golden dataset
A golden dataset is a curated set of inputs paired with known-correct outputs, used as the fixed reference against which an AI system’s quality is measured over time.
The value is in the curation, not the size. Fifty cases drawn from real traffic and real reported failures catch more regressions than a thousand synthetic ones, and can be assembled in days. A golden set should grow every time a new failure mode is found in production — that is what stops the same bug shipping twice.
Related terms
- Eval harness
An eval harness is the test infrastructure for a non-deterministic AI system: a dataset of representative inputs, a method for scoring each output, and a threshold that determines whether a run passes or fails.
- Regression gate
A regression gate is a CI check that fails a build when an evaluation suite’s pass rate drops below a defined threshold, preventing a prompt or model change from shipping a quality regression.
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