Evaluation Gate
An automated evaluation interception mechanism placed within CI/CD pipelines for code changes that affect LLM behavior. Instead of relying on manual code review, it runs evaluations against a golden dataset to ensure AI system quality.
Timeline (last 90 days)
An eval gate is the practice of connecting an evaluation suite into continuous integration: running the evaluator on a fixed dataset in the PR pipeline, comparing each metric against the main branch baseline, and blocking the merge if a threshold is exceeded.
Key design points for implementing an eval gate include: setting a tolerance for each metric rather than requiring it never to drop; distinguishing hard metrics (safety, compliance, tool-call legality) from soft metrics (tone, conciseness); tiering evaluation costs so a small dataset runs on every PR and the full dataset runs before merge or overnight; and writing the scores, judge version, and dataset version of each run into the experiment record.
All Facts (2)
An eval gate is the practice of connecting an evaluation suite into continuous integration: running the evaluator on a fixed dataset in the PR pipeline, comparing each metric against the main branch baseline, and blocking the merge if a threshold is exceeded.
50%UnverifiedKey design points for implementing an eval gate include: setting a tolerance for each metric rather than requiring it never to drop; distinguishing hard metrics (safety, compliance, tool-call legality) from soft metrics (tone, conciseness); tiering evaluation costs so a small dataset runs on every PR and the full dataset runs before merge or overnight; and writing the scores, judge version, and dataset version of each run into the experiment record.
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