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AI Agents / Agent evaluation and observability

AI Agents: Regression severity weighting

Weight data loss and wrong-target writes more heavily than presentation defects.

Compiled for Sorlavit Kim · Published · Updated · 1 min read

Environment and inputs: Framework-independent agent evaluation; OpenTelemetry illustrates trace correlation.

When to use it

Choose an observable task outcome before optimizing a model or prompt. Keep inputs and scoring rules stable enough to compare candidates, and inspect critical failures individually rather than hiding them inside an average quality score.

Check the result

Verify a candidate with a severe failure cannot pass on average score alone.

Save and compare results

Save the test input, configuration and result. Fix the failing boundary, repeat the same test and compare it with the saved working configuration.

Scope and limits

These exercises have not been tested on your systems. Check feature support and configuration names against the installed release and linked documentation.

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