Equation 4 · Building a Custom Evaluation Suite for a Production Agent
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Because a “pass” verdict is itself often a noisy measurement, not a fact, it is worth being explicit about how much noise a single run’s outcome carries before treating a change in the pass rate as real. If a task’s true pass rate is p under a baseline configuration and a candidate change is worth detecting only once it shifts that rate by at least , the number of repeated trials needed per configuration to detect the shift reliably — at significance level and statistical power 1- — is approximately
Sources cited in the article section
- [1] Demystifying evals for AI agents ↗
- [6] Evaluate systematically ↗
- [2] Your AI Product Needs Evals ↗
- [5] Evaluation best practices ↗
- [7] How to build continuous evaluation for AI agents with trace classifications ↗
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