How to Evaluate an AI Agent (When There's No Single Right Answer)
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You can't test an AI agent the way you test normal software. Agents are non-deterministic (same input, different outputs), open-ended (no single right answer), and multi-step (they can reach a good answer through a broken process). The answer is evaluation: a repeatable loop — define what good means, build a test set, measure with fitting metrics, and gate every change — that turns "it seemed to work" into "we measured it." Why agents break traditional testing Traditional software testing…
1Key Takeaways
- You can't test an AI agent the way you test normal software.
- Agents are non-deterministic (same input, different outputs), open-ended (no single right answer), and multi-step (they can reach a good answer through a broken process).
- The answer is evaluation: a repeatable loop — define what good means, build a test set, measure with fitting metrics, and gate every change — that turns "it seemed to work" into "we measured it." Why agents break traditional testing Traditional software testing….
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — AI reports that you can't test an AI agent the way you test normal software.
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