What Is Eval-Driven Development? How to Improve AI Agents

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Что произошло

LangChain describes eval-driven development, a methodology for building AI agents by defining success metrics upfront and iteratively comparing experimental changes against consistent benchmarks.

Почему это важно

Engineers building AI agents need this when manual testing becomes unreliable due to non-deterministic outputs and multiple valid answers, especially as agent complexity grows.

На что обратить внимание

Overfitting to evaluation datasets is a real risk; teams must maintain held-out test examples separate from tuning examples to verify genuine behavior improvement.