Eval-Driven Development: Risks and Rewards

Executable evaluations have improved development feedback for an embedded workflow-building copilot by turning vague complaints into specific, repeatable behavioral tests that can be addressed through a test-driven process. The approach uses tiers of testing, including deterministic unit tests for underlying agent functions, capability-suite integration evals for focused behaviors such as selecting authorized connections and explaining failures, and broad product-suite end-to-end evals that assess realistic user interactions like gathering workflow requirements. Developers use failed assertions, transcripts, tool calls, and artifacts to establish baselines and measure iterative improvements, while coding agents and subagents can accelerate experimentation under human oversight. The account also highlights the risk of Goodhart’s law, in which agents optimize narrowly for test scores rather than overall product quality, illustrated by an overly literal ban on congratulatory words. More effective mitigation emphasizes prompts that encourage direct, neutral, task-focused communication, alongside independent reviews and broader suite checks to prevent overfitting. The in-house Lux framework supports these evaluations and is intended to be described further in a later installment.

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