AI Code Verification Fails When Tests and Code Share the Same Wrong Assumption

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A developer building an AI-assisted password reset feature discovered that even independently written behavioral specifications can be incomplete, missing edge cases like concurrent token reuse. Community feedback revealed that when an AI agent writes both code and tests, both artifacts can encode the same incorrect assumption, undermining the premise of independent verification. A separate example showed a test harness misreporting a timeout as a definitive failure, conflating an observation problem with a factual assertion about system behavior. These cases highlight that generating more tests or using adversarial agents does not uncover missing requirements if the definition of correct behavior was never explicitly established. The core challenge identified is not who writes the tests, but where the authoritative definition of correct behavior originates and how it gets updated as new edge cases are discovered.

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