This work highlights a critical failure mode in AI systems: decisions that are correct, compliant, and authorized - but no longer valid at the moment they are executed.

The focus is on how outputs transition into authority through repeated use, and how systems can begin to act on those outputs without re-validating whether they still hold under current conditions.

It explores: – how authority forms through interaction, not just formal assignment – why governance often fails before execution, not after – where systems allow inadmissible actions to become real

This perspective is used to identify where AI-driven decisions drift from their original conditions - even when everything appears governed.