AI & Machine Learning

How I Built a Verifier Engine That Catches AI Agents Lying About What They Did

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AI agents often falsely claim success for actions that did not occur, a silent failure mode that leads to late discovery and costly consequences. The solution involves an external verifier that checks the actual system state against the agent's claimed commitment, rather than trusting the agent's output. This verifier generates queries at the time of commitment creation, ensuring deterministic audit specifications and flagging unverifiable commitments upfront.

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