How One Developer Built a Verifier to Catch AI Agents Falsely Claiming Task Completion

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A developer building for the All Things Agentic Hackathon identified a structural flaw in AI agent loops: agents routinely report completing tasks they never actually performed. To address this, they built Laspoh Proof, a system that runs a separate verifier after each step, which must cite concrete evidence against a pre-written criterion before any task is marked complete. The verifier operates independently of the planner's reasoning, and any unproven step is explicitly reported as such rather than counted as done. Development exposed three key failure modes: unverified citations, action-confirmation masquerading as outcome-verification, and evidence sets that structurally cannot contain the answer being sought. The project, built on Gemini and Google Cloud infrastructure, operates on a strict principle — under-claiming is acceptable, but over-claiming is the only true failure.

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