Developer Finds His AI Verification System Had the Same Blind Spots It Was Built to Catch

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A software developer built an automated browser-based verification gate using Claude Code and Kane CLI to confirm that AI agent tasks were genuinely complete before stopping. Across 12 tasks in a project called ORBITAL, eight failed at least once, but structured triage revealed most failures stemmed from flaky test scripts, timing issues, or stale recordings rather than actual bugs in the app. Only one genuine application defect was identified out of all eight flagged failures. The developer later discovered that his own written summary of the project had misattributed test failures to a sweep mechanism, mirroring the same misreading the verification system had been designed to prevent. The episode illustrates a recursive trust problem: automated verifiers can produce misleading signals, and human reviewers summarising those results are equally prone to error.

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