santa-method

Verify AI generated content for compliance and hallucinations by running dual independent reviewers against an identical objective rubric, requiring both to return structured PASS verdicts before production release. Targeted fixes are applied to any flagged issues until convergence.

Dual independent review for high-stakes AI outputs is a quality gate where two isolated reviewer agents evaluate the same deliverable using the same rubric without seeing each other's assessments, preventing context bleed and rubber-stamping of non-compliant content.

Stop AI reviewers from rubber-stamping or drifting during compliance validation by isolating their reviewer contexts and applying structured PASS/FAIL JSON verdicts against an identical objective rubric, ensuring independent assessments that prevent context bleed and reviewer drift.

You can use iterative fixing for production code that fails adversarial verification by triggering targeted re-generation of only the flagged issues, looping both reviewers until convergence or maximum iterations are reached to prevent fix regression.

Use a strict both-pass verdict gate for regulated language when human spot-checking is insufficient and constraint violations are unacceptable, requiring two independent reviewers to pass the same objective rubric before deployment-ready content ships.

Limitations of using dual review loops for technical documentation include potential infinite loops mitigated by max iterations, and the risk of fix regression requiring targeted re-generation of only flagged issues rather than full re-generation to maintain convergence.