santa-method

Dual-review verification evaluates generated outputs using two independent reviewers applying an identical rubric to quantify safety and quality issues. This process mitigates individual reviewer biases and requires convergence before shipping outputs to production environments.

Enforce context isolation during multi-agent quality assurance by using fresh reviewers for each iteration. This prevents memory bias and maintains rigorous checks by ensuring each reviewer evaluates outputs independently without prior iteration context.

The best way to ensure convergence before shipping is applying a dual-review rubric and looping iterative fixes until both independent reviewers pass. This governance mechanism prevents systematic errors from reaching end users.

Convergence-based review works for multi-agent generated content by triggering two independent reviewers on the latest output. Both reviewers apply identical rubrics to evaluate the same output, ensuring unbiased coverage and quality assurance.

Fresh reviewers each round prevent memory bias in the convergence loop. By enforcing context isolation and using new reviewers for every iteration, the dual-review process maintains rigorous, unbiased evaluation of safety and quality issues.