Don’t Let Claude Grade Its Own Homework

Using one AI model to review the code generated by another from a different provider can effectively catch errors and hallucinations. The author argues that self-review is weak because a model is biased towards its own plausible-sounding but incorrect output, a claim supported by research. A proposed solution involves an automated GitHub Actions workflow where OpenAI's Codex reviews pull requests generated by Anthropic's Claude. This cross-provider approach leverages the different training data and failure modes of each model to improve code quality before human review. The system is detailed with specific code examples for the GitHub workflow and action configuration.