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title: Don’t Let Claude Grade Its Own Homework | daily.dev
description: When AI coding agents like Claude produce large diffs at high speed, human review becomes the bottleneck. This post presents a cross-provider automated PR...
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# Don’t Let Claude Grade Its Own Homework

**[Towards Data Science](https://daily.dev/sources/tds)** · 25 min read · 0 upvotes · 0 comments

## Summary

When AI coding agents like Claude produce large diffs at high speed, human review becomes the bottleneck. This post presents a cross-provider automated PR review system: a Codex (OpenAI) agent runs in GitHub Actions to review every pull request authored by Claude. The core insight is that LLMs are biased toward their own output, so a reviewer from a different provider catches blind spots the author model misses. The setup includes a stateful prompt that tracks findings across pushes, honors written declines, and emits a machine-readable verdict parsed into a commit status. The post covers the full GitHub Actions workflow, prompt engineering for stateful reviews, cost/reliability lessons (model pinning, concurrency cancellation, retry logic), and Claude Code skills that automate the author-side response loop. The result: humans only see merge-ready PRs with a full audit trail.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://towardsdatascience.com/dont-let-claude-gaslight-you>

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---

Tags: [#ai-coding](https://daily.dev/tags/ai-coding), [#claude](https://daily.dev/tags/claude), [#github-actions](https://daily.dev/tags/github-actions), [#openai-codex](https://daily.dev/tags/openai-codex)

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