One signal

Using different instances of the same AI model for code review could leave shared blind spots, argues developer Paddo in a new analysis of Anthropic’s Claude Code process.

Paddo says tests adding a second model from another lab caught significant bugs missed by the first reviewer. The proposed takeaway is practical: model diversity may be more useful than asking one model to review its own work again and again. That is a reported test, not proof that every multi-model setup is safer. But it gives teams a concrete question to ask before trusting AI review: is the second opinion genuinely independent?

Discuss: Should teams require a different model to check AI-written code, or is a well-tested single-model review process enough?

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