文章讨论了AI辅助代码审查中常见的失败，特别是在模型在建立可复现的bug之前审查代码时。文章提出了一种工作流程，首先创建一个包含失败命令、预期输出和相关固定装置的“审查捆绑包”。这个不包含秘密的捆绑包随后会与模型共享以供审查。AI代理重试也出现了类似的问题，将原始提示覆盖为一个简短的注释会破坏关键的调试证据。作者建议实施“提示冻结”——在任何后续调用之前记录提示、工具模式、工单ID和重试所有者的简短文件，以确保清晰的审计跟踪并防止上下文丢失。 AI
影响 凸显了AI辅助代码审查和调试中的关键问题，并提出了改进可靠性和可审计性的方法。
排序理由 该集群讨论了AI辅助工作流程中的最佳实践和常见失败，而不是特定的发布或事件。
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