更多线路，更多拉取请求，相同的交付软件。瓶颈转移到了审核上。
哈佛大学的研究人员查看了 718 家公司超过 700,000 名员工的数据，发现完全代理的编码工具使代码行数增加了 30%，拉取请求增加了 23%。这两个数字均具有统计显着性。
令人不安的部分是：他们发现已解决的问题或史诗（它们实际发布的软件的替代品）没有明显的变化。收益体现在数量上，而不是结果上。
他们追踪审查。团队采用代理后，审查拉取请求的时间增加了 49%，每个请求的评论增加了 35%。特工写的速度比人类检查的速度快。
教训不是“停止使用代理人”。这是“雇用审阅者，否则代码就会堆积起来无人阅读。”我们优化了作家并忘记了编辑器。
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人工智能工具太多？这是找到您真正需要的东西的更好方法
If you only check AI news on weekends, this was the weekend to check. The theme was not a bigger model, it was models that do a specific job well enough to hand them the keys.
A model that finds vulnerabilities but refuses to step outside authorized scope is not just a better scanner. It is the first time the powerful exploit-finder has been gated to the people who already had permission to look.
