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AI 编程智能体生成了更多代码，但并没有生成更多软件
一项对数百家公司编程实践的研究发现，人工代码审查是 AI 编程工具整体效率的一大瓶颈，导致几乎没有证据表明企业使用 AI 工具能提高软件产量或减少就业。研究涵盖了 2021-2026 年 3 月间逾 700 家软件开发公司逾 70 万员工的 3 亿条工作事件（如 commits 和 pull requests）以及问题管理软件数据。公司在引入 AI 编程代理后，代码总行数平均增加了 30%，commit 总数增加了 20%，pull requests 总数平均增加了 23%。但代码行数的增加并没有直接转化为软件产出的提升。原因在于代码审查流程，引入 AI 编程智能体后，代码审查的平均耗时明显延长。总体而言，引入 AI 智能体后，代码审查流程时间平均增加了 49%。引入 AI 智能体后，代码审查的员工人数增加了 14%。虽然 AI 智能体贡献了部分代码审查意见和 pull requests，绝大部分审查工作仍然是由人类完成的。
https://arstechnica.com/ai/2026/10/ai-coding-agents-generate-more-code-but-not-more-software/
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AI programming AI agent generated more codes, but not more software
A study of programming practices in hundreds of companies found that the manual code review was a major bottleneck in the overall efficiency of the AI programming tool, leading to little evidence that businesses could use the AI tool to increase software production or reduce employment. The study covered over 300 million work events (such as committees and pull requests) and problem management software data for over 700 software development companies with more than 700,000 employees in March 2021-2026. With the introduction of AI programming agents, the number of code lines increased by an average of 30 per cent, the total number of lines increased by 20 per cent and the total numbers increased by an average of 23 per cent. However, the increase in code lines has not been directly translated into an increase in software output. This is because the code review process, which introduced AI programming AI agent, resulted in the apparent extension of the code review average latency. Overall, the introduction of AI AI agent resulted in an average increase in code review process time of 49 per cent. With the introduction of AI AI agent, the number of code review staff increased by 14 per cent. Although AI AI agent contributed some code reviews and pull reviews, the majority of reviews are still human.
https://arstechnica.com/ai/2026/10/ai-coding-agents-generate-more-code-but-not-more-software/
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