哈佛研究：AI 生成代码因下游瓶颈未能提升生产力
原标题：Study Finds AI-generated Code Fails to Boost Productivity Due to Downstream Bottlenecks
AI 摘要
哈佛大学基于 Jellyfish 平台对 718 家企业、约 3 亿条工作事件的研究发现，AI 编程助手和智能体虽能提升代码产出（智能体使代码行数增加 30%），但并未带来等比例的任务完成量提升。原因是 AI 生成的代码加重了代码审查等下游环节负担：PR 审查时间增加 49%，每条 PR 评论数增加 53%，需返工的 PR 占比翻倍。研究者认为，写代码仅占工程师 30-40% 的时间，其余互补环节成为瓶颈。
正文节选
A recent Harvard study of 718 firms, using the Jellyfish analytics platform, finds that although AI coding assistants and agents increase code volume, this does not translate into a corresponding increase in completed work, partly because AI-generated code increases the workload in later stages of development, particularly code review. The study was based on approximately 300 million work events of 700,000 workers across 700+ firms from January 2021 to March 2026. The data was gathered from seve