A new study challenges the common assumption that artificial intelligence always speeds up software development. Conducted by AI research nonprofit METR, the study focused on seasoned developers working with Cursor, a popular AI coding assistant, within open-source projects they knew well. Contrary to their expectations, these experienced developers took 19% longer to complete tasks when using AI compared to working without it.
Before the study, developers predicted AI would speed up their work by about 20-24%, but the actual results showed the opposite. The study’s lead authors, Joel Becker and Nate Rush, expressed surprise at the findings, with Rush originally anticipating a potential twofold productivity increase.
These findings complicate the popular narrative that AI tools dramatically boost the productivity of highly skilled engineers—a claim that has helped fuel heavy investment in AI-powered software development products. While AI is often touted as a way to replace entry-level coding jobs, the METR study reveals that its benefits may not extend to all developers or coding scenarios.
Previous research has shown significant AI-driven productivity gains, with some studies citing up to 56% faster coding speeds or 26% more tasks completed in a given time. However, METR’s work highlights that these improvements might be more relevant to junior developers or those unfamiliar with complex codebases. Experienced developers, intimately aware of the nuances of mature open-source projects, tended to slow down because they spent extra time reviewing and fixing AI suggestions.
Becker noted that while AI-generated code was often on the right track, it frequently required careful correction to meet precise needs. The study authors emphasized that the slowdown was specific to the context of experienced developers working in familiar environments and might not occur in other development settings.
Despite the slower task completion times, most participants, including the study authors, continue to use Cursor, finding that AI makes coding less effortful and more enjoyable—comparable to editing an essay rather than starting from scratch. Becker explained, “Developers have goals other than completing the task as soon as possible. So they’re going with this less effortful route.”