Measuring the impact of AI on experienced open-source developer productivity

> developers expected AI to speed them up by 24%, and even after experiencing the slowdown, they still believed AI had sped them up by 20%.

I feel like there are two challenges causing this. One is that it's difficult to get good data on how long the same person in the same context would have taken to do a task without AI vs with. The other is that it's tempting to time an AI with metrics like how long until the PR was opened or merged. But the AI workflow fundamentally shifts engineering hours so that a greater percentage of time is spent on refactoring, testing, and resolving issues later in the process, including after the code was initially approved and merged. I can see how it's easy for a developer to report that AI completed a task quickly because the PR was opened quickly, discounting the amount of future work that the PR created.

Qualitatively, we don't see a drop in PR quality in between AI-allowed and AI-disallowed conditions in the study; the devs who participate are generally excellent, know their repositories standards super well, and aren't really into the 'get up a bad PR' vibe -- the median review time on the PRs in the study is about a minute.

Developers totally spend time totally differently, though, this is a great callout! On page 10 of the paper [1], you can see a breakdown of how developers spend time when they have AI vs. not - in general, when these devs have AI, they spend a smaller % of time writing code, and a larger % of time working with AI (which... makes sense).

[1] https://metr.org/Early_2025_AI_Experienced_OS_Devs_Study.pdf