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

My personal theory is that getting a significant productivity boost from LLM assistance and AI tools has a much steeper learning curve than most people expect.

This study had 16 participants, with a mix of previous exposure to AI tools - 56% of them had never used Cursor before, and the study was mainly about Cursor.

They then had those 16 participants work on issues (about 15 each), where each issue was randomly assigned a "you can use AI" v.s. "you can't use AI" rule.

So each developer worked on a mix of AI-tasks and no-AI-tasks during the study.

A quarter of the participants saw increased performance, 3/4 saw reduced performance.

One of the top performers for AI was also someone with the most previous Cursor experience. The paper acknowledges that here:

> However, we see positive speedup for the one developer who has more than 50 hours of Cursor experience, so it's plausible that there is a high skill ceiling for using Cursor, such that developers with significant experience see positive speedup.

My intuition here is that this study mainly demonstrated that the learning curve on AI-assisted development is high enough that asking developers to bake it into their existing workflows reduces their performance while they climb that learing curve.

LLMs have a v. steep and long learning curve as you posit (though note the points from the paper authors in the other reply).

Current LLMs just are not as good as they are sold to be as a programming assistant and people consistently predict and self-report in the wrong direction on how useful they are.

One thing that happened here is that they aren't using current LLMs:

> Most issues were completed in February and March 2025, before models like Claude 4 Opus or Gemini 2.5 Pro were released.

That doesn't mean this study is bad! In fact, I'd be very curious to see it done again, but with newer models, to see if that has an impact.

I've been hearing this for 2 years now

the previous model retroactively becomes total dogshit the moment a new one is released

convenient, isn't it?

Even then though, “technology gets better over time” shouldn’t be surprising, as it’s pretty common.

For context, I've been using AI, a mix of OpenAi + Claude, mainly for bashing out quick React stuff. For over a year now. Anything else it's generally rubbish and slower than working without. Though I still use it to rubber duck, so I'm still seeing the level of quality for backend.

I'd say they're only marginally better today than they were even 2 years ago.

Every time a new model comes out you get a bunch of people raving how great the new one is and I honestly can't really tell the difference. The only real difference is reasoning models actually slowed everything down, but now I see its reasoning. It's only useful because I often spot it leaving out important stuff from the final answer.