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

Here's the full paper, which has a lot of details missing from the summary linked above: https://metr.org/Early_2025_AI_Experienced_OS_Devs_Study.pdf

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.

Well, there are two possible interpretations here of 75% of participants (all of whom had some experience using LLMs) being slower using generative AI:

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.

> Current LLMs

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.

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

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?

Convenient for whom and what...? There is nothing tangible to gain from you believing or not believing that someone else does (or does not) get a productivity boost from AI. This is not a religion and it's not crypto. The AI users' net worth is not tied to another ones use of or stance on AI (if anything, it's the opposite).

More generally, the phenomenon this is quite simply explained and nothing surprising: New things improve, quickly. That does not mean that something is good or valuable but it's how new tech gets introduced every single time, and readily explains changing sentiment.

Honestly the hype cycle feels very like crypto, and just like crypto prominent vcs have a lot of money riding on the outcome.

Of course, lot's of hype, but my point is that the reason why is very different and it matters: As an early bc adopter making your believe in bc is super important to my net worth (and you not believing in bc makes me look like an idiot and lose a lot of money).

In contrast, what do I care if you believe in code generation AI? If you do, you are probably driving up pricing. I mean, I am sure that there are people that care very much, but there is little inherent value for me in you doing so, as long as the people who are building the AI are making enough profit to keep it running.

With regards to the VCs, well, how many VCs are there in the world? How many of the people who have something good to say about AI are likely VCs? I might be off by an order of magnitude, but even then it would really not be driving the discussion.