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.

Yes, and I'll add that there is likely no single "golden workflow" that works for everybody, and everybody needs to figure it out for themselves. It took me months to figure out how to be effective with these tools, and I doubt my approach will transfer over to others' situations.

For instance, I'm working solo on smallish, research-y projects and I had the freedom to structure my code and workflows in a way that works best for me and the AI. Briefly: I follow an ad-hoc, pair-programming paradigm, fluidly switching between manual coding and AI-codegen depending on an instinctive evaluation of whether a prompt would be faster. This rapid manual-vs-prompt assessment is second nature to me now, but it took me a while to build that muscle.

I've not worked with coding agents, but I doubt this approach will transfer over well to them.

I've said it before, but this is technology that behaves like people, and so you have to approach it like working with a colleague, with all their quirks and fallibilities and potentially-unbound capabilities, rather than a deterministic, single-purpose tool.

I'd love to see a follow-up of the study where they let the same developers get more familiar with AI-assisted coding for a few months and repeat the experiment.