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.
We have 2 sibling teams, one the genAI devs and the other the regular GPU product devs. It is entirely unsurprising to me that the genAI developers are successfully using coding agents with long-running plans, while the GPU developers are still more at the level of chat-style back-and-forth.
At the same time, everyone sees the potential, and just like other automation movements, are investing in themselves and the code base.