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.
The developer who has experience using cursor saw a productivity increase not because he became better at using cursor, but because he became worse at not using it.
A much simpler explanation is what your parent offered. And to many behavioralists it is actually the same explanation, as to a true scotsm... [cough] behavioralist personality is simply learned habits, so—by Occam’s razor—you should omit personality from your model.
Cognitive science was able to explain stuff like biases, pattern recognition, language, etc. which behavioral science thought they could explain, but couldn’t. In the 1950s it was really the only game in town (except for psychometrics which failed in a way much more complete—albeit less spectacular—way then behaviorism), so understandably scientists (and philosophers) went a little overboard with it (kind of like evolutionary biology did in the 1920s).
I think a more fair viewpoint is to claim that behaviorism’s heyday in the 1950s has passed, but it still provides an excellent theoretical framework for some of human behavior, and along with cognitive science, is able to explain most of what we know about human behavior.