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688 points dheerajvs | 1 comments | | HN request time: 0.409s | source
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simonw ◴[] No.44523442[source]
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.

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smokel ◴[] No.44523720[source]
I notice that some people have become more productive thanks to AI tools, while others are not.

My working hypothesis is that people who are fast at scanning lots of text (or code for that matter) have a serious advantage. Being able to dismiss unhelpful suggestions quickly and then iterating to get to helpful assistance is key.

Being fast at scanning code correlates with seniority, but there are also senior developers who can write at a solid pace, but prefer to take their time to read and understand code thoroughly. I wouldn't assume that this kind of developer gains little profit from typical AI coding assistance. There are also juniors who can quickly read text, and possibly these have an advantage.

A similar effect has been around with being able to quickly "Google" something. I wouldn't be surprised if this is the same trait at work.

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1. blub ◴[] No.44528530[source]
One has to take time to review code and think through different aspects of execution (like memory management, concurrency, etc). Plenty of code cannot be scanned.

That said, if the language has GC and other helpers, it makes it easier to scan.

Code and architecture review is an important part of my role and I catch issues that others miss because I spend more time. I did use AI for review (GPT 4.1), but only as an addition, since not reliable enough.