In fact, one of the developers in the original study later revealed on Twitter that he had already done exactly that during the study, i.e. filtered out tasks he prefered not to do without AI: https://xcancel.com/ruben_bloom/status/1943536052037390531
While this was only one developer (that we know of), given the N was 16 and he seems to have been one of the more AI-experienced devs, this could have had a non-trivial effect on the results.
The original study gets a lot of air-time from AI naysayers, let's see how much this follow-up gets ;-)
In either case, it seems people ended up bolstering their preexisting views on AI based on whichever study most affirmed them (for the former, that AI coding models didn't actually help and created a mirage of productivity that required more work to fix than was worth it, the latter that AI models were improving at an exponential rate and will invariably eclipse SWE's in all tasks in a deterministic amount of time.)
I think the truth is somewhere in the middle. Just anecdotally we've seen multi-million dollar fortunes being minted by small teams developing using 90% AI-assisted coding. Anthropic claims they solely use agents to code and don't modify any code manually.
Repeat devs from the original experiment went from 0-40% slowdown to now -10-40% speedup - and METR estimates this as a 'lower-bound'
more devs saying they dont even want to do 50% of their work without AI, even for 50/hr
30-50% of devs decided not to submit certain tasks without AI, missing the tasks with the highest uplift
it also seems like there is a skill gap - repeat devs from the first study are more productive with ai tools than newly recruited ones with variable experience
overall it seems like the high preference for devs to use AI is actually hurting METR's ability to judge their speedup, due to a refusal to do tasks without it. imo this is indirectly quite supportive for ai coding's productivity claims.
I get that developers want to use AI. But are they also claiming there's not still a no/low-AI population of developers? Or that their means of selection don't find these developers?
Are they worried that by splitting devs into groups of AI experience they might be measuring some confounder that causes people to choose AI / not AI in their careers?
> The subjects are using ChatGPT 2.5 and copy-pasting code.
The reason AI hype seems to be so bipolar is that "AI" isn't one thing. Hundreds of models, dozens of tools. And to get something done well, a seasoned engineer needs to master half a dozen at a time.