Your first link is (in my opinion) highly biased in the samples they choose, they hired maintainers from open-source repos (people with multi years of experience, on their specific repo).
So indeed, IF you are in that case: Many years on the same project with multiple years experience then it is not usefull, otherwise it might be.
This means it might be usefull for junior and for experienced devs who are switching projects.
It is a tool like any other, indeed if you have a workflow that you optimized through years of usage it won't help.
Exactly. I think the study is a good reminder that we really have to be careful about the productivity gains attributed to AI. Main takeaway imo, despite limitations from the study, is AI is not a panacea, it can increase productivity, but only if used 'well' and with the good workflows in place, and in the right context.
You are welcomed to your point of view, but for me while one agent is finding an obscure bug, I have another agent optimising or refactoring, while I am working on something else. Its hard to believe I am deluded in thinking I am spending more time on a task.
I think the research does highlight that training is important. I don't throws devs agents and expect them to be productive.
Your first link is (in my opinion) highly biased in the samples they choose, they hired maintainers from open-source repos (people with multi years of experience, on their specific repo).
So indeed, IF you are in that case: Many years on the same project with multiple years experience then it is not usefull, otherwise it might be. This means it might be usefull for junior and for experienced devs who are switching projects. It is a tool like any other, indeed if you have a workflow that you optimized through years of usage it won't help.
Exactly. I think the study is a good reminder that we really have to be careful about the productivity gains attributed to AI. Main takeaway imo, despite limitations from the study, is AI is not a panacea, it can increase productivity, but only if used 'well' and with the good workflows in place, and in the right context.
> This means it might be usefull for junior and for experienced devs who are switching projects.
In other words: it might be useful for people who don't understand the generated code well enough to know that it's incorrect or unmaintainable.
> Or so you think.. > [1] https://metr.org/blog/2025-07-10-early-2025-ai-experienced-o...
You are welcomed to your point of view, but for me while one agent is finding an obscure bug, I have another agent optimising or refactoring, while I am working on something else. Its hard to believe I am deluded in thinking I am spending more time on a task.
I think the research does highlight that training is important. I don't throws devs agents and expect them to be productive.
I mean, hacker news is still the same aren't they using AI to completely make this website more of whatever it was before ????