So far I've found that the people who are hating on AI are stuck maintaining highly coupled that they've invested a significant amount of mental energy internalizing. AI is bad on that type of code, and since they've invested so much energy on understanding the code, it ends up taking longer for them to load context and guide the AI than to just do the work. Their code base is hot coupled garbage, and rather than accept that the tools aren't working because of their own lack of architectural rigor, they just shit on the tools. This is part of the reason that that study of open source maintainers using Cursor didn't consistently produce improvement (also, Cursor is pretty mid).

https://www.youtube.com/watch?v=tbDDYKRFjhk&t=4s is one of the largest studies I've seen so far and it shows that when the codebase is small or engineered for AI use, >20% productivity improvements are normal.