Code analysis firm sees no major benefits from AI dev tool when measuring key programming metrics, though others report incremental gains from coding copilots with emphasis on code review.
Hell yea. Our unit test coverage went way up because you can blow through test creation in second. I had a large complicated migration from one data set to another with specific mutations based on weird rules and GPT got me 80% of the way there and with a little nudging basically got it perfect. Code that would've taken a few hours took about 6 prompts. If I'm curious about a new library I can get a working example right away to see how everything fits together. When these articles say there's no benefit I feel people aren't using these tools or don't know how to use them effectively.
From the combined comments it looks like if you are a beginner or a pro then it's great; if you only have just enough knowledge to be dangerous (in german that's proverbial "gefährliches Halbwissen") you should probably stay away from it :-)
We always have to ask what language is it auto-completing for? If it is a strictly typed language, then existing tooling is already doing everything possible and I see no need for additional improvement. If it is non-strictly typed language, then I can see how it can get a little more helpful, but without knowledge of actual context I am not sure if it can get a lot more accurate.