I've done the same, and my experiences also match those in the article. Using a LLM as an autocomplete (typescript, kotlin) I found it'd be right about 10% of

I've done the same, and my experiences also match those in the article. Using a LLM as an autocomplete (typescript, kotlin) I found it'd be right about 10% of the time, very obviously wrong ~30% of the time, but mostly (~60%) *plausible*. Plausible is the worst, because if I don't spot the error immediately it'll come back to bite me in the coming hours/weeks and it takes me much longer to fully comprehend existing code than it does to write new code myself. Asking questions fares better, but I never have easy questions and for difficult ones it'll usually be wrong. Like, if I'm asking an LLM a question I'm usually at a point where I've read the docs and there's something I don't understand - so it's not that surprising that the LLM won't understand it either. Occasionally pointing out the flaw will get a better answer, but more often it just leads to a circle of flawed answers. I feel like people who say this is some sort of revolution are perhaps people who weren't very good at finding information themselves. The only places where this stuff seems to be an unqualified success so far is for jobs where the quality of the output is not very important.