I do not agree with @FiniteBanjo@lemmy.today’s take. LLMs as these are used today, at the very least, reduces the number of steps required to consume any previously documented information. So these are solving at least one problem, especially with today’s Internet where one has to navigate a cruft of irrelevant paragraphs and annoying pop ups to reach the actual nugget of information.

Having said that, since you have shared an anecdote, I would like to share a counter(?) anecdote.

Ever since our workplace allowed the use of LLM-based chatbots, I have never seen those actually help debug any undocumented error or non-traditional environments/configurations. It has always hallucinated incorrectly while I used it to debug such errors.

In fact, I am now so sceptical about the responses, that I just avoid these chatbots entirely, and debug errors using the “old school” way involving traditional search engines.

Similarly, while using it to learn new programming languages or technologies, I always got incorrect responses to indirect questions. I learn that it has incorrectly hallucinated only after verifying the response through implementation. This makes the entire purpose futile.

I do try out the latest launches and improvements as I know the responses will eventually become better. Most recently, I tried out GPT-4o when it got announced. But I still don’t find them useful for the mentioned purposes.

Mate, all it does is predict the next word or phrase. It doesn't know what you're trying to do or have any ethics. When it fucks up it's going to be your fuckup and since you relied on the bot rather than learned to do it yourself you're not going to be able to fix it.

I think they do have their help, but it’s not nearly as dramatic as some companies earning money from it want us to think. It’s just a tool that helps just like a good IDE has helped in the past.