Anyone who says yes is clearly not knowledgeable. Its like asking a spaghetti developer if they think their code is good. AI Physcosis is unlocking a new incompetence fear in me.

First thing is to separate out the term AI from LLM’s.

AI as a term encompasses many different technologies, some going back decades, a lot of which is used all over the place.
What we’re hearing a lot about right now are LLM’s and the surrounding ecosystem.

To answer the question though, yes, they can be used to produce output that fits a use case.
Whether or not it’s the best tool for the job is subjective, even in the cases where it’s technically viable.

There is a lot of bias and a lot of arguments for both sides.

You’d probably be best served by reading around a bit and figuring out how you feel about it.

You’re unlikely to get an unbiased discussion from a single source, especially here.
I’m not excluding myself , I’m bias AF.

The technology is interesting, the industrial implementation is an environmental and societal catastrophe.

It depends. At least, I find that it has a habit of falling on its metaphorical face if the task is anything more complex than the simplest things, so the idea that people can use it to make viable programs is baffling to me.

“Put these values into the CSV” works okay enough, but if you task it with more than that, like see if a column of values in the CSV is entered correctly from the markdown, it breaks.

Or it gets stuck in a loop, and there’s a very short point where it is faster to enter it by hand. Slightly ironic, though, that a language model doesn’t do too well with natural language processing.

I’d certainly not trust it for anything important like a production database, but the csv/markdown thing isn’t, and it’s no big deal if it gets destroyed by the model/agent, so it’s interesting to poke around with, and feel out the limitations, so you know its strengths and weaknesses.