It might make sense to learn now, before everyone expects that you be an expert with this tool in order to do your job. On the other hand perhaps they will be easier to learn if you wait.
There is an incredible amount of nuance to be had in using LLMs and we reached the stage, probably only in the last few weeks where all the pieces have fallen into place such that if you are skilled at using the LLMs just about all of the previous problems with them can now be easily mitigated. If you learn how. There is a lot to learn.
"we reached the stage, probably only in the last few weeks where ..." This has also been said every other month since 2023.
Personally I disagree with this. I've been using LLMs the last few years and learning a lot about techniques for getting value out of them. Even though they weren't very good for a while they seemed worth learning to me because the rate of improvement was so fast. We've now reached a point where if you know how to use them right you can get lots of value out of them.
I really don't mean to be rude here but consider perhaps the reason why you're having trouble seeing why they're valuable is because you haven't used them enough in the last few years or kept up with the developments closely enough. Maybe I'm wrong. But consider it's possible you are too.
> This has also been said every other month since 2023.
I'm sure others have said that but my perspective has been that the models are not quite good enough yet, for a while but that the trajectory is so crazy that it made sense to make the bet and invest lots of time into learning how to use them on the assumption that they would soon be good.
Even now I would say they have a long way to go. What is hard but possible today will be easy tomorrow. But quite a lot is now possible with the right techniques. Crazy things.
It really is like working with an over-eager employee. They just also happen to be a pathological liar.