Never have FOMO when it comes to AI. When it's good enough to be a competitive advantage, everyone will catch up with you in weeks, if not days. All you are doing is learning to deal with the very flaws that have to be fixed for it to be worth anything.
Embrace that you aren't learning anything useful. Everything you are learning will be redundant in a year's time. Advice on how to make AI effective from 1 year ago is gibberish today. Today you've got special keyword like ultrathink or advice on when to compact context that will be gibberish in a year.
Use it, enjoy experimenting and seeing the potential! But no FOMO! There's a point when you need to realize it's not good enough yet, use the few useful bits, put the rest down, and get on with real work again.
If it takes you hours to figure out what's working and what's not, then it isn't good enough. It should just work or it should be obvious when it won't work.
I mean that’s like saying doing normal coding or working on any project yourself isn’t good enough because you put in hours to figure out what works and doesn’t.
That analogy is off, because LLMs aren't a project I'm working on. They are a tool I can use to do that. And my expectation on tools is that they help me and not make things more complicated than they already are.
When LLMs ever reach that point I'll certainly hear about it and gladly use them. In the meantime I let the enthusiasts sort out the problems and glitches first.
I’d rather put hours in figuring out what works and what doesn’t to get more value out of my future use.