Of course agents is now a buzzword that means nothing so there is that.
I have been working on LLMs since 2017, both training some of the biggest and then creating products around them and consider I have no experience with agents.
GPT-3, while being impressive at the time, was too bad to even let it do that, it would break after 1 or 2 steps, so letting it do anything by itself would have been a waste of time where the human in the loop would always have to re-do everything. It's planning ability was too bad and hallucinations way to frequent to be useful in those scenarios.
Do you know of any kind of write up (by you or someone else) on this topic? Admittedly I never really spent too much time on this since I was working on pre-training, but I did try to do a few smart things with it and it pretty much failed at every thing, in big part because it wasn't even instruction tuned, so was very much still an autocomplete model.
So would be curious to learn more about how people got it to succeeed at agentic behaviors.