I can work on ideas with LLMs, even within my own area of expertise. They know quite a lot, and can take an idea I have and run with it. I would never trust them to be correct, but if I give them a new idea and ask them to work out details and raise any issues they find, I can quickly evaluate their findings, and take them into account when developing the idea further.
I do not do this on all ideas, not even most. Most of the time it is still me, a sheet of paper or some code. But still, comparing to how it was a year ago, it is night and day!
A year ago I would just close the window after the first reply, shaking my head at its stupidity. I can still get that experience by using anything but Opus 5.5 or Fable. I tried the $20 ChatGPT tier last week and was immediately thrown back to that old annoyance! (I am sure the best OpenAI models are fine)
Or my coworkers?
I'm pretty sure 'Who wants to be a millionaire' and the likes would work very differently if the contestants could search the internet for the answer.
I would also wager that OOP knows LLM limits quite well, and a more interesting discussion would be for why someone perceives LLMs as dumb as opposed to speculating whether they're aware of the frontier or not.
That is just my point though; these things still do happen, but much, much, much fewer than they used to, and this changes massively every month - both due to improvements in the models themselves, but also experience gained from operating them.
Forming an opinion on using agents for software work once, and then treating your experience as the status quo months later thus leads to wrong conclusions. If you give a model a way to evaluate its work in a short, closed feedback loop, you can orchestrate it to build correct systems pretty easily now. That definitely wasn't true even just three months ago.
If, however, you do not actually use this technology regularly, you will not be able to achieve good results, which objectively makes sense and wouldn't be different for any other skill either.