Yeah, people seem to forget one of the L's in LLM stands for Language, and human language is likely the largest chunk in training data.

A cli that is well designed for humans is well designed for agents too. The only difference is that you shouldn't dump pages of content that can pollute context needlessly. But then again, you probably shouldn't be dumping pages of content for humans either.

It's not obvious that human language is or should be the largest amount of training data. It's much easier to generate training data from computers than from humans, and having more training data is very valuable. In paticular, for example, one could imagine creating a vast number of debugging problems, with logs and associated command outputs, and training on them.

I also feel like it's just a matter of time until someone cracks the nut of making agents better understand GUI's and more adept at using them.

Is there progress happening in that trajectory?