Classifiers to classify things, traditional neural nets to identify things. Typical run of the mill.

In OpenAI hype language, this is a problem for "Software 2.0", not "Software 3.0" in 99% of the cases.

The thing about matching an informal tone would be the hard part. I have to concede that LLMs are probably better at that. But I have the feeling that this is not exactly the feature most companies are looking for, and they would be willing to not have it for a cheaper alternative. Most of them just don't know that's possible.

I'm assuming the post is about automated "context engineering". It's not a human doing it.

In this arrangement, the LLM is a component. What I meant is that it seems to me that other non-LLM AI technologies would be a better fit for this kind of thing. Lighter, easier to change and adapt, potentially even cheaper. Not for all scenarios, but for a lot of them.

Yes, when all is said and done people will realize that artificial intelligence is too expensive to replace natural intelligence. AI companies want to avoid this realization for as long as possible.