Maybe. The point is that in case of software it is fairly easy to verify if that what LLM produced is correct or not. Compiler checks syntax, we can write tests, there is whole infrastructure for checking if something works as expected. In addition, LLM are just text generating algorithms and software is all about text, so if LLM see 1 000 000 a CRUD example in Python, it can generate it easily, as we have a lot of code examples out there thanks to open source.

That's why LLMs shine in coding tasks. If you move to other parts of engineering, like architecture, construction or stuff like investment (there is no AI boom there, why?) where there is no so much source text available, tasks are not so repeatable like in software, or verification is much more complicated, then LLM-s are no longer that useful.

In software also I believe we will see soon that a competitive advantage have not those who adopted LLM, but those who did not. If you ask LLM what framework/language/approach use for a given task, contrary to what people think, LLM is not "thinking", it just generates text answer on the base of what it was trained on, so you will get again and again same most popular frameworks/langs/approaches suggested, even if there is something better, yet not that popular to get into model weights in a significant way.

Interesting times, anyway.