[dwallin]

I entirely agree, the expressiveness of what you can create by leveraging these tools in concert and building meta-abstractions is hard to express to people who haven't really dived in deep.

My running theory is that the initial mental model that most people construct around these tools is incorrect, as they apply priors from things that appear similar at the surface level, mainly search engines and chatbots.

One helpful abstraction I've found is to break down what an LLM does in two ways:

1) It can operate as a language calculator. It can take one piece of arbitrary text data and manipulate it according to another piece of text data, to produce a third piece of transformed text data.

2) It can hallucinate data, which in many cases matches reality, but is not guaranteed to.

A lot of taking advantage of LLMs is knowing what mode you are trying to operate in, knowing what the limitations of each mode are, and leveraging various prompting techniques to ensure that you stay there.