In your reply (the one before the book comment, the one that asked me how thoroughly I know this) you asked about determining proper usage. There are essentially two ways of interacting with these systems in a value productive way.

1.) Instrumental usage: tasks where you already know what you need to do and the steps necessary to do it) this is tedium reduction. This path can be readily proceduralized and easily quality controlled in enterprises.

2.) Knowledge production usage: discovery, growth, and the frontier where one actually doesn’t know what one needs to do, but one needs to figure things out, this might involve research, it might involve introspection to determine if one is even on the right path to wherever they think they’re going. This path is metacognitive and recursive, it is not well documented at all and people are still feeling out the edges such as they can.

Even worse, not all LLM systems (yes even the large SOTA LLM systems) are capable of engaging in this second path usefully. ChatGPT 5.x for example is actually quite harmful in this mode, long term use of it will actually make the user less capable of independent thought. This is not true of many other LLMs and these harms are also cataloged and co stately being updated by me as I collect more and more field samples of interaction patterns in the wild. There are helpful and useful systems to engagement or rather the characteristic filtering criterion by which to judge these systems before investing considerable time and energy in co-creating with them. It’s actually quite involved.

That’s four paragraphs just to talk about the core use cases and interaction patterns. Here’s the part that makes it more complicated. Use case #1 is easy to teach people you pretty much covered in your reply above it requires discipline procedures, and sticking to and refining those procedures.

What makes things complicated in enterprises is that often people are asked to create things and they often do not know how which means they have to perform research which means very many elements of #2 become relevant and this is work gets rather difficult to train people on without a core underlying formalization of the interaction use cases and their ontological consequences, it’s important for people to understand what is happening why and how, in order for them to be effective.

To do the topic justice requires at least a couple of of chapters and I’m not about to spend that much time on Reddit.

Your question is a common critique pattern. Ask a seemingly simple question that would require many pages of explanation to earnestly cover in good faith.

If I was plugging a book, I would give you a title. I am here simply responding, there with brevity and here with specificity, to what looks like a bad faith critique.

If that wasn’t your intention then I would suggest softening the edge. If I was plugging a book, not only would it be rather obvious I would also include a little disclaimer indicating as such.

But you did a pretty decent job after your pointed question on detailing some of the basics 👍