I wrote a book about software engineering mental models that barely mentions AI on purpose. Only in the Appendix section I explain the rationale for not talking about AI, pasting it here:

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Thoughts on AI

I consciously decided not to talk about AI throughout this book. Not because I don't believe in the benefits of using AI... I do.

I believe AI will keep bringing a lot of value to society.

I believe AI will keep changing our profession in many profound ways.

But whatever happens, I believe the principles here are still going to be incredibly valuable, even if the software engineer profession ceases to exist with its current name.

We might be working at a totally different level of abstraction, but the values, principles, mental models, patterns of communication and behavior described in this book will still make a huge difference. I believe they are atemporal.

Having said that, here are my recommendations regarding AI:

- Think of AI as another tool you have to create value, just like your IDE, the code you write or the emails you send.

- Keep yourself long enough in the problem space before throwing an AI api to solve a problem that might not exist

- Unless you are working at the frontier of AI development, ignore the noise. AI is now the shiny object everyone wants to be up to date with. JavaScript frameworks were used as a joke between value-driven software engineers because there would be a new one every 6 months and a lot of people would move to it without the real need. AI changes and improves every day or week. Being on top of it is probably a full time job. Instead of following all the news on a daily basis, level up your AI game in batches every 3 or 6 months. It will be more than enough.

- The most interesting use of AI for me has been in finding out my unknowns-unknowns. One question I frequently ask is "What are the building blocks of this problem/system/piece of knowledge?"