Only in some industries, and only on modern stacks. Those of us who work on legacy platforms in enterprise environments don't need it at all. On the contrary, the younger folks who use it can't get good info out and are trashing systems when they try.

I do use basic LLM assistance, at a chatbot level. It is close enough and quick enough to give me a good head start when writing something new, and its problems are fairly quick to see and fix. But the fully baked tools are overkill for the value they offer, at least where I work.

I'd say that you need to know your environment, know what AI tools are available, and know which ones work best in your particular slice of the industry. Because if I ever go back to modern stacks, I know the AI tolls will have far more value.

Sometimes I wonder if my timing is really 'bad', to be out of work in a year that the learning curve become so steep.

Then when I worked with AI coding tool, it's like coaching a new junior. Though their 'way of coding' bought a lot of 'surprises'.

100% agree. I'm currently out of tech (and not all that likely to return) but this is the one thing I feel certain about if I do decide to come back: there will not be a place for me as some sort of artisanal, non-"AI-first/fluent" engineer (whether I like it or not).

Even in adjacent roles (design, PM, etc), I'm confident "how do you leverage AI?" will be one of the central evaluation questions.

Edit: for emphasis, again: whether I like it or not.