In my experience, AI has given far more leverage to software engineers than anyone else, because they have a feel for what computers can do, what's easy, what's hard, what's performant, or poorly specified, etc. Therefore I think retraining is mostly about being willing to experiment with AI-assisted workflows and not being too tied to old ways of doing things. As long as you are focused on the problems you are solving, I think you'll do okay.

What I'm more concerned about are the younger generation where all the learning tasks have been automated. I have faith that the strong, naturally curious engineering types will still learn to do great engineering, and honestly without some of the mental blocks and calcified assumptions that us greybeards have. But how do they get in the foot in the door and the reps needed to develop senior-level judgment is another question.

In some sense we need the current mania to die down and the long-term maintenance implications of heavy AI assistance to become more apparent. Basically I think we need the AI bubble to pop and then 1-2 years for things to stabilize, and then we'll recalibrate on hiring expectations and best practices for AI usage. The current AI maximalist and doomer views I think are both basically driven by capitalist incentives and wishful thinking from investors and a reality check is going to come in some form (whether technically, socially or politically).