Performance work, lower level issues that interact with external software, hardware spec implementation, large testing efforts, long-standing customer-side issues. Anything that throwing AI at won't immediately solve.
Long before AI I've built a career around going after the tasks people deemed too difficult or too lenghty. This strategy creates a lot of room to negotiate. Now with AI, I'm seeing people walking in circles feeding one AI text into another and not being able to interpret the AI output. That's when they stop caring whether I'm using AI or not, as long as the problem gets solved.
You'll probably write way less code than before still, but at least you get to keep more general problem solving and code analysis skills.