This is a fair observation, and I think it actually reinforces the argument. The burnout you're describing comes from treating AI output as "your code that happens to need review." It's not. It's a hypothesis. Once you reframe it that way, the workflow shifts: you invest more in tests, validation scenarios, acceptance criteria, clear specs. Less time writing code, more time defining what correct looks like. That's not extra work on top of engineering. That is the engineering now. The teams I've seen adapt best are the ones that made this shift explicit: the deliverable isn't the code, it's the proof that the code is right.