It depends. A lot of projects / features really don't require a ton of engineering thought. Add a new table that has some foreign keys with existing tables, add a new page that lets you modify that table, add a new set of REST CRUD handlers that do some validation and store the data, add a new message queue that does whatever needs to happen when the data gets changed.
If AI can handle things like that, then let AI do it: it's not really engineering work anyway; it's copy-and-paste from a previous design, just change the handler logic and the names of things. If 90% of incoming features are like that, then that gives you a lot more time to work on the 10% that are more complex.
Eventually, you'll end up with spaghetti code no matter how well you plan out the architecture, whether human or AI is doing designs. But it'll move that direction even faster with AI, and eventually AI won't be able to understand it well enough to reliably design things anymore. That's where the real engineering will come in. As the system evolves, how do we re-architect things so that AI (and humans) can understand the patterns again and make future changes more reliably?
Right now, it seems like services go through major refactors/rewrites like that every five years or so. And those rewrites tend to be slow and often unsuccessful: even though the existing system is complex, engineers are used to it and it's easier to add one more bandaid than to wait for the full rewrite. Then such rewrites can get stuck in navel-gazing as there's no "perfect" way to do them, and it's lower effort just to go back to the system you already know.
As AI creates more churn though, the architecture will need to be rethought much more frequently. Additionally there will be more urgency to deliver the cleanup because AI will be completely blocked by the existing spaghetti, which brings all product dev to a halt, and you don't have time for navel-gazing because there's no fallback option.
So I think the engineering work post-AI is really going to be this kind of infrastructural planning and rearchitecting, such that AI can deliver features on top of it without friction. And in a way, as an engineer, that's what I want to be doing anyway. We've always had this ideal of continuous refactoring and continuous improvement, that always gets pushed to the backburner when compared to feature development. "Sure this refactor will help future velocity, but we need to make our quarterly goals!" But now, AI will compress those timelines so that maintaining clean architectures has a direct effect on the deliverables of the current quarter.
I personally think this is great. If, in the future, PMs can launch whole features without engineers writing a line of code, that's awesome. It's our job to maintain a system where such an ideal is possible. Which sounds like the job I wanted when I originally signed up to be an engineer.