We also haven't really seen how large volumes of generated sourcecode will stand up over time (like, decades) in terms of maintainability. My prediction is you

We also haven't really seen how large volumes of generated sourcecode will stand up over time (like, decades) in terms of maintainability. My prediction is you'll encounter a lot more disposable software. That's fine for making general code more of a commodity (cheap and accessible), but where you get commodities you eventually find demand for more premium flavors of product. Those tend to derive from taste and opinion (attributes which, for example, were major success factors of the iPhone at its peak design). The act of software development formalizes paradigms, surfaces unknowns and forces their resolution. Traditionally the work product gets better over time as you iterate. My own coarse rule of thumb is on average it takes until version 3 or so - i.e. 3 rewrites - until you to land at the kind of high caliber product that stems from really understanding the problem space and having worked in it extensively enough to have a good mental model and have uncovered the edge cases and hammered out an optimal solution. While AI is famous for fast iteration, I expect in cases where the designers wielding the tool lack a deep understanding of what's going on, potentially exacerbated by never actually having to work with the codebase, it may actually turn out to impede their ability to reach that plateau. Not saying this will be true for all use cases, just that the tool makes it seductively easy to fall into that trap.