AI is also excellent at reverse engineering specs from existing code, so you can also ask it to reflect simple iterative changes to the code back into the spec, and use that to guide further development. That doesn't have much of an equivalent in the old Waterfall.
Yeah, if done right. In my experience, such a reimplementation is often lossy, if tests don’t enforce presence of all features and nonfunctional requirements. Maybe the primary value of the early versions is building up the test system, allowing an ideal implementation with that in place.
Or put this way: We’re brute forcing (nicer term: evolutionizing) the codebase to have a better structure. Evolutionary pressure (tests) needs to exist, so things move in a better direction.
What matters ultimately is the system achieves your goals. The clearer you can be about that the less the implementation detail actually matters.
For example; do you care if the UI has a purple theme or a blue one? Or if it's React or Vur. If you do that's part of your goals, if not it doesn't entirely matter if V1 is Blue and React, but V4 ends up Purple and Vue.
AI makes it cheap to implement complex first drafts and iterations.
I'm building a CRM system for my business; first time it took about 2 weeks to get a working prototype. V4 from scratch took about 5 hours.