That's a theory but I've never seen this work in practice. A piece of software is unique. If it weren't, we'd just use the cp command.
What usually happens is you get a set of requirements that looks simple. Then you start thinking about a design and see 10 different possibilities, each corresponding to a slightly different interpretation of the requirements set. You iterate a few times reviewing the designs with who set the requirements and a few peers and see more possible variations to the requirements. You need to double check its parent requirements up to the master requirements. Then you need to take time/feature/quality tradeoffs, affecting the fulfillment of requirements.
Once starting to implement, you see dependencies to other software (framework, sdk, drivers, language features,...) and understand that other software is not what you thought, or has bugs. Or you see an issue with performance or see that one particular feature becomes unfeasible.
That's where all the complexity goes. AI doesn't change that, but can make prototyping iterations and bug hunting faster, as long as someone holds it on a leash and understands its decisions.
It has to be someone's job to push back on the Product Guy's stupid idea and answer all the awkward questions about the not-so-happy path with it. Unfortunately, because of the way we've ended up with this process, that person is often the engineer tasked with building it, without any effective political power to challenge the design process.
My senior year software engineering class had a whole section on requirements gathering.