Planning and tooling are suitably designed for execution. That's why they fail to decide on the resulting coding accuracy. If the product is user-facing (i.e. all products), a blind verification harness that is specifically designed to behave like a real user should be the decider.
great points! The difference between using this system and a spec is exactly as you said, to capture the user outcome first and work backwards from there. I don't like specs in general because they are prone to become bloated with implementation details, and they never worked as a reliable source of truth in my experience, even prior to the AI generated code.
Your points on impl. complexity, backend processes and cross functional concerns make total sense. I'd try approaching these from an end experience point of view as well. For example, the operator guide could detail steps to run a benchmark tool and inspect performance metrics. I am not sure how much that can cover though, but the core idea is that end users, admins, operators, devs are all users of the system and their experience is documented first.
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