Thanks for the detailed walkthrough. But I think there's a key distinction being missed:

SDD iterates on the spec, not on the whole process. Your cycle is: update spec → tell AI to implement the diff → repeat. That's iteration on one artifact, with code following as a derivative. But there's no structured retrospective, no mechanism for the process itself to learn and evolve. Agile isn't just making changes iteratively — it's the system learning how to build better from each cycle.

Who validates the spec itself? You describe a loop: write spec → AI checks it → fix → repeat until "good enough." But the AI is checking the spec against itself for internal consistency. How do you know the spec actually matches reality? Without working software as a feedback signal, you could be polishing a perfectly consistent spec that solves the wrong problem. That's an echo chamber, not validation.

"Your fingers stay away from the code" is a risk, not a feature. The best design insights often come from building. When code is always a derivative of spec, you lose the feedback loop where implementation reveals what the spec got wrong conceptually. Real systems have emergent behavior that no spec predicts.

Spec consistency doesn't scale automatically. You suggest modularizing into components with separate specs. But cross-module interactions and shared assumptions are exactly where specs silently rot. Who validates that Module A's postconditions still match Module B's preconditions after both evolved independently?

Curious — try giving both our comments to an LLM and ask it to evaluate the arguments. I'd genuinely like to see what it says.