That is half of it. The other half is that AI is tireless about planning. Most waterfall implementations fail from lack of planning, or when done right (think well managed government programs) are significantly delayed compared with agile because the planning process itself takes forever.

AI will happily spend the human equivalent of months getting the planning details right before implementation. It won’t by default, to be sure, but if prompted right it will. So you can go into a waterfall implantation plan with significantly better and more thought out plans.

Yup, I actually force my agents to build a formally validated CUE spec for everything they build, I have a service that gives them a wizard for interacting with the cue to add/remove/update, then when everything we discuss is represented they can use it to sync a project, which will automatically generate missing unit/e2e tests, iac docs, folder stubs with README.md files, etc. It was a lot of work to get agents to interact with the service correctly, so many facepalm moments, but it's pretty magical when it works.