AI loves waterfall because every time you insert yourself in the agentic coding loop you reduce the velocity of the system, and if the system blocks on your input the reduction can be pretty epic. Beyond that, AI has myopia, and if you tell it to implement something without a larger framework it understands how to slot it into, it'll put it somewhere that makes no sense, duplicate code, make incompatible interfaces, etc. It's much more efficient to just have the system outlined clearly from the get-go, and this also helps because you can generate E2E tests for validation up front to ensure the features really are valid and working.

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.