The primary reason is because what you are rapidly refactoring in these early prototypes/revisions are the meta structure and the contacts.
Before AI the cost of putting tests on from the beginning or TTD slowed your iteration speed dramatically.
In the early prototypes what you are figuring out is the actual shape of the problem and what the best division of responsibilities and how to fit them together to fit the vision for how the code will be required to evolve.
Now with AI, you can let the AI build test harnesses at little velocity cost, but TDD is still not the general approach.
Like any framework they all have costs,benefits, and places they work and others that they don’t.
Unless taking time to figure out what your inputs and expected outputs, the schools of thought that targeted writing all tests and even implement detail tests I would agree with you.
If you focus on writing inputs vs outputs, especially during a spike, I need to take prompt engineering classes from you
Maybe I am more of a Leet coder than I think?