Defining tests that test for the right things requires an understanding of the problem space, just as writing the code yourself in the first place does. It's a catch-22. Using LLMs in that context would be pointless (unless you're writing short-lived one-off garbage on purpose).

I.e. the parent is speaking in the context of learning, not in the context of producing something that appears to work.

I'm not sure that's true. Bombarding code with huge numbers of randomly generated tests can be highly effective, especially if the tests are curated by examining coverage (and perhaps mutation kills) in the original code.