> if they are correct I see no issue at all.
Indeed. Are you verifying that they are correct, or are you glancing at the output and seeing something that seems plausible enough and then not really scrutinizing? Because the latter is how LLMs often propagate errors: through humans choosing to trust the fancy predictive text engine, abdicating their own responsibility in the process.
As a consumer of an API, I would much rather have static types and nothing else than incorrect LLM-generated prosaic documentation.
Can you provide examples in the wild of LLMs creating bad descriptions of code? Has it ever happened to you?
Somehow I doubt at this point in time they can even fail at something so simple.
Like at some point, for some stuff we have to trust LLMs to be correct 99% of the time. I believe summaries, translate, code docs are in that category