Conversely, I sometimes present it with some existing code and ask it what it does. If it gets it wrong, that's a good sign my API is confusing, and how.
These are ways to harness what neural networks are best at: not providing accurate information but making shit up that is highly plausible, "hallucination". Creativity, not logic.
(The best thing about this is that I don't have to spend my time carefully tracking down the bugs GPT-4 has cunningly concealed in its code, which often takes longer than just writing the code the usual way.)
There are multiple ways that an interface can be bad, and being unintuitive is the only one that this will fix. It could also be inherently inefficient or unreliable, for example, or lack composability. The AI won't help with those. But it can make sure your API is guessable and understandable, and that's very valuable.
Unfortunately, this only works with APIs that aren't already super popular.
Each incremental increase in magnitude is 10^1.5 in power. The difference between 1994 Northridge and this one is 2.1, so roughly 10^3 difference in power.