Yea, a bit like a cheating student rote memorizing and copying another students technique for solving a type of problem, and failing hard as soon as there's too much variation from the original problem.
That said the input space of supported problems is quite large and you can configure the problem parametrs quite flexibly.
I guess the issue is that what the model _actually_ provides you is this idiot savant who has pre-memorized everything without offering a clear index that would disambiguate well-supported problems from ”too difficult” (i.e. novel) ones
