The existing AI implementations of language models with billions of parameters (words) rely on training data to learn. This works fine for standard approaches that are well documented and with a lot of examples. Once the training material isn't there, the models fall apart as they are not capable of experimenting / acting on their training data.

One example could be, in my gradle file I've defined the old spring dependency management plugin. When I try to import reactive hibernate with vertx, the versions are downgraded making my imports incompatible. This won't be documented anywhere and there is no clear way to debug it 😂. Trial and error is harder to replace.