Try to increase the complexity of the work you're doing. It's not that AIs don't makes mistakes but they are able to pattern match to larger and larger pieces of the problem as more people use it and more iterations of the model are released. So your challenge is now in steering it in a way that these errors are minimised while reducing bloat.

Try to think of yourself as a professor who's trying to come up with a problem statement worth solving. The AI is your "lab" that will help you run experiments.