This can sometimes be fixed with a few-shot example for in-context-learning. But you are right that the model can go off the rails if it is being forced too fa

This can sometimes be fixed with a few-shot example for in-context-learning. But you are right that the model can go off the rails if it is being forced too far from where its 'happy place' is, especially for smaller models.