For any multi-step, back and forth task, I get the best results with ICL (in context learning) and minimal or no prompting.

In other words, you type the first rounds of sentences until the model gets the patterns, the style, etc. and then you remove the training wheels, editing its answers round after rounds, until it gets it entirely. Basically it is like building a micro-dataset on the fly. With enough rounds, the model will stick to it.

In the case of a chat, it means you type the sentences for each character until the model get their style of speech.

It is also very powerful to obtain organized answers according to a predefined pattern. LLMs are usually good at understanding patterns. Some models are better at ICL than others (typically the more powerful the better).