I was thinking exactly the same as I read the OP, right where the dad+kid were answering hypothetical ChatGPT questions with Yes and No. I think LLMs inference

I was thinking exactly the same as I read the OP, right where the dad+kid were answering hypothetical ChatGPT questions with Yes and No. I think LLMs inference training should include teaching it to ask questions back before starting full-fledged generation. You know, make it a little more Socratic. Right now the approach is: ChatGPT starts answering and, if it's going the wrong way, you either hit "Stop Generating" or just wait for it to finish then figure yourself how to improve the prompt. LLMs should be also trained in ranking the prompt and determining what questions would make the prompt statistically stronger to generate. I bet it would result in savings running it too. In fact, one can try this out by configuring a system prompt that tells the model to ask questions before getting started with an answer.