> Langchain uses this prompt: "The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details fro

> Langchain uses this prompt: "The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know." There seem to be a lot of cases where people claim the models can't do something, but with minimal direction, they can. Like avoiding bias. Or doing long digit math carefully, instead of guessing, etc. I don't know a human that doesn't need any feedback either. Obviously, many of these things would be better handled in the learning stage, so bias avoidance, careful serial thought processes, etc., were its baseline thinking. When that happens I would expect fewer mistakes, but also an overall increase in the quality of responses, and ability to handle greater complexity. Clear careful thinking reduces error in each step, making longer chains of reasoning more viable.