{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/68966959a914492db08e8f0e82c578ca\" frameborder=\"0\" width=\"1152\" height=\"864\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":864,"width":1152,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":864,"thumbnail_width":1152,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/68966959a914492db08e8f0e82c578ca-1687432572078.gif","duration":774.319,"title":"Prompts and completions: how to structure your AI's knowledge base 🤖","description":"Hey there! In this video, I'm going to talk about prompts and completions, which are essentially the dialogue that your AI will have with its clients. I'll explain how to provide training data to your AI so that it can use your data instead of generalized knowledge from the internet. We'll also discuss how many prompts and completions you need, depending on whether you're coaching or mentoring and how niche your areas of expertise are. I'll use a tree analogy to explain how to structure your prompts and completions, starting with the trunk (fundamentals) and branching out into areas of expertise. Finally, I'll share some tips on how to improve your AI's learning through defined tuning and feedback."}