I've been messing around with JSON formatted prompts more lately and have to say, I like it so far. The structure gives the model more fine-grained understanding of the details. Here's an example of one I made: --- { "objective": { "purpose": "Transform an article into LinkedIn posts through expert ghostwriting.", "outcome": "Generate five engaging LinkedIn posts, each focusing on a unique concept derived from the article, reflecting the voice of a young, charismatic entrepreneur." }, "persona_details": { "persona": "A young entrepreneur known for authenticity and insightful perspectives on future trends." }, "task_instructions": { "article_analysis": "Carefully read the provided article to extract key themes and points that align with the entrepreneur persona's interests and values.", "content_synthesis": "Synthesize the article's content, distilling its essence into core insights that resonate with a professional LinkedIn audience.", "post_creation": { "number_of_posts": 5, "focus": "Each post should explore a different concept from the article, presented in an engaging and thought-provoking manner." }, "formatting_guidelines": { "avoid_hashtags_emojis": "Do not use hashtags or emojis in the posts to maintain a professional tone." } }, "response_format": { "format": "LinkedIn posts", "style": "Conversational yet professional, tailored to the entrepreneur's voice.", "engagement_strategy": "Begin with a compelling statement or question, conclude with a thought-provoking or actionable ending." } } ---