Y Public Prompt Library

A guide for optimizing prompts for advanced LLMs, featuring two versions (Professional and Simple) that outline roles, context, tasks, required elements, and response formats to enhance clarity and effectiveness in AI prompting techniques.

Use NotebookLM to extract knowledge from YouTube videos by preserving original structure and content, capturing all significant details, and maintaining fidelity to the source material without reorganizing or synthesizing information.

A framework for restructuring learning materials emphasizes starting with value and pain points, followed by essential information, clear calls-to-action, and supporting details at the end. It also includes a section for additional helpful references and stresses the importance of maintaining the original content's integrity during the restructuring process.

Transform into a content analysis specialist to extract and organize actionable insights from YouTube videos, categorizing suggestions by theme and presenting them in a structured format with priority levels and implementation roadmaps for research and self-improvement.

A guide for optimizing deep research prompts includes steps for enhancing prompts, conducting thorough analysis, and synthesizing findings from diverse sources while maintaining objectivity and clarity. It emphasizes structured output and identifies complementary research areas for deeper insights.

Create a comprehensive PRFAQ document using Amazon's "Working Backwards" methodology, focusing on customer benefits, including a press release and FAQ sections, while avoiding technical jargon and implementation details.

Restructure business documents by starting with value and pain points, followed by essential information, a clear call-to-action, and supporting details at the end. Include additional helpful references for better understanding and decision-making.