GPT "MetaPrompt"

🚀 Self-Improving Meta Prompt:  1. Identify the Challenge: Clearly state the need for a prompt that evolves with continuous feedback and self-improvement.   2. Integrate TDD Principles: Specify that tests (including edge cases) must be defined before constructing the prompt. This ensures that every element is verifiable from the start.   3. Differentiate Thinking Systems: Instruct the AI to generate initial, intuitive ideas (system 1) and then validate those ideas with rigorous, methodical analysis (system 2).   4. Plan Iterative Refinement: Detail a process for repeated testing, gathering feedback, and refining the prompt over multiple cycles until optimal performance is achieved.   5. Include Root Cause Analysis & Kanban: Require that the prompt incorporates instructions for performing a root cause analysis (using methods like the 4 Whys) and for tracking progress using a Kanban board (with columns such as "todo", "doing", and "done").   6. Consolidate into a Final Template: Merge all of the above steps into one cohesive meta prompt template that can be directly used and further refined as needed.    

💡 Technical Documentation Meta Prompt:  1. Define the Objective: Clearly state that the meta prompt is intended to guide the creation of detailed technical documentation instructions. Emphasize the need for comprehensive coverage of all technical aspects.   2. List Key Technical Requirements: Enumerate all essential technical details, specifications, and edge cases that must be addressed. Ensure that the prompt covers every necessary detail for robust documentation.   3. Apply TDD Principles: Specify that tests (including edge cases) must be outlined for each technical requirement. This guarantees that every part of the documentation is verifiable and maintains quality.   4. Use Structured Analysis (4 Whys): Instruct the AI to employ the 4 Whys method to uncover any hidden ambiguities or gaps. Each "Why?" should dig deeper into the reasons behind the technical requirements, exposing potential issues.   5. Plan for Iterative Feedback: Describe a process for gathering feedback and refining the meta prompt. Ensure that the prompt is designed for iterative improvement based on test outcomes and user input.   6. Merge into a Coherent Template: Combine all the above steps into one unified meta prompt template that clearly guides the generation of technical documentation prompts.     

🤔 4 Whys Analysis Meta Prompt:  1. State the Initial Problem: Begin with a clear, superficial description of a prompt design challenge that needs addressing.   2. Ask the First "Why?": Instruct the AI to question why this initial problem exists, capturing the immediate reason behind it.   3. Ask the Second "Why?": Delve deeper by asking why the reason identified in the first "Why?" is occurring, uncovering further layers.   4. Continue with Two More "Whys": Repeat the process two additional times (for a total of four "Why?" questions) to expose deeper, underlying causes.   5. Link Each Insight to Tests: For every level of insight gained, specify corresponding tests or validation measures that can verify whether the prompt addresses the identified issues.   6. Synthesize into a Final Meta Prompt: Combine all the layers of analysis into a comprehensive meta prompt template that thoroughly addresses the root challenges.    

📋 Kanban Workflow Meta Prompt:  1. Outline the Kanban Framework: Clearly define the visual workflow using a Kanban board with distinct columns labeled "todo", "doing", and "done".   2. Define Tasks for Each Column: Instruct the AI to break down the meta prompt creation process into specific tasks or steps, assigning each to the appropriate column based on its current status.   3. Link Tasks to Test Outcomes: Specify that every task should be associated with clear test outcomes or feedback loops. This ensures that each step is validated and that progress is measurable.   4. Provide Guidelines for Task Transitions: Describe the criteria for moving tasks between columns (e.g., from "todo" to "doing", and from "doing" to "done") based on successful test results and iterative refinements.   5. Plan for Iterative Refinement: Include a process for revisiting and updating tasks as new insights or test failures emerge. Emphasize that the Kanban board is a living document that adapts to continuous feedback.   6. Consolidate into a Comprehensive Template: Merge all of the above instructions into a single, unified meta prompt template that guides the creation of meta prompts using the Kanban approach for systematic, test-driven refinement.