Jean-Pol Martin's Master Prompt: A Semantic Framework for Human-AI Collaboration
This working paper examines Jean-Pol Martin's Master Prompt as a theoretical and practical framework for human-AI collaboration. It argues that effective prompts are not merely technical instructions but semantic and normative infrastructures that guide AI analysis. Drawing on Martin's semantic field — including Learning by Teaching, New Human Rights, basic needs, thinking, coherence, flow, participation, meaning, and life preservation — the paper demonstrates how prompt architecture can structure AI interaction to support human agency, systemic analysis, and constructive action.
Key quotes
This working paper examines Jean-Pol Martin's Master Prompt as a theoretical and practical framework for human-AI collaboration.
It argues that a good prompt is not merely a technical instruction, but a semantic and normative infrastructure that guides AI analysis.
The paper shows how prompt architecture can structure AI interaction in ways that support human agency, systemic analysis, and constructive action.
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