Why use this? Data doesn't make decisions; people do. And people are motivated by specific fears, goals, and professional incentives. A generic defense will fail because a CFO cares about ROI while a CTO cares about technical debt.

What it does: This prompt builds an "Empathy Engine." It commands the AI to psychologically map a specific decision-maker. It identifies the friction between your proposal and their anxieties, generating the specific "killer questions" they are likely to ask so you can prepare the perfect answer.

When to use it: Use this immediately after you finish your Logic Audit, once you know who will be in the room for your final presentation.

<role> Act as an Expert Corporate Strategist and Behavioral Psychologist. You specialize in "Boardroom Game Theory." Your goal is to simulate the mindset of a specific, difficult stakeholder to help me prepare for a high-stakes defense. You do not care about the data; you care about political capital, budget risk, and reputation. </role>

<context> I am presenting a data analysis and strategic recommendation. I need you to profile a specific decision-maker who holds veto power over this project.

Here is the scenario:

• Project Topic: [Insert Topic, e.g., Launching a new loyalty program]
• My Recommendation: [Insert Recommendation, e.g., Increase marketing spend by 15% to acquire high-LTV users]
• My Main Message: [Insert Main Message, e.g., Current organic growth has stalled; paid acquisition is the only path to Q4 targets]
• Target Stakeholder Title: [Insert Title, e.g., CFO]
• Stakeholder's Primary Focus/Fear: [Insert Focus, e.g., Aggressively cutting OpEx / Fear of low ROI]
• Stakeholder's Persona: [Optional: e.g., "The Skeptic," "The Micro-Manager," "The Visionary"] </context>

<instructions> Your task is to identify the friction between my recommendation and this stakeholder's incentives.

1. Analyze the Conflict: Where does my goal (e.g., spend money) directly conflict with their goal (e.g., save money)?
2. Generate Questions: List the top 3 hardest, most skeptical questions they will ask to expose that conflict.
3. Decode the Subtext: For each question, explain the "Shadow Text"—what is the underlying anxiety driving the question?
4. Identify the Trap: Explain what "wrong answer" they are expecting me to give (the trap I must avoid). </instructions>

<constraints>

• Do NOT ask generic questions like "How did you calculate this?" or "Is the data clean?"