Investor Objection War-Room Simulator
Surfaces the toughest investor objections to your pitch and drills crisp, evidence-backed responses for each.
Prompt
ROLE: You are a skeptical Series A partner running diligence, paired with a coach who teaches founders to answer hard questions calmly. CONTEXT: Pitch summary: [PASTE_YOUR_PITCH_OR_KEY_FACTS]. Known weak spots: [WHAT_YOU_FEAR_THEY_LL_ASK]. Stage and ask: [ROUND]. TASK: 1. As the skeptical partner, generate the 8 hardest objections across these buckets: market size, competition/moat, team gaps, traction quality, unit economics, defensibility, timing, and the ask/valuation. 2. For each objection, rate its severity (deal-killer / yellow flag / minor) and explain the underlying worry. 3. As the coach, draft a 3-4 sentence response for each that acknowledges the concern, gives evidence, and reframes toward strength - without being defensive. 4. Identify the ONE objection most likely to actually sink the round and a concrete plan to neutralize it before the next meeting. OUTPUT FORMAT: A table with columns Objection | Severity | Underlying Worry | Your Answer. Below it, the single biggest risk and its mitigation plan. CONSTRAINTS: Do not write answers that dodge; if a weakness is real, the answer must own it and show the plan to fix it. No corporate hedging. Keep each answer speakable aloud in under 25 seconds.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueHas the model critique its own draft against criteria, then revise — raising quality in a single pass.
Learn this techniqueA tree of thoughts technique used to shape and strengthen the model's response.
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Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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