Overview
This prompt aims to critically assess a startup idea by identifying potential failure points through a “Pre-Mortem” analysis. Entrepreneurs and investors will benefit from this rigorous evaluation to strengthen their business strategies and reduce risks.
Prompt Overview
Purpose: This analysis identifies critical failure points for your startup idea to prevent future pitfalls.
Audience: Targeting entrepreneurs and investors seeking insights into potential risks in early-stage ventures.
Distinctive Feature: The focus on a “Pre-Mortem” approach allows for proactive risk management before launch.
Outcome: By addressing these flaws, you can refine your strategy and increase your chances of success.
Quick Specs
- Media: Text
- Use case: Analysis, Comparison & Evaluation, Content Strategy
- Industry: Investment Banking, Venture Capital & Private Equity, Warehousing & Distribution
- Techniques: Decomposition, Role/Persona Prompting, Self-Critique / Reflection
- Models: Claude 3.5 Sonnet, Gemini 2.0 Flash, GPT-4o, Llama 3.1 70B
- Estimated time: 10-20 minutes
- Skill level: Intermediate
Variables to Fill
- [INPUT: Industry/Sector, e.g., EdTech] – Input: Industry/sector, E.g., Edtech
Example Variables Block
- [INPUT: Industry/Sector, e.g., EdTech]: Example Input: Industry/sector, E.g., Edtech
The Prompt
# Role
Act as a skeptical Venture Capitalist and Product Strategist with 20+ years of experience analyzing early-stage startups. You have seen thousands of companies fail and understand the subtle patterns that lead to failure?including hidden unit economic flaws, false market signals, and operational bottlenecks.
# Task
Perform a “Pre-Mortem” analysis on my startup idea. Instead of validating why it will succeed, I want you to assume that 2 years from now, this startup has FAILED completely. Your task is to work backward to identify the specific “Fatal Flaws” that caused this failure.
# Context
I am building a startup in the [INPUT: Industry/Sector, e.g., EdTech] space.
My core idea is: [INPUT: Short description of idea, e.g., A platform that connects retired teachers with students for on-demand tutoring via video chat].
My target audience is: [INPUT: Target Audience, e.g., High school students preparing for SATs].
My proposed monetization model is: [INPUT: Revenue Model, e.g., Subscription of $20/month].
# Output Instructions
Analyze the idea and provide a report covering these 5 critical failure categories. Be brutally honest, direct, and critical. Do not sugarcoat.
1. Market False Positives: Why might the “demand” I think exists actually be a mirage? (e.g., nice-to-have vs. need-to-have).
2. Unit Economics Collapse: Analyze the math. Where will the Customer Acquisition Cost (CAC) likely exceed Lifetime Value (LTV)? What hidden costs am I ignoring?
3. Distribution Bottlenecks: Assume nobody signs up. What is the specific friction point in my go-to-market strategy that blocked growth?
4. The “Why Now” Trap: Why might this be the wrong timing? (Too early? Too late? Technology not ready?)
5. Operational fragility: What is the single hardest operational piece to scale that will break when volume increases?
# Formatting
– Use bullet points for clarity.
– For each point, provide a “Mitigation Tactic” (a specific 1-sentence strategic fix).
– End with a “Risk Score” (0-10) where 10 is “Extremely Risky/High Probability of Failure.”
Screenshot Examples
How to Use This Prompt
- Market False Positives: Demand may be overstated or niche.
- Unit Economics Collapse: CAC could surpass LTV significantly.
- Distribution Bottlenecks: High friction in user acquisition channels.
- The “Why Now” Trap: Market may be saturated or timing off.
- Operational Fragility: Scaling tutoring quality may become unmanageable.
Tips for Best Results
- Market False Positives: The demand for on-demand tutoring may be overstated, as many students prefer in-person interactions or free resources. Mitigation Tactic: Conduct thorough market research to validate the necessity of your service versus existing alternatives.
- Unit Economics Collapse: Customer Acquisition Cost (CAC) could exceed Lifetime Value (LTV) if marketing expenses are high and retention rates are low due to competition. Mitigation Tactic: Implement a robust retention strategy and calculate realistic CAC and LTV metrics before launch.
- Distribution Bottlenecks: Friction in your go-to-market strategy may arise from ineffective partnerships with schools or low brand recognition. Mitigation Tactic: Develop strategic partnerships with educational institutions to enhance credibility and visibility.
- Operational Fragility: Scaling the platform may be hindered by the difficulty of maintaining quality control over a large pool of tutors. Mitigation Tactic: Establish a rigorous vetting and training process for tutors to ensure consistent quality as you grow.
FAQ
- What if the demand for my tutoring platform is overstated?
The demand may be a mirage if students prefer free resources or in-person tutoring. Mitigation Tactic: Conduct thorough market research to validate demand before launching. Risk Score: 7 - How can my unit economics fail?
Customer Acquisition Cost (CAC) may exceed Lifetime Value (LTV) due to high marketing expenses. Mitigation Tactic: Create a detailed financial model to analyze CAC and LTV early on. Risk Score: 8 - What distribution challenges could hinder growth?
Potential friction points include ineffective marketing channels or poor user experience. Mitigation Tactic: Test multiple marketing channels and optimize user onboarding processes. Risk Score: 6 - Is this the wrong time to launch my startup?
The market may be saturated with similar services or technology may not support your idea yet. Mitigation Tactic: Stay updated on industry trends and adjust your launch timeline accordingly. Risk Score: 7 - What operational issues could arise as I scale?
Scaling the quality of tutoring could be challenging, leading to inconsistent user experiences. Mitigation Tactic: Develop a robust training program for tutors to maintain quality as you grow. Risk Score: 8
Compliance and Best Practices
- Best Practice: Review AI output for accuracy and relevance before use.
- Privacy: Avoid sharing personal, financial, or confidential data in prompts.
- Platform Policy: Your use of AI tools must comply with their terms and your local laws.
Revision History
- Version 1.0 (December 2025): Initial release.
