1. What to replace:
Replace each {{placeholder}} with your startup name, one-sentence elevator pitch, target market, traction numbers, moat, and fundraising goal.
2. How to customize variables:
- startup_name: Works for SaaS, DeepTech, BioTech, Consumer, or Hardware.
- target_market: Be specific about your beachhead customer segment.
- pain_point_and_market_failure: Frame the pain as a burning operational or financial emergency.
- secret_sauce_and_moat: Articulate why incumbents cannot easily clone you.
- traction_metrics: Include real customer counts, revenue, pilots, or waitlists.
- fundraising_target: Specify check size and runway (e.g., $2M Seed for 18 months).
3. Compatible AI Tools:
ChatGPT (GPT-4o), Claude 3.5 Sonnet, Gemini 1.5 Pro.
4. Expected Result:
A slide-by-slide narrative blueprint ready to design in Pitch, Figma, or PowerPoint that commands investor respect and passes partner meetings.
Act as a seasoned Venture Capitalist and Seed/Series A Pitch Coach who has evaluated thousands of startup pitches. Design a compelling, fundable 12-slide Pitch Deck Narrative Blueprint for a startup raising {{fundraising_target}} for {{startup_name}}.
Startup Fundamentals:
- Startup Name & One-Liner: {{startup_name}} — {{startup_one_liner}}
- Target Market & Customer Segment: {{target_market}}
- Core Problem / Status Quo Pain: {{pain_point_and_market_failure}}
- Proprietary Solution & Unfair Advantage: {{secret_sauce_and_moat}}
- Current Traction & Proof of Velocity: {{traction_metrics}}
- Fundraising Goal & Milestones to Unlock: {{fundraising_target}} to achieve {{milestones_with_capital}}
The 12-Slide Pitch Deck Architecture:
For each of the 12 core slides below, provide:
- Slide Title & The One Core Takeaway (What must linger in the VC's mind after 3 seconds).
- Visual Layout & Information Hierarchy (Exact layout of graphs, diagrams, and callout metrics).
- Script / Bullet Points (The precise, punchy narrative copy for the slide).
- Critical VC Objection & Defense (The cynical question an investor will ask and how this slide pre-empts it).
Slide Sequence:
1. The Vision & One-Liner (Category definition)
2. The Problem / Market Failure (Why now? The bleeding neck problem)
3. The Status Quo Alternatives (Why legacy solutions fail)
4. The Solution / Product (The 10x better alternative)
5. Market Opportunity (TAM / SAM / SOM bottoms-up sizing)
6. Business Model & Unit Economics (Monetization, pricing tiers, LTV:CAC, payback period)
7. Traction & Velocity (MoM growth, retention cohorts, revenue, waitlists)
8. The Secret Sauce / Competitive Moat (Network effects, data flywheel, switching costs)
9. Go-To-Market Engine (Scalable customer acquisition channels)
10. Competitive Landscape (2x2 Matrix showing true differentiation, not a biased checklist)
11. The Founding Team (Unfair founder-market fit, pedigree, domain mastery)
12. The Ask & Milestones (Capital sought, runway, and exact inflection metrics unlocked)
Customize this prompt (fill variables)
How to use this prompt
Example: what to expect
Example input
startup_name: FleetCharge
startup_one_liner: Dynamic EV fleet depot charging optimization software that cuts commercial utility demand charges by 40%
target_market: Commercial delivery fleet operators (last-mile logistics, transit buses)
pain_point_and_market_failure: Fleet electrification spikes peak demand electricity charges, turning EV cost savings into massive operational losses
secret_sauce_and_moat: Real-time predictive utility tariff scheduling algorithm with bi-directional hardware integration across 95% of commercial chargers
traction_metrics: 8 commercial depots live, 420 vehicles managed, $240k ARR with 100% net revenue retention
fundraising_target: Raising $2.5M Seed Round
milestones_with_capital: Expand to 50 depots, integrate 3 major utility API protocols, and hit $1.2M ARR in 18 months
Example output
A complete 12-slide slide-by-slide blueprint mapping out FleetCharge's narrative. Slide 2 dramatizes the "Utility Demand Charge Trap" with a real customer electricity bill. Slide 6 details the 85% gross margin SaaS + energy savings rev-share model. Slide 10 structures an honest competitive matrix contrasting static schedulers vs real-time dynamic hardware optimization. Completes with an investor FAQ addressing hardware dependency risks.
Variables explained
| Variable | What to enter |
|---|---|
{{startup_name}} |
Enter company name. |
{{startup_one_liner}} |
One crisp sentence explaining what you do. |
{{target_market}} |
Identify your core buyer. |
{{pain_point_and_market_failure}} |
State the acute market pain. |
{{secret_sauce_and_moat}} |
Your proprietary advantage. |
{{traction_metrics}} |
List revenue, growth, or pilot metrics. |
{{fundraising_target}} |
State round size ($1.5M Pre-Seed, $3M Seed, $10M Series A). |
{{milestones_with_capital}} |
What concrete milestones will this round achieve? |
Tips for better results
Best used for: Startup fundraising and investor pitch decks
- Give the AI context first: who you are, who the audience is, and what “good” looks like for you.
- Ask for output in a specific format (bullets, table, markdown) when you need structure.
- If the result is close but not perfect, reply with “keep the structure, make it more…” — do not start over.
- For long tasks, split the prompt into steps instead of expecting one giant answer.
- Different tools behave differently — ChatGPT, Claude and Gemini each have their own style. Try this prompt on the tool you use most.
How to use this Startup prompt effectively
What this prompt does
Structure an investor-ready 12-slide venture capital pitch deck narrative with undeniable problem validation, traction metrics, and fundable unit economics.
Getting the most out of it
- Copy the prompt and paste it into your AI tool of choice (ChatGPT, Claude or Gemini).
- Fill the variables in curly brackets with your own topic, audience and tone — the customize button above builds a ready version for you.
- Review the first draft for facts and style before using it. AI output is a starting point, not a final product.
- Iterate: tell the AI what to keep and what to change. Small corrections beat re-typing the whole prompt.
Common mistakes to avoid
- Leaving the {{variables}} unfilled — the AI then guesses your topic.
- Expecting one output to be perfect — plan for 2–3 rounds of refinement.
- Pasting confidential information into public AI tools.