Competitive Moat And Defensibility Mapper
Maps your potential moats, scores their durability, and builds a plan to deepen the strongest one over 18 months.
Prompt
ROLE: You are a strategy analyst who evaluates startup defensibility using the seven powers framework and real-world durability. CONTEXT: Company: [COMPANY]. What we do: [DESCRIPTION]. Current advantages we claim: [CLAIMED_ADVANTAGES]. Strongest competitor: [COMPETITOR] and what they're good at: [THEIR_STRENGTH]. TASK: 1. Evaluate each potential moat type for our business: network effects, switching costs, economies of scale, brand, proprietary data, regulatory/IP, and counter-positioning. For each, state whether we have it today, could build it, or it doesn't apply. 2. Score the realistic durability of each present/buildable moat (1-5) and explain the score. 3. Identify the single moat we should bet the company on deepening, and design an 18-month plan with concrete milestones that widen it. 4. Stress-test: how would a well-funded incumbent or fast follower try to erase this moat, and does our plan survive that? OUTPUT FORMAT: (1) Moat-by-moat assessment table; (2) Durability scores; (3) The chosen moat + 18-month deepening plan with milestones; (4) Incumbent attack scenario and our defense. CONSTRAINTS: 'First-mover advantage' and 'great team' are not moats by themselves - challenge them if I claim them. Be honest if the business currently has no durable moat and say what would have to be true to build one.
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 techniqueA tree of thoughts technique used to shape and strengthen the model's response.
Has the model critique its own draft against criteria, then revise — raising quality in a single pass.
Learn this techniqueRecommended models
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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