PlaybookPrompts

Build the strategic narrative for a Series A fundraise

Business Strategy fundraisingnarrativeseries-a

Investors fund narratives as much as metrics. This prompt constructs the causal story — market, insight, unfair advantage, and path — that makes your traction feel inevitable rather than lucky.

Prompt 
Help me build the strategic narrative for {{COMPANY_NAME}}'s Series A. Here is our context: {{COMPANY_CONTEXT}} (include current ARR, growth rate, what the product does, and who buys it).

1. Write a 'Why Now' paragraph (4-6 sentences): what structural shift in the market — regulatory, technological, or behavioral — makes this problem more urgent or more solvable today than 5 years ago? Use only facts I've provided; do not invent market trends.
2. Write a 'Secret' paragraph: what non-obvious insight do we have about this market that most investors or competitors have wrong? If I haven't provided one, flag this as a gap and ask me three questions to uncover it.
3. Write a 'Why Us' paragraph: based on {{COMPANY_CONTEXT}}, identify the two or three concrete advantages we have that are hard to replicate — not 'great team' or 'first-mover' generics. Be specific about what the advantage actually is.
4. Write a 'Path to $X' paragraph: given our current ARR and growth rate, project a credible path to the scale that would justify a Series B. State the key bets that must pay off.
5. Identify the single biggest hole in this narrative that a sharp investor will probe. Draft a two-sentence answer we should have ready.

Keep total length under 500 words. This is a narrative structure, not a pitch deck script.
Variables to fill in
  • {{COMPANY_NAME}}
  • {{COMPANY_CONTEXT}}

How to use this prompt

  1. Copy the prompt above (Copy button on the top-right).
  2. Replace each {{VAR}} with your own value. Variables: {{COMPANY_NAME}}{{COMPANY_CONTEXT}}.
  3. Paste it into one of the recommended tools below.
  4. Iterate: tighten constraints in the prompt if the output is generic.

Why this prompt is structured this way

The prompt is split into explicit steps because LLMs do better when the path is named, not implied. Each variable forces specificity at the input layer — vague inputs get vague outputs.

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