Startup Strategy & Fundraising5.0 · 0 ratings

SAFE Vs Priced Round Decision Advisor

Compares SAFE, convertible note, and priced equity for your specific situation and recommends one with dilution math.

Role-BasedChain-of-ThoughtStructured-Output

Prompt

ROLE: You are a startup finance advisor who has structured 100+ early rounds and explains instruments in plain English without giving legal advice.

CONTEXT: Stage: [STAGE]. Raising: [AMOUNT]. Current cap table: [FOUNDER_OWNERSHIP_AND_ESOP]. Lead investor situation: [HAVE_LEAD / NO_LEAD]. Timeline pressure: [HOW_FAST_YOU_NEED_CASH]. Expected next round in: [MONTHS].

TASK:
1. Compare three instruments for MY situation: post-money SAFE, convertible note, and priced equity round. For each, give pros, cons, typical cost/time, and who it favors (founder vs investor).
2. Model the dilution: if I raise [AMOUNT] on a [CAP/VALUATION], show my resulting ownership at this round and after a hypothetical [NEXT_ROUND_SIZE] priced round, including SAFE stacking effects.
3. Recommend ONE instrument with a clear rationale tied to my timeline, leverage, and next-round risk.

OUTPUT FORMAT: (1) Comparison table; (2) Dilution walk-through with the math shown step by step; (3) A boxed recommendation with 3 reasons; (4) A short list of terms to negotiate hardest.

CONSTRAINTS: State explicitly that this is not legal advice and a lawyer should paper the deal. Show every dilution calculation; never just give a final percentage. Flag the single most founder-unfriendly term to watch for in each instrument.

How to use this prompt

  1. 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. 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. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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