Build a startup financial model
A driver-based 3–5 year model (revenue, costs, hiring, cash, runway) laid out so you can build it in a spreadsheet.
This is a practical, copy-paste process for preparing to fundraise.. Use it when you want a clear structure, then add your own details and the linked evidence.
Published by Deepstory Research. Reviewed Sep 2026.
How to use this method
- 1. Copy or downloadCopy the prompt below, or download the method file and attach it to your chat.
- 2. Paste into any AIChatGPT, Claude, Gemini or Copilot. Replace each [PLACEHOLDER] with your details, or let the AI ask you.
- 3. Add evidenceAttach the evidence files listed on this page so the AI works from sourced numbers, not guesses.
The prompt
Paste it as-is. The AI will ask for anything still in [BRACKETS].
# Build a startup financial model Method by Deepstory Research: deepstoryresearch.com/method/startup-financial-model You are a startup CFO who has built models for seed to Series B rounds. Follow the method below step by step. Goal: A driver-based 3–5 year model (revenue, costs, hiring, cash, runway) laid out so you can build it in a spreadsheet. ## My inputs - Business model: [BUSINESS_MODEL] (example: B2B SaaS, monthly subscriptions) - Current numbers: [CURRENT_NUMBERS] (example: MRR, customers, burn) - Funding plan: [FUNDING_PLAN] (example: raise $1.5M in 6 months) - Hiring plan: [HIRING_PLAN] (example: known roles) Before you start: if any input above is still in [BRACKETS] or missing, ask me for it in one short numbered list and wait. Do not guess. If I attached files (data, briefs, Deepstory evidence files), treat them as the primary source. ## Steps to follow 1. List the revenue drivers (e.g. leads → conversion → customers → ARPA → churn). 2. List cost drivers: headcount by role, COGS, marketing, overhead. 3. Lay out monthly assumptions for year 1 and annual for years 2–5. 4. Produce P&L, cash flow and runway. 5. Add base, upside and downside cases. 6. Give spreadsheet structure: tabs, rows and formulas. ## Deliver the output in this structure - Driver tree - Assumptions sheet - Revenue build - Headcount plan - P&L and cash flow summary - Runway and funding need - Scenario comparison - Spreadsheet layout & formulas ## Quality rules - Every output traces to an assumption cell. - Churn and ramp times must be realistic; cite benchmarks or label assumptions. - Label every number as FACT (with source and date), ESTIMATE (show the calculation) or ASSUMPTION. - If a Deepstory evidence file is attached, use its figures as the reference values and cite its source references; tag claims that are not from it as [UNVERIFIED]. - End with: the 3 assumptions that matter most, what would change the answer, and the single best next step.
What you need to give the AI
| Input | Placeholder | Example |
|---|---|---|
| Business model | [BUSINESS_MODEL] | B2B SaaS, monthly subscriptions |
| Current numbers | [CURRENT_NUMBERS] | MRR, customers, burn |
| Funding plan | [FUNDING_PLAN] | raise $1.5M in 6 months |
| Hiring plan | [HIRING_PLAN] | known roles |
Use it when
- Preparing to fundraise.
- Deciding how many people you can hire.
Best with: An AI tool that can create spreadsheets (e.g. with code or file output), or paste the layout into Excel/Sheets.
What you get
- Driver tree
- Assumptions sheet
- Revenue build
- Headcount plan
- P&L and cash flow summary
- Runway and funding need
- Scenario comparison
- Spreadsheet layout & formulas
The procedure, step by step
Read this before you run it, so you can check the AI actually followed the method.
List the revenue drivers (e.g. leads → conversion → customers → ARPA → churn).
List cost drivers: headcount by role, COGS, marketing, overhead.
Lay out monthly assumptions for year 1 and annual for years 2–5.
Produce P&L, cash flow and runway.
Add base, upside and downside cases.
Give spreadsheet structure: tabs, rows and formulas.
Quality checks built into the prompt
- • Every output traces to an assumption cell.
- • Churn and ramp times must be realistic; cite benchmarks or label assumptions.
- • Every number labelled FACT, ESTIMATE or ASSUMPTION; claims outside attached evidence tagged [UNVERIFIED].
Evidence to use with this method
Methods tell the AI how to think. Evidence gives it sourced numbers to think with. Download a context file and attach it with the prompt.
Six-Economy Macro Baseline
A common-country, common-period baseline for real growth, inflation, modeled unemployment and trade exposure across the United States, China, India, Germany, the United Kingdom and Japan.
US Inflation & the Fed
The full 2026 inflation story on one page: the CPI path and category breakdown, the mid-year turn and the still-rising core PCE outlook, and the Fed’s rate response — fed funds, the 10-year Treasury, and the 30-year mortgage.
Private Credit: A $1.2 Trillion Disagreement
Estimates of global private credit AUM differ by more than a trillion dollars. This index shows the spread rather than picking a number.
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Deepstory methods are process guidance for AI tools. Review AI output before relying on it; legal, tax, medical and investment decisions need a qualified professional.