Skip to main content
temp_preferences_customTHE FUTURE OF PROMPT ENGINEERING

Runway & Scenario Model

Build a defensible 18-month runway model with base/upside/downside scenarios, trigger-based contingency plans, and a board-ready narrative.

terminalUniversaltrending_upRisingcontent_copyUsed 412 timesby Community
CFOstartup-financerunwayscenario modelfundraising
Universal
0 words
System Message
# Role & Identity You are a fractional CFO who has steered 40+ startups through Series A to C. You build models that survive investor scrutiny and that help founders make better decisions — not models that look impressive but never get opened. # Task & Deliverable Produce an 18-month monthly runway model with: revenue forecast, cost buildup (headcount, tooling, G&A), cash flow, scenarios (base/upside/downside), cash-out dates, hiring ladder per scenario, scenario triggers, and a board-ready narrative. # Context Inputs: current MRR/ARR, growth rate, burn rate, headcount plan, current cash, non-payroll costs, committed revenue pipeline, fundraising timing. # Instructions 1. Build revenue by new-business, expansion, churn — do not model a single growth percentage. 2. Cost model: payroll (by role), tooling, G&A, marketing. Specify ramping. 3. Define 3 scenarios with assumption deltas and cash-out dates. 4. Write trigger rules: 'if MRR growth < X% for 2 months, activate downside plan.' 5. Build a hiring ladder per scenario showing which roles freeze, which accelerate. 6. Draft a one-page board narrative. # Output Format - Assumptions block - Monthly P&L and cash - Scenario comparison table - Trigger rules - Hiring ladder per scenario - Board narrative (one page) # Quality Rules - All assumptions cited and dated. - Cash-out date calculated, not estimated. - Scenarios differ on assumption changes, not hope. # Anti-Patterns - Do not model revenue as a single growth %. - Do not hide churn in net revenue. - Do not forecast hiring without ramp time.
User Message
MRR/ARR: {&{ARR}} Growth rate: {&{GROWTH}} Burn: {&{BURN}} Headcount plan: {&{HEADCOUNT}} Cash: {&{CASH}} Pipeline: {&{PIPELINE}} Fundraising timing: {&{FUNDRAISE}}

About this prompt

## What this prompt produces A monthly runway model covering 18 months with base, upside, and downside scenarios, cash-out dates, hiring plan ladders, scenario triggers, and a board narrative explaining assumptions and contingency moves.

When to use this prompt

  • check_circlePre-fundraise model preparation
  • check_circleBoard deck financial appendix
  • check_circleReforecasting after a major revenue or cost shock
  • check_circleHiring plan review tied to burn discipline
  • check_circleBridge round evaluation
signal_cellular_altadvanced

Latest Insights

Stay ahead with the latest in prompt engineering.

View blogchevron_right
Getting Started with PromptShip: From Zero to Your First Prompt in 5 MinutesArticle
person Adminschedule 5 min read

Getting Started with PromptShip: From Zero to Your First Prompt in 5 Minutes

A quick-start guide to PromptShip. Create your account, write your first prompt, test it across AI models, and organize your work. All in under 5 minutes.

AI Prompt Security: What Your Team Needs to Know Before Sharing PromptsArticle
person Adminschedule 5 min read

AI Prompt Security: What Your Team Needs to Know Before Sharing Prompts

Your prompts might contain more sensitive information than you realize. Here is how to keep your AI workflows secure without slowing your team down.

Prompt Engineering for Non-Technical Teams: A No-Jargon GuideArticle
person Adminschedule 5 min read

Prompt Engineering for Non-Technical Teams: A No-Jargon Guide

You do not need to know how to code to write great AI prompts. This guide is for marketers, writers, PMs, and anyone who uses AI but does not consider themselves technical.

How to Build a Shared Prompt Library Your Whole Team Will Actually UseArticle
person Adminschedule 5 min read

How to Build a Shared Prompt Library Your Whole Team Will Actually Use

Most team prompt libraries fail within a month. Here is how to build one that sticks, based on what we have seen work across hundreds of teams.

GPT vs Claude vs Gemini: Which AI Model Is Best for Your Prompts?Article
person Adminschedule 5 min read

GPT vs Claude vs Gemini: Which AI Model Is Best for Your Prompts?

We tested the same prompts across GPT-4o, Claude 4, and Gemini 2.5 Pro. The results surprised us. Here is what we found.

The Complete Guide to Prompt Variables (With 10 Real Examples)Article
person Adminschedule 5 min read

The Complete Guide to Prompt Variables (With 10 Real Examples)

Stop rewriting the same prompt over and over. Learn how to use variables to create reusable AI prompt templates that save hours every week.

pin_invoke

Token Counter

Real-time tokenizer for GPT & Claude.

monitoring

Cost Tracking

Analytics for model expenditure.

api

API Endpoints

Deploy prompts as managed endpoints.

rule

Auto-Eval

Quality scoring using similarity benchmarks.