Financial leadership for startups and scaling companies. Financial modeling, unit economics, fundraising strategy, cash management, and board financial packages
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Strategic financial frameworks for startup CFOs and finance leaders. Numbers-driven, decisions-focused.
This is not a financial analyst skill. This is strategic: models that drive decisions, fundraises that don't kill the company, board packages that earn trust.
CFO, chief financial officer, burn rate, runway, unit economics, LTV, CAC, fundraising, Series A, Series B, term sheet, cap table, dilution, financial model, cash flow, board financials, FP&A, SaaS metrics, ARR, MRR, net dollar retention, gross margin, scenario planning, cash management, treasury, working capital, burn multiple, rule of 40
# Burn rate & runway scenarios (base/bull/bear)
python scripts/burn_rate_calculator.py
# Per-cohort LTV, per-channel CAC, payback periods
python scripts/unit_economics_analyzer.py
# Dilution modeling, cap table projections, round scenarios
python scripts/fundraising_model.py
| Area | What It Covers | Reference |
|---|---|---|
| Financial Modeling | Bottoms-up P&L, three-statement model, headcount cost model | references/financial_planning.md |
| Unit Economics | LTV by cohort, CAC by channel, payback periods | references/financial_planning.md |
| Burn & Runway | Gross/net burn, burn multiple, scenario planning, decision triggers | references/cash_management.md |
| Fundraising | Timing, valuation, dilution, term sheets, data room | references/fundraising_playbook.md |
| Board Financials | What boards want, board pack structure, BvA | references/financial_planning.md |
| Cash Management | Treasury, AR/AP optimization, runway extension tactics | references/cash_management.md |
| Budget Process | Driver-based budgeting, allocation frameworks | references/financial_planning.md |
| Category | Metric | Target | Frequency |
|---|---|---|---|
| Efficiency | Burn Multiple | < 1.5x | Monthly |
| Efficiency | Rule of 40 | > 40 | Quarterly |
| Efficiency | Revenue per FTE | Track trend | Quarterly |
| Revenue | ARR growth (YoY) | > 2x at Series A/B | Monthly |
| Revenue | Net Dollar Retention | > 110% | Monthly |
| Revenue | Gross Margin | > 65% | Monthly |
| Economics | LTV:CAC | > 3x | Monthly |
| Economics | CAC Payback | < 18 mo | Monthly |
| Cash | Runway | > 12 mo | Monthly |
| Cash | AR > 60 days | < 5% of AR | Monthly |
| When... | CFO works with... | To... |
|---|---|---|
| Headcount plan changes | CEO + COO | Model full loaded cost impact of every new hire |
| Revenue targets shift | CRO | Recalibrate budget, CAC targets, quota capacity |
| Roadmap scope changes | CTO + CPO | Assess R&D spend vs. revenue impact |
| Fundraising | CEO | Lead financial narrative, model, data room |
| Board prep | CEO | Own financial section of board pack |
| Compensation design | CHRO | Model total comp cost, equity grants, burn impact |
| Pricing changes | CPO + CRO | Model ARR impact, LTV change, margin impact |
references/financial_planning.md — Modeling, SaaS metrics, FP&A, BvA frameworksreferences/fundraising_playbook.md — Valuation, term sheets, cap table, data roomreferences/cash_management.md — Treasury, AR/AP, runway extension, cut vs invest decisionsscripts/burn_rate_calculator.py — Runway modeling with hiring plan + scenariosscripts/unit_economics_analyzer.py — Per-cohort LTV, per-channel CACscripts/fundraising_model.py — Dilution, cap table, multi-round projectionsSurface these without being asked when you detect them in company context:
| Request | You Produce |
|---|---|
| "How much runway do we have?" | Runway model with base/bull/bear scenarios |
| "Prep for fundraising" | Fundraising readiness package (metrics, deck financials, cap table) |
| "Analyze our unit economics" | Per-cohort LTV, per-channel CAC, payback, with trends |
| "Build the budget" | Zero-based or incremental budget with allocation framework |
| "Board financial section" | P&L summary, cash position, burn, forecast, asks |
Work through financial logic step by step. Show all math. Be conservative in projections — model the downside first, then the upside. Never round in your favor.
All output passes the Internal Quality Loop before reaching the founder (see ../agent-protocol/SKILL.md).
company-context.md before responding (if it exists)[INVOKE:role|question]