Mvp Launcher

MVP Launcher

Framework for rapid MVP validation and launch using proven startup methodologies from Y Combinator, lean startup, and first-principles thinking.

Core Workflow

1. Problem-Solution Validation

Ask the forcing questions:

• What specific problem are you solving? (Not a solution in disguise)
• Who has this problem urgently enough to pay?
• How are they solving it now? (Current alternatives = market validation)
• Why will they switch to your solution?

Output: One-sentence value proposition that passes the "mom test"

2. Market Sizing (Быстрая оценка)

Use scripts/market_sizer.py for TAM/SAM/SOM calculation:

python scripts/market_sizer.py --total-market 1000000 --addressable-percent 10 --obtainable-percent 5

Reality checks:

• TAM > $1B = maybe real market
• SAM > $100M = venture-scale potential
• SOM (first year) = be honest, usually <1% of SAM

3. MVP Scope Definition

Принцип: Smallest thing that proves value hypothesis

Use assets/mvp_canvas.md template to define:

• Core value proposition (1 sentence)
• Primary user action (1 action)
• Success metric (1 number)
• Time to first value (<5 minutes ideal)

Anti-pattern: "But we also need..." → NO. Ship, measure, iterate.

4. Monetization Strategy

See references/monetization-models.md for quick selection guide.

Key decisions:

• Pricing model: subscription / usage-based / transaction / freemium
• Price point: value-based (not cost-plus)
• Payment psychology: annual discounts, tiered pricing, anchor pricing

Forcing function: If they won't pay $X for this, the problem isn't urgent enough.

5. Unit Economics

Use scripts/unit_economics.py for rapid calculation:

python scripts/unit_economics.py --ltv 1200 --cac 400 --churn-rate 5

Minimum viability:

• LTV:CAC ratio ≥ 3:1
• CAC payback ≤ 12 months
• Monthly churn ≤ 5% (for SaaS)

If numbers don't work at scale, pivot or kill the idea.

6. Build & Launch Strategy

Week 1-2: Core feature + payment Week 3: First 10 paying customers (manual sales, no automation yet) Week 4: Measure, learn, decide: iterate / pivot / kill

Tech principles:

• No-code/low-code first (n8n, Airtable, Webflow)
• Manual processes behind automated facade
• Don't build what you can integrate
• PostgreSQL + Python API = enough for 100k users

7. Metrics Framework

See references/metrics-framework.md for stage-specific KPIs.

MVP stage - track only:

• Activation rate (signup → first value)
• Retention (D1, D7, D30)
• Revenue per user
• NPS or qualitative feedback

Ignore: total users, page views, social followers (vanity metrics)

8. Go-to-Market

Before product-market fit:

• Do things that don't scale (Paul Graham)
• Talk to users every day
• Manual sales → learn messaging
• Early adopters ≠ mainstream market

Channel testing sequence:

1. Direct outreach (LinkedIn, email, communities)
2. Content/SEO (if long sales cycle)
3. Paid ads (only after LTV:CAC proven)
4. Partnerships/integrations

Decision Points

When to iterate:

• Users sign up but don't activate → onboarding problem
• Users try once then churn → not enough value
• Good engagement, won't pay → wrong audience or positioning

When to pivot:

• No organic growth after 3 months of trying
• LTV:CAC fundamentally broken
• Users love it, but market too small

When to kill:

• No one cares (not even early adopters)
• You've stopped believing in it
• Better opportunity identified

Reference Materials

Load as needed:

• Monetization models: See references/monetization-models.md
• Metrics frameworks: See references/metrics-framework.md
• YC startup playbook: See references/yc-playbook.md

Templates

• MVP Canvas: assets/mvp_canvas.md - One-page planning template
• Unit economics sheet: Generate via scripts
• Weekly progress template: In assets/

Anti-Patterns to Avoid

• Building for 6 months before talking to users
• Perfecting features instead of testing core hypothesis
• Raising money before product-market fit
• Hiring before proving the model works
• Optimizing conversion before understanding why users stay
• "If we build it, they will come"