Minimum Viable Product Playbook MTA
Designing, building, and learning from MVPs to accelerate product-market fit

Table of Contents:

• Introduction
• Chapter 1 What MVP Really Means: Definitions, Origins, and Myths
• Chapter 2 Product–Market Fit Demystified: Signals, Stages, and Pitfalls
• Chapter 3 Choosing the Right Problem: Opportunity Sizing and Jobs to Be Done
• Chapter 4 Outcomes, Hypotheses, and Success Metrics
• Chapter 5 Scoping the Smallest Lovable Product
• Chapter 6 Customer Discovery and Rapid Research
• Chapter 7 Experiment Portfolio: Fake Doors, Concierge, and Wizard‑of‑Oz
• Chapter 8 Prototyping Fidelity: Sketches, Click‑Throughs, and Code
• Chapter 9 Designing Learning Loops and Experiment Cadence
• Chapter 10 MVP Architectures and Tech Stack Choices
• Chapter 11 Data Instrumentation and Analytics Fundamentals
• Chapter 12 A/B/n Testing: Power, Significance, and Ethics
• Chapter 13 Pricing and Monetization Experiments
• Chapter 14 Go‑to‑Market for MVPs: Channels, Positioning, and Launches
• Chapter 15 Enterprise and B2B MVPs: Pilots, Security, and Procurement
• Chapter 16 Consumer and Marketplace MVPs: Seeding and Network Effects
• Chapter 17 AI and Data Products: Datasets, Bias, and Feedback Loops
• Chapter 18 Hardware and IoT MVPs: Rapid Prototyping and Supply Risk
• Chapter 19 Design Systems for Speed: Reuse without Rigidity
• Chapter 20 Team Topologies and Roles for MVP Velocity
• Chapter 21 Governance, Risk, and Compliance Without Drag
• Chapter 22 The Decision Framework to Avoid Overbuilding
• Chapter 23 Interpreting Signals: Cohorts, Retention, and PMF Metrics
• Chapter 24 Scaling Post‑MVP: Roadmaps, Debt, and Quality
• Chapter 25 Case Studies: MVPs That Found Fit (and Those That Didn’t)