AI Pricing Playbook: A Practical Guide for Startups is the operator’s guide to pricing AI products without killing adoption, margin, or trust.SaaS pricing logic breaks the moment your COGS becomes compute, your “user” becomes an agent, and value shows up as outcomes, not seats. This book shows you how to build pricing that matches how AI actually ships: variable usage, workflow depth, model routing, and reliability constraints.You’ll go from fundamentals to execution: value-based pricing for B2B AI, outcome-based models that don’t backfire, launch pricing that survives the first six months, and the mechanics of token and credit systems. You’ll learn why per-user pricing quietly caps growth, how to escape pricing debt before it compounds, and how to design pricing infrastructure so packaging, meters, limits, and billing don’t become your bottleneck.It also goes where most pricing books stop: metric density (how many measurable value events you can charge for), dynamic pricing for volatile usage, unit economics under model costs, and how to fight price wars when competitors are wrappers racing to zero. Finally, it tackles the long tail: how to price for niche, fragmented markets without turning your team into a custom-quote factory.Inside the BookPractical models for value-based and outcome-based pricing in AILaunch frameworks, pricing experiments, and adjustment rulesCredit, token, and hybrid systems that reduce friction without leaking valuePackaging strategies for Enterprise vs SMB, with clear tradeoffsGuardrails for margins: unit economics, meters, limits, and anti-abuse designBattle-tested moves to avoid price wars and win with smarter constraintsIf you are building an AI product and your pricing still looks like SaaS, this is the reset.
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