Strategy, economics, evaluation, governance
Token Economics, Pricing, and Margin Design
AI product economics are volatile because cost scales with user behavior, model choice, context size, latency expectations, and retry patterns. This module teaches leaders to model usage before pricing the product or promising unlimited intelligence.
Deep dive summary
What this module actually teaches.
Passage 1AI product economics are volatile because cost scales with user behavior, model choice, context size, latency expectations, and retry patterns. This module teaches leaders to model usage before pricing the product or promising unlimited intelligence.
Passage 2Learners study inference cost drivers, prompt caching, context-window tiers, model routing, free-to-paid conversion risks, and how feature packaging can steer users toward sustainable usage. The module avoids simplistic token calculators and instead builds a margin model tied to real product flows.
Passage 3By the end, students can explain which features are cost centers, which can be bundled, which require usage caps, and which justify premium pricing because they replace expensive human work.
Learning operating system
Module prerequisites, concepts, outcomes, and artifacts
Prerequisites
- Basic SaaS metrics
- familiarity with pricing models
Key concepts
- inference cost modeling
- usage tiers
- gross margin
- model routing economics
- prompt cache impact
- pricing fences
Target audience
- Product leaders, growth teams, and founders defining AI packaging, plan limits, and business models.
Outcomes
- Estimate AI feature margins under realistic usage scenarios
- Design plan limits that protect both users and the business
- Translate technical cost levers into product packaging decisions
Artifacts
- AI margin model
- pricing-tier stress test
- usage policy draft
Code example
Real patterns, ready to copy into your editor.
A code reference card that frames this module's concepts in real syntax. Copy any example to study it or adapt it directly in your own editor.
1type ModuleBrief = {2 track: string;3 difficulty: string;4 keyConcepts: string[];5 reviewGate: 'human-review-required';6};7 8export const moduleBrief: ModuleBrief = {9 track: 'Product Leaders',10 difficulty: 'Intermediate',11 keyConcepts: [12 'inference cost modeling',13 'usage tiers',14 'gross margin',15 'model routing economics',16 'prompt cache impact',17 ],18 reviewGate: 'human-review-required',19};