Part Overview
Part I grounds you in why AI fundamentally changes product creation. You will understand the dramatic economic shifts, what AI can and cannot do reliably, the Human-AI Product Stack framework, and the scientific principles underlying AI products.
This part establishes the evidence loop that runs throughout the entire book. Rather than presenting AI product development as a linear pipeline, this book is structured around a recursive cycle where each part:
- Observes real-world AI product behavior and outcomes
- Theorizes principles that explain what works and what fails
- Experiments through hands-on practice and prototyping
- Feeds back findings to revise earlier assumptions
Part I specifically lays the groundwork by establishing the economic reality (50x cost reduction), the capability boundaries (what AI reliably does), the Human-AI Product Stack (how humans and AI collaborate), and the scientific principles (cognitive load, complementary change) that will recur in every subsequent part. When later parts surface tensions or contradictions with these foundations, treat those moments as the evidence loop closing.
"The GPT-4 equivalent that cost $20 per million tokens in 2022 now costs $0.40. That is a 50x price reduction in four years."
The Economics Revolution
Chapters in This Part
The dramatic cost decline in AI, reasoning models, multimodal capabilities, and the build/buy/bake decision framework.
Honest capabilities assessment, hallucination mitigation, and practical limitations.
The interplay between human judgment and AI capabilities in product development.
- 3.1 Visual Model of the Human-AI Stack
- 3.2 AI as Amplifier
- 3.3 Feedback Loops
- 3.4 Anti-Patterns
Cognitive load theory, complementary change theory, and philosophical frameworks.
What You Will Learn
- Understand the 50x cost reduction and its strategic implications
- Recognize what AI can and cannot do reliably
- Apply the Human-AI Product Stack framework
- Grasp the scientific foundations underlying AI product development
Earlier artifacts updated by this part:
- None (this is the foundational part)
Later chapters this part prepares for:
- Part II, Ch 6: Build/buy/bake decisions depend on the economic framework (Ch 1)
- Part II, Ch 7-8: AI-native discovery and UX design extend the Human-AI Stack (Ch 3)
- Part III, Ch 10-14: Vibe-coding feasibility is bounded by AI capabilities (Ch 2)
- Part IV, Ch 15-20: Engineering architectures embody the Human-AI Stack principles
- Part V, Ch 21-25: Eval frameworks operationalize the capabilities/limitations map
- Part VI, Ch 26-30: Shipping strategies must account for AI reliability constraints
- Part VII, Ch 31-33: The capstone synthesizes all foundational concepts