Part Overview
Part VI covers everything after prototyping: launching AI products, building learning loops, designing team structures, and strategic positioning.
Interlock with Previous Part
What this part inherits from Part V:
- Eval pipelines (Ch 21) become the foundation for launch criteria and post-launch monitoring
- Observability and failure analysis (Ch 22) inform launch readiness assessment
- Reliability and guardrails (Ch 23) become SLA commitments
- Cost management (Ch 24) becomes unit economics for pricing and GTM
- Governance frameworks (Ch 25) become compliance requirements for launch
What this part changes retroactively:
- Eval definitions get validated by production behavior: real users reveal eval gaps
- Reliability requirements get refined based on actual usage patterns
Artifacts that now need updating:
- GTM strategies must account for AI product-specific launch risks
- Team topologies (Ch 28) reflect the eval-driven culture established in Part V
Chapters in This Part
GTM strategies, pricing models, onboarding.
User feedback, continuous improvement, learning flywheels.
Cross-functional teams, AI-first culture.
Organizational structures, career paths, hiring.
Competitive positioning, 2026+ trends.
Bridge Notes
Earlier artifacts updated by this part:
- Part II, Ch 6: Product strategy now accounts for launch and scaling constraints
- Part IV, Ch 15-20: Engineering decisions are validated against operational requirements
- Part V, Ch 21-25: Evals, guardrails, and cost models become launch commitments
Later chapters this part prepares for:
- Part VII, Ch 31-33: The capstone synthesizes shipping and scaling as the final phases of the product lifecycle