61.5 Operating Rhythms for AI Products
656.3 Safety Testing and Adversarial Prompt Testing
71.6 The AI Product Owner Charter
666.4 Operationalizing Red-Teaming in a PM Cadence
81.7 Escalation Ladder for AI Issues
676.5 Hallucination Metrics and Measurement
91.8 Onboarding Checklist for New AI Product Owners
686.6 The Release-Readiness Checklist for LLMs
101.9 Five Metrics Every AI Product Owner Must Track
696.7 Staged Rollout Plan: Shadow, Canary, Progressive
111.10 Manager's Checklist
706.8 Rollback Criteria and Decision Points
121.11 Takeaway
716.9 Red-Teaming Catches a Critical Safety Gap
132 AI Product Lifecycle: Stages, Handoffs, and KPIs
726.10 Manager's Checklist
142.1 Why It Matters
736.11 Takeaway
152.2 The Six-Stage AI Product Lifecycle
747 Human-in-the-Loop: Patterns that Scale
162.3 Stage Artifacts and Handoffs
757.1 Why It Matters
172.4 Manager's Deliverables and Acceptance Criteria per Stage
767.2 The HITL Pattern Catalog
182.5 The Stage-Gate Checklist
777.3 Confidence Thresholds and Escalation Rules
192.6 The Go/No-Go Decision Matrix
787.4 Reviewer Workflow UX Design
202.7 Lifecycle KPIs That Connect Business and Model Health
797.5 HITL Metrics That Matter
212.8 Combining Business Impact with Model Metrics
807.6 Costing and Staffing Human Review
222.9 Vignette: A Disciplined Stage-Gate Prevents a Premature Production Launch
817.7 Automation Opportunities Within HITL
232.10 Manager's Checklist
827.8 Measure Diminishing Returns on Human Review
242.11 Takeaway
837.9 Vignette: Tiered HITL at Meridian Insurance
253 Requirements: From Outcomes to Measurable Specs
847.10 Manager's Checklist
263.1 Why It Matters
857.11 Takeaway
273.2 Translating Business Goals to Model Requirements
868 Monitor, Observability, and MLOps for PMs
283.3 Defining Target Metrics
878.1 Why It Matters
293.4 Acceptable Failure Modes and Edge Cases
888.2 Designing the Minimal Monitoring Stack
303.5 Requirements for LLMs and RAG Systems
898.3 Business Metrics vs. Model Metrics
313.6 Non-Functional Requirements
908.4 Drift Detection: Data Drift and Concept Drift
323.7 Budgeting for Annotation and Human Review
918.5 Alerting Thresholds and Escalation
333.8 Stakeholder Negotiation Tactics
928.6 The Incident Runbook for Model Failures
343.9 The PRD Addendum Template
938.7 Retraining Triggers and Decision Points
353.10 Vignette: Precise Requirements Save Weeks of Rework
948.8 Tool Choices and Monitor Investment Priorities
363.11 Manager's Checklist
958.9 The Observability Dashboard
373.12 Takeaway
968.10 Early Drift Detection Averts Major Cust Impact
384 Model Selection and Architecture Tradeoffs
978.11 Manager's Checklist
394.1 Why It Matters
988.12 Takeaway
404.2 The Model Selection Decision Framework
999 Release Mgmt, & Long-term Stewardship
414.3 Arch Compare: API, RAG, Fine-Tune, and Hybrid
1009.1 Why It Matters
424.4 Accuracy vs Latency vs Cost vs Interpretability
1019.2 Release Management Practices for AI Products
434.5 Cost-Sensitivity Analysis for Early POCs
1029.3 Feature Flags User Segmentation for AI Rollouts
444.6 Vendor Evaluation Criteria
1039.4 The Rollback Playbook
454.7 Integration Risk Assessment
1049.5 Sunset Strategy and the Sunset Decision Matrix
464.8 Build vs. Buy Decision Matrix
1059.6 Migration Planning for Model Transitions
474.9 Vignette: The Hybrid RAG Decision
1069.7 Stakeholder Communication During Sunsets
484.10 Manager's Checklist
1079.8 Knowledge Capture for Successor Products
494.11 Takeaway
1089.9 The Phased Sunset Playbook
505 Data Strategy, Labeling, and Feature Stores
1099.10 Early Planning Enables a Smooth Migration
515.1 Why It Matters
1109.11 Manager's Checklist
525.2 Designing the Production Data Pipeline
1119.12 Takeaway
535.3 Quality Gates for Data Integrity
11210 Conclusion
545.4 Labeling Workflows and Annotation Governance
11310.1 Shift From Building Features to Gov Intel
555.5 Feature Stores for Repeatability and Consistency
11410.2 The Operating System You Now Own
565.6 Budget Annotation Effort Against Model Improve
11510.3 The Human Side of AI Product Ownership
575.7 Sampling Strategies for High-Impact Edge Cases
11610.4 Looking Ahead: Future You Are Prepare For
585.8 The Data Readiness Checklist
11710.5 A Final Charge
595.9 Vignette: Focused Labeling Sprint Moved Needle
