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AI Systems Handbook

A practical handbook for deciding when to use AI and how to build, evaluate, operate, and govern AI-enabled systems responsibly.

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A luminous AI constellation held within evaluation, governance, tool, feedback, and human-control rings.

Reading order

Contents

Part 1

AI Fundamentals Without the Hype

6 entries
  1. 01 What AI Is, and What AI Systems Are
  2. 02 How Machines Learn from Data
  3. 03 Prediction, Classification, Ranking, Recommendation, and Forecasting
  4. 04 Generative AI, LLMs, and Multimodal Models
  5. 05 Agents, Tools, and Autonomy
  6. 06 Why AI Fails

Part 2

Deciding When AI Is Appropriate

5 entries
  1. 07 The AI Appropriateness Question
  2. 08 From Vague Idea to Testable Use Case
  3. 09 Risk Triage Before Building
  4. 10 Business Case, Cost, and Value Realization
  5. 11 Data Readiness and Rights Readiness

Part 3

Data, Models, and the AI Development Lifecycle

5 entries
  1. 12 Data as Product, Evidence, and Liability
  2. 13 Model Selection: Rules, Classical ML, Deep Learning, Foundation Models, and Hybrids
  3. 14 Training, Fine-Tuning, Prompting, and Retrieval
  4. 15 Model Documentation and Release Discipline
  5. 16 The AI Lifecycle: From Idea to Retirement

Part 4

Designing Reliable AI-Enabled Systems

8 entries
  1. 17 AI Product Requirements
  2. 18 Human-Centered AI Design
  3. 19 Human Oversight, Escalation, and Accountability
  4. 20 Architecture Patterns for AI Systems
  5. 21 Retrieval-Augmented Generation Systems
  6. 22 Guardrails, Policies, and Control Layers
  7. 23 Security Architecture for AI Applications
  8. 24 Privacy, Confidentiality, and Data Protection by Design

Part 5

Evaluation, Testing, and Assurance

8 entries
  1. 25 Evaluation Mindset: From Demo to Evidence
  2. 26 Metrics for Predictive Models
  3. 27 Evaluating Generative AI
  4. 28 Evaluating RAG and Knowledge Systems
  5. 29 Evaluating Agents and Tool-Using Systems
  6. 30 Robustness, Fairness, Bias, and Segment Performance
  7. 31 Red Teaming, Adversarial Testing, and Abuse Cases
  8. 32 Online Experiments, Pilots, Shadow Mode, and Launch Decisions

Part 6

Production Operations and Reliability

7 entries
  1. 33 MLOps and LLMOps Foundations
  2. 34 Observability, Monitoring, and Drift
  3. 35 Incident Response for AI Systems
  4. 36 Change Management and Continuous Improvement
  5. 37 Reliability, Resilience, and Fallback Design
  6. 38 Cost, Latency, and Performance Engineering
  7. 39 Decommissioning and End-of-Life

Part 7

Responsible AI Governance

7 entries
  1. 40 Governance as an Operating System
  2. 41 Accountability, Transparency, and Explainability
  3. 42 Fairness, Harm, and Impact Assessment
  4. 43 Regulatory and Policy Landscape
  5. 44 Third Parties, Vendors, and Foundation Model Providers
  6. 45 Intellectual Property, Content, and Provenance
  7. 46 Environmental and Societal Considerations

Part 8

Organizational Adoption and Culture

4 entries
  1. 47 Building an AI Operating Model
  2. 48 AI Portfolio Management
  3. 49 AI Literacy, Training, and Change Management
  4. 50 Culture: Skepticism, Evidence, and Responsible Velocity

Part 9

Part IX - Worked Case Studies

8 entries
  1. Case 1 Case Study 1: Internal Knowledge Assistant
  2. Case 2 Case Study 2: Customer Support Summarization and Drafting
  3. Case 3 Case Study 3: Fraud Detection Model
  4. Case 4 Case Study 4: Clinical Documentation Assistant
  5. Case 5 Case Study 5: Hiring Workflow Assistant
  6. Case 6 Case Study 6: Autonomous IT Remediation Agent
  7. Case 7 Case Study 7: Public Sector Benefits Triage
  8. Case 8 Case Study 8: Education Tutor

Part 10

Part X - Appendices and Field Tools

15 entries
  1. Appendix A Appendix A: AI Appropriateness Scorecard
  2. Appendix B Appendix B: AI Use Case Canvas
  3. Appendix C Appendix C: Initial AI Risk Triage Form
  4. Appendix D Appendix D: Dataset Datasheet Template
  5. Appendix E Appendix E: Model Card Template
  6. Appendix F Appendix F: AI Evaluation Plan Template
  7. Appendix G Appendix G: Generative AI Evaluation Rubric
  8. Appendix H Appendix H: Human Oversight Plan Template
  9. Appendix I Appendix I: AI Threat Model Worksheet
  10. Appendix J Appendix J: AI Monitoring Plan Template
  11. Appendix K Appendix K: AI Launch Readiness Checklist
  12. Appendix L Appendix L: AI Incident Report Template
  13. Appendix M Appendix M: AI Change Request Template
  14. Appendix N Appendix N: Illustration System for the Future Book
  15. Appendix O Appendix O: Glossary