Autonomous Agents: transforming engineering and business
In the style of The Phoenix Project: from chaos to effectiveness with AI agents.
Status: Work in Progress. The structure is stable; chapters are being edited and refined.
How to read this book#
Fast start for engineers:
- Start with Chapter 1 — create your first working prompt and verification plan
- Use the “Quick start” section in each chapter for immediate practical value
- Come back to the full chapter when you need depth
For managers and business stakeholders:
- Start with the short summary at the beginning of each chapter
- Read Appendix A: Business case template as a template for justification
- Read Appendix B: Organizational transformation as a change-management playbook
Structure: 3 cases, 10 chapters#
Case 1: deployment chaos (Chapters 1–4)#
- Chapter 1: first prompt
- Chapter 2: system prompt and guardrails
- Chapter 3: from a business request to spec v1 + plan v1
- Chapter 4: architecture design v1
Case 2: the Brent bottleneck (Chapters 5–7)#
- Chapter 5: SOP “design -> PR”
- Chapter 6: operations and incidents
- Chapter 7: security and infrastructure
Case 3: the payroll incident (Chapters 8–10)#
Chapters
Chapter 1: first prompt + verification plan
How to write your first prompt as a contract and verify an agent’s output with a verification plan instead of taking it on faith.
ChapterChapter 2: system prompt + guardrails + dialogue SOP
How to turn a one-off prompt into a role with guardrails: constraints, stop conditions, and a repeatable dialogue SOP.
ChapterChapter 3: spec v1 + plan v1
How to turn a task into a manageable project: spec v1, a work plan, a risk register, and verifiable done criteria.
ChapterChapter 4: Phoenix Project architecture v1
Architecture design v1: components, contracts, tradeoffs, and verifiable decisions instead of arrow slides.
ChapterChapter 5: an agent-driven SOP for "design → PR"
A repeatable development process with an agent: from design and guardrails to PR, verification gates, and artifacts that reduce Bus factor.
ChapterChapter 6: operations and incidents
How to make incident response repeatable: SLI/SLO, triage, response scenarios, escalation criteria, and verifiable runbooks.
ChapterChapter 7: security and infrastructure
Security-by-design for agent workflows: threat model, guardrails, change plan, least privilege, and fast rollback.
ChapterChapter 8: eval dataset + golden tests
How to measure agent quality: eval datasets, golden tests, regressions, and a continuous improvement loop without "trusting the answer".
ChapterChapter 9: agent teams + governance
How to make multi-agent practice manageable: delegation, roles and checks, Skill Router, Git-first Agent Skills, and failure patterns.
ChapterChapter 10: capstone (full cycle)
A full end-to-end cycle—from business request to production operations—on one continuous case.
ChapterAppendix
Appendix A: business case template for adopting AI agents
A business case template without false precision: variables, risks, mitigations, and go/no-go criteria for adopting AI agents.
AppendixAppendix B: organizational transformation
A practical playbook: how to roll out an agent practice without resistance and without false precision.
AppendixAppendix C: development process and project artifacts
An end-to-end process map and the engineering artifacts (ADR, `runbook`, PR, DoD) that turn words into evidence.
AppendixGlossary
Terms, abbreviations, and artifacts used across the book: SLO/SLI, SOP, guardrails, eval datasets, and more.
Appendix