Appendix F: Recommended Reading

★ Michael E. Gerber — The E-Myth Revisited (HarperCollins, 1995). The book that taught me, in my twenties, to draw the finished org chart and then fill the boxes. Its core ideas are the backbone of this one: systems run the business and people run the systems; work on the business, not in it; design around roles, not around whoever happens to be there. Read it imagining that half the boxes will be filled by agents, and almost every page becomes more useful.

★ Andrew S. Grove — High Output Management (Random House, 1983). Grove’s claim that a manager’s output is the output of the organisation they oversee is the clearest answer to the executive who uses agents to do the work personally. His sections on delegation, task-relevant maturity and monitoring delegated work read as if written for supervising agents. It is also the best book on meetings and reports you will find.

★ Peter F. Drucker — The Effective Executive (Harper & Row, 1967). Drucker insists that executives are judged by results and contributions, not by effort or methods. That is the source of this book’s "what and why, never how". His chapter on knowing where your time goes is a useful audit for any leader who suspects agents have made them busier rather than more effective.

◆ Peter F. Drucker — The Practice of Management (Harper, 1954). The book that popularised management by objectives, paired with self-control: agree the result, then let the person, or the agent, manage how they get there. Older and longer than The Effective Executive, but it is where the idea of a role defined by its contribution to the whole is set out in full.

★ W. Edwards Deming — Out of the Crisis (MIT Press, 1986). Deming’s argument that most problems come from the system, not the worker, is the foundation of the Friction Review. Replace "worker" with "model" and the book is a direct rebuttal to the reflex of blaming the AI. Dense in places; the chapters on the fourteen points and on common versus special causes repay the effort.

★ Atul Gawande — The Checklist Manifesto (Metropolitan Books, 2009). The best short case for writing down procedure, and the best warning about doing it badly. Gawande’s checklists are short, aimed at the steps experts skip under pressure, and leave judgment to the professional. That is exactly the balance this book argues for between plain-English playbooks and hard rules.

★ Matthew Skelton & Manuel Pais — Team Topologies (IT Revolution, 2019; 2nd edition, 2025). A shared vocabulary for team types, interaction modes and, above all, cognitive load: a team should own only as much as it can hold in its head. That idea becomes the role coherence test in Chapter 5. Read it when you start deciding which roles share an agent and which need their own.

◆ Taiichi Ohno — Toyota Production System: Beyond Large-Scale Production (Productivity Press, 1988). The source for lean thinking and standard work: the idea that the documented procedure is the baseline from which every improvement starts. It is short and practical. Read it before you write your first Playbook.

◆ Eliyahu M. Goldratt & Jeff Cox — The Goal (North River Press, 1984). A novel about a failing factory and the theory of constraints: the throughput of a system is set by its bottleneck, and speeding anything else up only builds inventory. When agents make one part of your organisation ten times faster, this book tells you where the queue will form, which is usually at the human who has to review the output.

◆ Frederick P. Brooks Jr. — The Mythical Man-Month (Addison-Wesley, Anniversary Edition, 1995). Brooks showed that communication overhead grows faster than headcount, and that adding people to a late project makes it later. The same arithmetic applies to adding agents to a muddled process. His case for conceptual integrity, one mind owning the design, is the human version of the single-writer rule.

○ Melvin E. Conway — "How Do Committees Invent?" (Datamation, April 1968). The four-page paper behind Conway’s Law: organisations design systems that mirror their own communication structures. If your agents talk to each other through private messages and personal logins, your systems will end up shaped like that too. Short enough to read in a coffee break.

★ L. David Marquet — Turn the Ship Around! (Portfolio, 2013). A submarine captain’s account of replacing "permission to…" with "I intend to…", moving decisions to the people with the information. It is the best model I know for promoting an occupant to more autonomy: state intent, show the evidence, earn the next step. It also explains why leaders who issue detailed instructions get followers rather than owners.

★ Liz Wiseman with Greg McKeown — Multipliers (HarperBusiness, 2010). Wiseman distinguishes leaders who amplify the intelligence of their teams from "diminishers" who, often with good intentions, do the thinking for them. Executives with agents are at constant risk of becoming diminishers: the agent lets them do everyone’s work. Read it as a mirror.

◆ General Stanley McChrystal, with Tantum Collins, David Silverman & Chris Fussell — Team of Teams (Portfolio, 2015). How a rigid command structure learned to share information widely and push decisions down without losing coherence. The lesson for agents is the pairing: decentralised execution works only with radical transparency, which is why this book insists that agents work in public.

◆ Camille Fournier — The Manager’s Path (O’Reilly, 2017). Written for engineering managers, but its account of moving from doing to delegating is the best I have read on the individual contributor’s side of the shift. Hand it to the expert on your team who builds the best personal agents and finds it hardest to let go of the work.

◆ Will Larson — An Elegant Puzzle (Stripe Press, 2019). Systems thinking applied to management: team sizing, migrations, succession, and the habit of writing policy down so it can be debated and improved. His habit of treating the organisation as a system to model and adjust suits a team whose occupants change with every model release.

◆ Ethan Mollick — Co-Intelligence: Living and Working with AI (Portfolio, 2024). The most accessible framework for how generative AI changes work. Mollick’s advice to treat AI as a capable but strange colleague, and to invite it into everything to find where it helps, is the right starting posture. Read it early; this book picks up where it leaves off, when there are many such colleagues to organise.

These are articles, papers and specifications, most from 2025 and 2026. Full citations are in the footnotes of Appendix D. Hand the technical ones to your engineers; read the starred ones yourself.

★ Rich Sutton — "The Bitter Lesson" (2019, incompleteideas.net). A one-page essay arguing that, over the long run, general methods that use more computation beat systems built on hand-coded human knowledge. It is the strongest argument for plain-English playbooks over elaborate scaffolding, and the reason every lock-in in Chapter 11 carries a review date.

★ Erik Schluntz & Barry Zhang — "Building Effective Agents" (Anthropic, December 2024). The clearest introduction to agents for a non-engineer: what distinguishes a workflow from an agent, and why the simplest design that works is usually best. If you read one technical piece, read this one.

★ Barry Zhang, Keith Lazuka & Mahesh Murag — "Equipping Agents for the Real World with Agent Skills" (Anthropic, October 2025). Introduces skills and compares building one to "putting together an onboarding guide for a new hire." That sentence is the bridge between this book’s Playbooks and what your engineers will build. Short and readable.

◆ Prithvi Rajasekaran and colleagues — "Effective Context Engineering for AI Agents" (Anthropic, September 2025). Why an agent’s performance depends on giving it the smallest set of high-signal information, and the techniques for doing so. The technical companion to the Role Pack chapter.

◆ Lance Martin — "The Components of Agent Memory" (Anthropic, November 2026). How agents remember across sessions, in layers from raw transcripts to always-loaded context, and why stronger models do better with the purpose of memory than with rules for it. Useful for anyone deciding what goes in a Role Pack and what stays in a log.

◆ Justin Young — "Effective Harnesses for Long-Running Agents" (Anthropic, November 2025), and Prithvi Rajasekaran — "Harness Design for Long-Running Application Development" (Anthropic, March 2026). Two engineering posts on keeping agents productive over hours and days: progress files, one feature at a time, generator and evaluator agreeing on "done" in advance. The second contains the line every leader should remember: every component in a harness encodes an assumption about what the model can’t do on its own.

◆ Yubin Kim & Xin Liu — "Towards a Science of Scaling Agent Systems" (Google Research, January 2026). A controlled study of 180 agent configurations: coordinated teams contained error amplification and helped on parallel work, while every multi-agent variant tested made sequential planning worse. The evidence behind Chapter 6.

◆ Walden Yan — "Multi-Agents: What’s Actually Working" (Cognition, April 2026). A practitioner’s update from a team that had argued against multi-agent systems: they now work, mostly when several agents contribute thinking and one writes. Pair it with the Google study.

◆ Mert Cemri and colleagues — "Why Do Multi-Agent LLM Systems Fail?" (arXiv, 2025). A taxonomy of 14 failure modes in three groups (system design, misalignment between agents, and verification) drawn from more than 1,600 annotated traces. A good checklist for a Friction Review when several agents were involved.

◆ M. Grace, J. Hadfield, R. Olivares & J. De Jonghe — "Demystifying Evals for AI Agents" (Anthropic, January 2026). How to test whether an agent does its job, including why a 75 per cent success rate becomes about 42 per cent across three unattended runs, and why 20 to 50 tasks drawn from real failures is a good start. The practical side of acceptance.

◆ Anthropic — "Best Practices for Claude Code" (documentation). Written for developers, but its distinction between guidelines the model may weigh and rules the software enforces is the cleanest statement of the three tiers anywhere. Read the section on enforcing rules that can’t have exceptions.

◆ Dex Horthy — 12-Factor Agents (HumanLayer, GitHub). Twelve principles for production agents, written by someone who found that the agents that work are "mostly deterministic code, with LLM steps sprinkled in". A useful counterweight to this book’s preference for English; read it to know where the other side is right.

◆ Gregor Zunic — "The Bitter Lesson of Agent Harnesses" (Browser Use, April 2026), and Philipp Schmid — "The Importance of Agent Harness in 2026" (January 2026). Two short posts from builders who cut their scaffolding back as models improved: "Don’t wrap the LLM", and "Build to Delete". They are why lock-ins should be easy to remove.

○ Microsoft — "Administrative Relationships in Microsoft Entra Agent ID" (Microsoft Learn, 2026). The enterprise version of the sponsor model: owners for technical administration, sponsors for business accountability, managers for the reporting line. Read it when your agent count outgrows a spreadsheet.

○ NIST National Cybersecurity Center of Excellence — Accelerating the Adoption of Software and Artificial Intelligence Agent Identity and Authorization (concept paper, February 2026). The US standards body’s framing of agent identity, authorisation, auditing and non-repudiation. Situational, but the questions it asks make a good identity checklist for your security lead.

○ Model Context Protocol specification, revision 2026-07-28, and the A2A protocol 1.0 announcement (Linux Foundation, April 2026). The two open standards that let agents reach your tools and each other. Your engineers need the details; you need to know that standard interfaces are what make a role’s occupant replaceable.

○ Chip Huyen — AI Engineering: Building Applications with Foundation Models (O’Reilly, 2025). The most complete book-length guide to building production AI systems, including agents and evaluation. For the technical lead who wants one book rather than fifty blog posts.

★ Gareth Price — Applied Alchemy: The Startup CTO’s Field Guide to Building Technology Companies from Nothing (2026; startupctobook.com). My first book, written for technical leaders in startups. Its chapters on the move from maker to multiplier, on operating rhythm, and on AI transformation are the human-team foundations this book builds on. If you are the technical co-founder or CTO who will implement the Blueprint, start there; it also ends with an AI advisor appendix, the model for Appendix G.

Seventeen books and papers on organisations and leadership, about twenty pieces on agents. The first group will not change. The second will be out of date within a year, which is itself the lesson: build on the ideas that last, and treat the tooling as an occupant you expect to replace.