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Leading Engineering Teams in the AI Era

The manager's playbook for AI-native engineering organizations

This book is 100% completeLast updated on 2026-06-15

The first book that addresses engineering management specifically for the AI-native era. Classic EM books like The Manager's Path and An Elegant Puzzle predate agentic coding tools — this one starts where they left off. Every chapter

produces a concrete artifact: a hiring rubric, a performance calibration guide, a budget template, a rollout plan. By the end, you have a complete management playbook for leading engineering teams where agents write most of the code.

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About

About

About the Book

The first book to address engineering management in the age of AI coding agents. Covers team design, hiring, career ladders, performance calibration, code review governance, security, budgeting, and the path to Director — with a concrete playbook artifact built chapter by chapter. Written by a senior engineering leader managing 60+ engineers across three countries.

Author

About the Author

CAIO INCAU

aio Incau é Engineering Manager com experiência liderando times de engenharia de software em larga escala. No dia a dia, combina gestão de pessoas com profundidade técnica para entregar produtos que impactam milhões de usuários. Começou a usar Claude Code por curiosidade, virou adepto por produtividade, e escreveu este livro para que outros desenvolvedores não precisem descobrir tudo sozinhos.                

                                                                                                                              

Contents

Table of Contents

  1. Why Engineering Leadership Is Being Rewritten
  2. The AI-Native Operating Model
  3. Team Topologies with Agents in the Loop
  4. Measuring Real AI ROI and Productivity
  5. From AI Adoption to AI Accountability
  6. Hiring and Assessing Engineers in the AI Era
  7. Career Ladders When Agents Write the Code
  8. Performance Management and Calibration
  9. Code Review, Quality, and Governance of Agent Output
  10. Security, Risk, and Compliance for AI-Assisted Teams
  11. Budgeting: AI Spend, Token Costs, and Tool Sprawl
  12. Leading Change: Rollout, Resistance, and Upskilling
  13. Multi-Country and Distributed Teams in the AI Era
  14. The EM's Own Workflow with AI
  15. The Road to Director: Scaling Yourself
  16. Appendix: Templates, Checklists, and Quick References

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