Agentic Coding with OpenAI Codex CLI

Build intelligent agent workflows using Agentic Engineering, MCP, hooks, and delivery automation

Paperback Engels 2026 9781808348891
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Comprehensive guide to Codex CLI: prompting, AGENTS.md, MCP, hooks, skills, sub-agents, orchestration, CI/CD, security, and enterprise deployment, with exercises

Key Features

Move from first principles to production workflows and team-scale agentic practice.
Apply proven patterns for orchestration, code review, migration, testing, and CI/CD delivery.
Harden agent sessions with approval modes, kernel-level sandboxing, and security practices.
Purchase of the print or Kindle book includes a free PDF eBook

Book DescriptionAgentic Coding with OpenAI Codex CLI is a comprehensive guide to agentic AI development with OpenAI's command-line coding agent. Across six parts, you'll move from first principles to production workflows and team-scale practice: prompting and AGENTS.md configuration, approval modes and kernel-level sandboxing, model selection, context and cost management, MCP servers, hooks, skills, sub-agents and orchestration, worktrees, CI/CD integration, security hardening, and enterprise deployment.
Later chapters cover debugging and testing agentic workflows, AI code review, practical engineering guides (codebase migration, backend, frontend, and infrastructure as code), and the bigger picture: benchmarks, competing tools, harness engineering, and how to structure an agentic engineering team.
Whether you're a solo developer looking to multiply your output or an engineering lead rolling out agentic workflows across a team, this book gives you the mental models and practical techniques to work effectively with AI coding agents.
It draws on real-world experience and community insights, and every chapter includes learning objectives, worked examples, and hands-on exercises.What you will learn

Set up, authenticate, and prompt Codex CLI effectively
Write AGENTS.md rules and apply patterns that avoid common pitfalls
Choose approval modes, kernel-level sandboxing, and trust boundaries
Manage model selection, reasoning effort, context windows, and cost
Extend the agent with MCP servers, hooks, and skills
Coordinate sub-agents, multi-agent orchestration, and worktrees
Integrate Codex into CI/CD, security hardening, and enterprise deployment
Apply Codex to code review, migration, backend, frontend, and infrastructure as code

Who this book is forThis book is for software developers who are comfortable in a terminal and want to use AI agents for real engineering work rather than isolated code suggestions. It is also useful for tech leads and engineering managers who need a framework for adopting agentic coding safely at team or enterprise scale. DevOps practitioners and architects interested in integrating agent workflows into delivery pipelines will also find it relevant. Some experience with version control and command-line tools is assumed; no prior knowledge of Codex CLI is required.

Specificaties

ISBN13:9781808348891
Taal:Engels
Bindwijze:Paperback
Aantal pagina's:670
Uitgever:Packt Publishing Limited

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Inhoudsopgave

Table of Contents
  1. What Is Codex CLI?
  2. Getting Started with Codex CLI
  3. Prompting Codex CLI Effectively
  4. AGENTS.md: Patterns and Pitfalls
  5. Approval Modes and Trust Boundaries
  6. Model Selection and Reasoning Effort
  7. Context Window Management
  8. MCP: Consuming and Serving
  9. Hooks: Intercepting the Agent Lifecycle
  10. The Skills Ecosystem: Using and Writing Skills
  11. Sub-Agents and Parallel Execution
  12. Multi-Agent Orchestration Patterns
  13. Worktrees and Isolated Execution
  14. Cost Management and Quota Strategy
  15. CI/CD Integration
  16. Security Hardening
  17. Enterprise Deployment
  18. Debugging and Diagnosing Agent Failures
  19. Testing and Evaluation Strategy for Agentic Workflows
  20. AI Code Review
  21. Codebase Migration and Modernisation
  22. Backend Engineering
  23. Frontend Engineering
  24. Infrastructure as Code
  25. Benchmarks and Real-World Performance
  26. Competing Tools and When to Use Each
  27. Harness Engineering for Long-Running Agents
  28. The Agentic Engineering Pod

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          Agentic Coding with OpenAI Codex CLI