Agentic Coding with OpenAI Codex CLI: Build intelligent agent workflows using Agentic Engineering, MCP, hooks, and delivery automation
暫譯: 使用 OpenAI Codex CLI 的代理編碼：利用代理工程、MCP、hooks 和交付自動化構建智能代理工作流程

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 Description:

Agentic 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 for:

This 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.

Table of Contents:

- What Is Codex CLI?

- Getting Started with Codex CLI

- Prompting Codex CLI Effectively

- AGENTS.md: Patterns and Pitfalls

- Approval Modes and Trust Boundaries

- Model Selection and Reasoning Effort

- Context Window Management

- MCP: Consuming and Serving

- Hooks: Intercepting the Agent Lifecycle

- The Skills Ecosystem: Using and Writing Skills

- Sub-Agents and Parallel Execution

- Multi-Agent Orchestration Patterns

- Worktrees and Isolated Execution

- Cost Management and Quota Strategy

- CI/CD Integration

- Security Hardening

- Enterprise Deployment

- Debugging and Diagnosing Agent Failures

(N.B. Please use the Read Sample option to see further chapters)