Agentic Coding with OpenAI Codex CLI: Build intelligent agent workflows using Agentic Engineering, MCP, hooks, and delivery automation

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.