Codex CLI — is a practice-oriented guide on creating, configuring, and scaling intelligent CLI agents for software development. The material is structured in such a way as to provide the reader not only with theory but also with practical techniques that can be immediately implemented into team or individual development workflows.
What You Will Learn from the Book
The guide covers the full cycle of working with agent engineering based on OpenAI Codex CLI — from basic principles to complex system configurations. The reader will encounter:
- detailed analyses of prompts and principles of their design;
- structure and optimization of
AGENTS.mdfor different scenarios; - creation and configuration of MCP servers;
- use of hooks, skills, and sub-agents;
- building task trees (worktrees) and complex orchestration chains;
- embedding agents into CI/CD;
- rules for safe operation and corporate deployment.
Practical Focus of the Materials
Each chapter is accompanied by clear learning objectives, understandable examples, and practical assignments. This approach ensures a deep understanding of how agents work "under the hood" and how to extract maximum benefit from them in real-world development.
Who This Guide is For
- independent developers seeking to increase speed and quality of work;
- team leads and engineers implementing agent workflows in the team process;
- architects studying methods for integrating AI assistants into corporate infrastructure;
- AI enthusiasts wanting to understand modern methods of agent engineering.
About the Author
The book is written by Daniel Vaughan — a practicing engineer and author of numerous technical materials on agent systems. His experience working with production environments and feedback from the broad IT community have made this guide highly practical and focused on real-world tasks.
Why You Should Study Codex CLI Now
Agent engineering is quickly becoming a key competency in the modern development cycle. Mastering Codex CLI provides a competitive advantage: you can automate routines, improve code quality, accelerate releases, and implement AI orchestration on a team or company-wide scale.
