Agentic Coding Workflows with Codex
Build Complex Workflows with ChatGPT Codex AI Agents and Deploy in Days
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Narrated by:
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Jon Mills's voice replica
This title uses a narrator's voice replica
About this listen
The future of software development is autonomous, intelligent, and faster than ever before. If you have been watching AI coding tools evolve from simple autocomplete to sophisticated programming partners, this book shows you how to harness their full potential through agentic workflows that plan, code, test, and refactor with minimal human intervention.
Agentic Coding Workflows with Codex is your complete practical guide to building AI-driven development pipelines that work like experienced junior developers. This is not about generating code snippets on demand. This is about designing autonomous coding agents that break down complex problems, write production-ready code, handle errors intelligently, and iterate toward working solutions.
Whether you are a software engineer looking to multiply your productivity, a prompt engineering specialist refining your craft, or a developer exploring cutting-edge AI automation, this book delivers the hands-on knowledge you need to build truly autonomous coding systems.
Inside, you will discover:
• How OpenAI Codex and similar LLM coding agents actually work and where they excel in real development workflows
• Step-by-step methods for designing agentic coding systems that automate repetitive tasks, handle complex refactoring, and accelerate your entire development lifecycle
• Advanced prompt engineering strategies specifically optimized for autonomous coding agents, including chain-of-thought prompting and iterative refinement techniques
• Practical frameworks for integrating AI coding assistants into your existing development environment, CI/CD pipelines, and project management tools
• Techniques for building autonomous code review agents, automated testing workflows, and self-correcting debugging systems
• Real-world implementation examples spanning web development, API integration, data engineering, and automation scripting
©2026 Michael Patterson (P)2026 Michael Patterson