Learn Multi Agent Engineering with OpenAI Codex

About this course

This course contains the use of artificial intelligence.

Build Multi-Agent Systems with OpenAI Codex is a practical course for developers, technical builders, and AI workflow operators who want to move beyond one-off prompting and design reliable multi-agent software workflows.

The course walks through the full lifecycle of agentic engineering with Codex: defining the problem, splitting work into roles, designing prompt contracts, coordinating subagents, managing context, reviewing outputs, debugging failed runs, and packaging a clean handoff. Instead of treating an AI coding assistant as a magic text box, you will learn how to run it as part of a structured production process.

Across 15 sections and 64 lessons, you will see how to build reusable workflows for planning, implementation, review, QA, release preparation, dashboards, and final delivery. Each lesson includes a downloadable resource package so you can review the prompts, checklists, examples, and supporting files after watching the video.

This is not a course about passive AI theory. It is focused on practical execution: how to tell agents what to do, how to keep them aligned, how to verify their work, and how to turn messy autonomous output into dependable software artifacts.

By the end, you will have a complete operating model for multi-agent Codex projects: from the first project brief through task decomposition, agent orchestration, validation, documentation, and handoff. You can apply these patterns to internal tools, product prototypes, courseware, dashboards, automation projects, or any software workflow where multiple AI-assisted workstreams need to stay coordinated.

If you already use AI coding assistants and want a more disciplined way to plan, execute, review, and ship with them, this course gives you a clear framework and a library of practical examples to adapt to your own projects.

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