Description
Learn Multi Agent Engineering with OpenAI Codex is a course on designing and building multi-agent software development workflows with OpenAI Codex published by Udemy Online Academy. This course explores the full agent-driven engineering cycle with Codex: defining the problem, dividing work into roles, designing immediate contracts, coordinating sub-agents, managing context, reviewing outputs, debugging failed executions, and packaging a clean deliverable. Designed for developers, AI engineers, software architects, and programmers interested in agent-driven coding, this course explores how multiple specialized AI agents can work together to analyze requirements, write code, review implementations, run tests, debug issues, and perform complex development tasks.
Learners will study multi-agent architecture, agent roles, task delegation, context management, tooling, orchestration, agent communication, parallel workflows, and human supervision. This course is not about passive AI theory. It focuses on practical implementation: how to tell agents what to do, how to keep them coordinated, how to validate their work, and how to turn chaotic automated output into reliable software artifacts. By the end, you will have a complete operational model for Codex multi-agent projects: from the first project brief to task decomposition, agent coordination, validation, documentation, and project delivery.
What you will learn in Learn Multi Agent Engineering with OpenAI Codex:
- Design multi-agent Codex workflows with clear roles, responsibilities, and handoff contracts.
- Break large software tasks into planner, implementer, reviewer, QA, and documentation agent workstreams.
- Write effective Codex prompts that preserve context, constraints, and acceptance criteria.
- Use structured task boards, manifests, and progress trackers to coordinate long-running builds.
- Add testing, review, and release gates so agent-generated changes are verified before shipping.
- Debug failed agent runs, stale context, broken assumptions, and noisy outputs without losing control.
- Package reusable project artifacts, examples, and references for students or teammates.
- Build an end-to-end multi-agent dashboard and handoff workflow using production-style practices.
- and …
Course specifications
Publisher: Udemy
Instructors: The AI Orchestrator
Language: English
Level: Introductory to Advanced
Number of Lessons: 64
Duration: 6h 4m
Course topics
Learn Multi Agent Engineering with OpenAI Codex Prerequisites
Basic familiarity with software development workflows, code editors, and command-line tools.
Access to OpenAI Codex or a Codex-capable coding agent is helpful for practicing the demos.
A computer that can run a browser, terminal, code editor, and downloadable project files.
No advanced AI or distributed-systems background is required; the agent patterns are introduced step by step.
Pictures
Learn Multi Agent Engineering with OpenAI Codex introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 1080p
Downloadly link
Rapidgator link
File password (s): www.downloadly.ir
Size
2.3 GB