OpenAI Codex Masterclass: From Prompting to Agentic Workflows
OpenAI Codex Masterclass: From Prompting to Agentic Workflows
Most people use AI in a simple loop: ask a question, get an answer, then ask another question. But that is only a small part of what these tools can do.
This masterclass is about moving from AI that answers to AI that works.
OpenAI Codex can take a clear goal, understand the context, plan the steps, work across files and tools, check its own output, and help complete real tasks. Instead of repeatedly explaining what you need, you can build a system with persistent instructions, rules, permissions, and reusable workflows.
Across two practical hours, participants will see real work built in front of them and then build it themselves. The session focuses on two core areas:
Codex for Development: planning, building, debugging, testing, and deploying applications.
Codex Work: creating structured AI workspaces with projects,
AGENTS.md, Skills, plugins, and persistent instructions.
The masterclass is designed to be practical and demonstration-led. Participants will see how a clear goal can be transformed into a plan, a completed task and a verified output.
This is not another session about prompt tricks. It is about learning how to give AI a job, the right context, and the right rules so it can carry real work.
Why Codex
Codex is built around a simple idea: give AI a goal and let it help complete the work, not just answer prompts.
It can work autonomously across code, files, web, CLI, desktop, and connected tools, making it useful not only for developers, but also for founders, marketers, operators, and other professionals.
This masterclass is not about comparing coding tools. It focuses on learning a practical way of working with AI: giving it context, rules, tools, and clear outcomes so it can take on larger parts of your work.
Masterclass Objective
The goal is to give participants a practical understanding of how Codex can support:
Software and product development
Structured professional work
Participants will learn how to provide the right context, establish working rules, supervise AI actions, and evaluate the quality of the final output.
Who Should Join?
This masterclass is suitable for:
Students and recent graduates
Developers, designers, and product builders
Startup founders
Business and operations professionals
Marketers and content creators
Researchers and educators
Project and team managers
Anyone interested in AI automation
No advanced programming experience is required. Basic technical knowledge is helpful for the development section, but the overall masterclass is designed for both technical and non-technical participants.
Prerequisites
Participants should bring:
A laptop with internet access
A ChatGPT account with Codex or ChatGPT Work access
The ChatGPT desktop app, where available
Basic familiarity with files and folders
A GitHub account, if joining the development activities
One project, task, or workflow they want to improve
Masterclass Tracks
Track 1: Codex for Development
Plan and build: Turn ideas or codebases into structured development tasks and working features.
Debug and verify: Fix issues, run tests, review code, and check output quality.
Ship with Codex: Use GitHub, parallel tasks, deployment, and final verification.
Track 2: Codex Work
Create persistent workspaces: Use projects,
AGENTS.md, and reusable instructions.Build Skills and workflows: Route tasks, connect tools, and automate repeatable work.
Work across tools: Use files, browsers, plugins, and connected services with defined rules.
What You’ll Learn
By the end of the masterclass, participants will understand how to:
Move from conversational AI to agentic AI
Structure a Codex project
Write clear, outcome-focused instructions
Use Plan Mode for more complex tasks
Build, debug, test, and review applications
Create persistent instructions with
AGENTS.mdUse Skills, plugins, files, browsers, and connected tools
Build repeatable productivity workflows
Identify tasks suitable for automation
Apply the right permissions and human approval controls