Alexander Embiricos, the product lead for Codex at OpenAI, shares practical workflows for getting the most out of this AI coding agent. In this episode, he demonstrates how both non-technical users and experienced engineers can leverage Codex to accelerate development, from making simple code changes to building production-ready applications. Alex walks through real examples of using Codex in VS Code and terminal environments, implementing parallel workflows with Git worktrees, and creating detailed implementation plans for complex projects. He also reveals how OpenAI uses Codex internally, including how they built the Sora Android app in just 28 days, and offers insights on automated code review and the future of AI-assisted development.

What you’ll learn:

How to set up and use Codex in VS Code and terminal environments for both simple and complex coding tasks
A practical workflow for running multiple Codex instances in parallel using Git worktrees to avoid conflicts
How to create detailed implementation plans using the Plans.md technique for complex engineering projects
Why context is critical when prompting Codex—and how to provide the right information for better results
How OpenAI uses automated code review to accelerate development while maintaining high quality standards
The key differences between vibe coding for prototypes versus building production-ready applications with AI
How the new GPT-5.2 model improves Codex’s capabilities with faster reasoning and better problem-solving