How OpenAI uses Codex
This document details how OpenAI's technical teams utilize Codex daily to accelerate various engineering tasks. It compiles use cases and best practices, demonstrating how Codex enhances speed, work quality, and complexity management across different teams like Security, Product Engineering, and Infrastructure. ✨
Article Points:
1
Codex accelerates code understanding, refactoring, and performance tuning.
2
It boosts test coverage and increases development velocity for engineers.
3
Codex aids in staying focused and supports exploration/ideation for solutions.
4
Best practice: Start with Ask Mode for plans, then use Code Mode for well-scoped tasks.
5
Best practice: Structure prompts like GitHub Issues, providing detailed context for better results.
6
Best practice: Utilize AGENTS.md for persistent context and 'Best of N' for diverse solutions.
How OpenAI uses Codex
Introduction
Use Cases

Code understanding

Code Modification & Optimization

Improving test coverage

Increasing development velocity

Staying in flow

Exploration & ideation

Best Practices

Start with Ask Mode

Improve dev environment

Structure prompts like GitHub Issues

Use task queue as backlog

AGENTS.md for context

Leverage Best of N

Looking Ahead