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.
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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
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