Latent Space: The AI Engineer Podcast ChatGPT Codex: The Missing Manual
2221 snips
May 16, 2025 
Josh Ma, a core developer on the ChatGPT Codex team at OpenAI, and Alexander Embiricos, a member leading Codex testing, dive into the origins and future of Codex, the Autonomous Software Engineer. They discuss the shift from traditional pair programming to AI collaboration, exploring best practices for integrating AI in coding. The conversation also touches on balancing control and trust with AI outputs, understanding task durations, and the evolving user experience. They emphasize the significance of user feedback for future enhancements and the complexities of pricing in AI tools.
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Origin Story of ChatGPT Codex
- Alexander Embiricos shared how his prior work on a pair programming tool evolved into building an AI software engineer with reasoning models and tool access.
- Their early experiments led to Codex, giving an agent access to a computer to safely perform software engineering tasks autonomously.
Josh Ma's Path to Codex
- Josh Ma described his journey from founding Airplane to joining OpenAI and contributing to ChatGPT Codex.
- He highlighted the similarity in themes between internal tools and AI-driven software engineering agents.
Use agents.md and Linting
- Use an agents.md file to instruct AI agents with hierarchical and prioritized instructions.
- Gradually invest in linting and formatting to help agents generate consistent and testable code.