How OpenAI Built Its Coding Agent

How OpenAI Built Its Coding Agent

OpenAI’s Codex has already shipped hundreds of thousands of pull requests in its first month. But what is it really, and how will coding agents change the future of software?

In this episode, General Partner Anjney Midha goes behind the scenes with one of Codex’s product leads- Alexander Embiricos - to unpack its origin story, why its PR success rate is so high, the safety challenges of autonomous agents, and what this all means for developers, students, and the future of coding.

Timecodes:

0:00 Intro: The Vision for AI Agents

1:25 Codex’s Origin and Naming

3:20 Early Prototypes and Agent Form Factors

6:00 Cloud Agents: Safety and Security

9:40 Prompt Injection and Attack Vectors

12:00 PR Merging: Metrics and Transparency

17:00 The Future of Code Review and Automation

20:00 User Adoption: Internal vs. External Surprises

22:00 Multi-Turn Interactions and Product Learnings

29:30 Best-of-N, Slot Machine Analogy, and Creativity

33:00 Human Taste, Iteration, and Collaboration

40:00 AI’s Impact on Software Engineering Careers

45:00 Education, CS Degrees, and AI Integration

49:00 Prototyping, Hackathons, and Speed to Magic

55:00 Legacy Code, Modernization, and Global Adoption

1:00:00 Enterprise, Security, and Air-Gapped Environments

1:05:00 Product Roadmap and Future of Codex

1:10:00 Advice for Founders and Startups

1:15:00 Education Reform and Project-Based Learning

1:20:00 Hiring, Building, and New Grad Advice

Resources:

Find Alex on X: https://x.com/embirico

Find Anjney on X: https://twitter.com/AnjneyMidha

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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.


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