How OpenAI Built Its Coding Agent
Show Notes
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:
Intro: The Vision for AI Agents
Codex’s Origin and Naming
Early Prototypes and Agent Form Factors
Cloud Agents: Safety and Security
Prompt Injection and Attack Vectors
PR Merging: Metrics and Transparency
The Future of Code Review and Automation
User Adoption: Internal vs. External Surprises
Multi-Turn Interactions and Product Learnings
Best-of-N, Slot Machine Analogy, and Creativity
Human Taste, Iteration, and Collaboration
AI’s Impact on Software Engineering Careers
Education, CS Degrees, and AI Integration
Prototyping, Hackathons, and Speed to Magic
Legacy Code, Modernization, and Global Adoption
Enterprise, Security, and Air-Gapped Environments
Product Roadmap and Future of Codex
Advice for Founders and Startups
Education Reform and Project-Based Learning
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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Find a16z on LinkedIn
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Follow our host: https://twitter.com/eriktorenberg
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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