#define AI Engineer
summary
Career narrative centers on repeated independent study, building a GPU rig for ML experiments, and shifting from web startups to AGI-driven work with a Turing-inspired learning claim rather than rule-writing. Engineering and research integrate tightly, trading compute from research to scale viral launches (1 million users in 5 days, then 100 million users in 5 days), and tooling like Codex writes low double-digit percent of PRs with 24,000 PRs merged in a day cited as evidence that vibe coding and agentic workflows are already changing software engineering.
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chapters (10)
- 0:00Greg Brockman's Journey and the Power of Independent Study
- 2:50Joining Stripe and the Grind of a Startup
- 8:04The Power of Independent Study
- 10:18Journey into Machine Learning and Belief in AGI
- 16:10The Relationship Between Engineering and Research at OpenAI
- 21:11Scaling Challenges and Successes at OpenAI
- 24:32Vibe Coding and the Future of Software Engineering
- 26:06Impact of Codex on Coding Practices
- 29:20Scaling Bottlenecks and Future of AI Infrastructure
- 38:06Evolution of Development Workflow with AGI
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