OpenAI's Tibo Sottiaux on building Codex: why Rust, open source, and agents reshaping code reviews
The Pragmatic Engineer · rss · 2026-09-09
The Pragmatic Engineer podcast interviews Tibo Sottiaux, creator of Codex and head of OpenAI's Core Products & Platform org, on how Codex was built and how OpenAI uses AI across its SDLC.
Key takeaways
- Career arc: A VP abruptly killed his Google Ads project, teaching him to question product-market fit; he reveals Google had an internal "ChatGPT-like" LLM project about a year before OpenAI's launch but never shipped it. He joined OpenAI in 2023 after learning ChatGPT was built and maintained by 20 engineers.
- Engineering choices: Codex CLI is written in Rust despite models being better at Python/TypeScript, targeting millions of cloud instances where performance, security and scale came first. Open source brings trust and contributors, but the team's work sometimes gets copied into other tools before shipping in Codex. Openness is also why Codex supports any model, unlike Claude Code.
- Harness vs models: The harness stays slightly ahead of the latest model, providing guardrails and steerability "crutches" that shrink as models improve.
- Inside OpenAI: Codex is plugged into Slack, every doc and all code; the team works in public channels with broad permissions.
- Industry outlook: Cloud dev environments may resurge as agents configure machines; correctness checks and security reviews will be automated; dependency upgrades take hours and multi-year re-architectures take days; late-night "in the zone" coding sessions are history.
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