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Tibo Sottiaux is one of the engineers who created Codex, and today, he heads up the Core Products & Platform org at OpenAI which also includes Codex. He’s also one of the most public faces of Codex due to his frequent – and generous – usage reset announcements, like this one yesterday.
In this episode of the Pragmatic Engineer Podcast, Tibo and I discuss how Codex was built and continues to be iterated upon. We explore why the Codex CLI is written in Rust and was released as open source, how the harness and models have evolved, and why Codex supports models from multiple providers.
Tibo also shares details about how the OpenAI team uses Codex throughout the software development lifecycle, including code reviews, maintenance, and system rearchitecture. We look into how AI is lowering the cost of changing code – and some interesting side effects of this – the merger of ChatGPT and Codex, and also how Tibo uses the tools in his own work.
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Timestamps
00:00 Intro
07:21 Working at Google
12:41 What drew Tibo to OpenAI
15:19 The early days of Codex
18:20 Why Codex was built in Rust
21:15 Why Codex is open source
25:50 Codex plays nice with other models: why?
32:09 How the harness works
36:44 Harness and model improvements
41:19 The SDLC behind Codex
46:39 Code reviews at Codex
52:09 Maintenance and architecture
56:43 How AI tools expand what engineers can do
1:02:30 The Merge: ChatGPT + Codex
1:07:16 How Tibo uses Codex and ChatGPT
1:10:44 Advice for engineers who want to work in AI
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The Pragmatic Engineer deepdives relevant for this episode:
• How Uber uses AI for development: inside look
• Why Ramp built its own in-house coding agent, Inspect
• “I ship code I don’t read”: with Peter Steinberger, the creator of OpenClaw
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