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OpenAI’s Head of ChatGPT: We’re entering a new era of AI (again) | Tibo Sottiaux

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Original episode
PodcastLenny's Podcast: Product | Career | Growth
Publisher/creatorLenny Rachitsky
Published
Shortcast updated

About this episode

Tibo Sottiaux leads ChatGPT and Codex at OpenAI. Under his stewardship, OpenAI has shipped some of its most consequential consumer launches: Codex, ChatGPT Work, and most recently, the new Dots personal agent platform. He joined me at DevDay, hours after his team launched more than 20 new products, to talk about where things are heading.

We discuss:

1. Dots, OpenAI’s new personal AI assistant

2. Why most actions on the internet will soon be taken by agents

3. Why loops, graphs, and fine-tuning agent workflows are a passing phase

4. Which skills are trending up and down in the AI era

5. How Tibo’s Dot warned him about a production outage five minutes before the launch

6. OpenAI’s approach to AI safety

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Brought to you by:

WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more

DX—Engineering intelligence for the AI era

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Episode transcript: https://www.lennysnewsletter.com/p/openais-head-of-chatgpt-were-entering

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Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0

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Where to find Tibo Sottiaux:

• X: https://x.com/thsottiaux

• LinkedIn: https://www.linkedin.com/in/thibault-sottiaux-27195366

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Where to find Lenny:

• Newsletter: https://www.lennysnewsletter.com

• X: https://twitter.com/lennysan

• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/

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In this episode, we cover:

(00:00) Introduction to Tibo Sottiaux

(01:12) How Tibo uses AI in his daily work

(03:10) The vision for always-on AI agents

(06:15) How AI will continue to change work

(07:32) Bringing Codex, ChatGPT, and Dots together

(08:20) The sci-fi inspiration behind the technology

(09:02) Building AI with the community

(10:13) Understanding the Dots structure

(11:34) OpenAI’s open ecosystem and plugin revenue sharing

(13:39) How plugins get discovered and recommended

(14:39) The research behind Dots

(16:20) Where humans will remain valuable

(17:25) Agent fatigue, loneliness, and context switching

(18:55) The pressure to do more with AI

(20:09) An agent that spotted a production outage before a live demo

(21:42) Agent guardrails and connecting multiple devices

(23:25) The skills becoming more valuable in the AI era

(25:56) Advice for people early in their careers

(27:18) How teams build and ship inside OpenAI

(28:59) Autonomy, trust, and learning from mistakes

(30:45) Building for a future where agents dominate internet activity

(32:41) What Tibo has changed his mind about

(33:55) OpenAI’s approach to AI safety and alignment

(36:15) Moving beyond model pickers toward simpler AI

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Referenced:

• OpenAI Dots: https://chatgpt.com/features/dots

• Her on Netflix: https://www.netflix.com/title/70278933

• Star Trek: https://www.imdb.com/title/tt0060028

• Pi: https://pi.ai

• OpenCode: https://opencode.ai

• Notion: https://www.notion.com

• Figma: https://www.figma.com

• OpenClaw: https://openclaw.ai

• Peter Steinberger on X: https://x.com/steipete

• Grok Bot: https://x.ai/bot

• Muse: https://muse.ai

• Instinct: https://instinct.com

• Ahmed Ibrahim on LinkedIn: linkedin.com/in/ahmedibrhm

• The Hugging Face incident and the road ahead: https://openai.com/index/hugging-face-incident-and-the-road-ahead

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Recommended book:

• Neuromancer: https://www.amazon.com/Neuromancer-William-Gibson/dp/0441007465

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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

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Lenny may be an investor in the companies discussed.



To hear more, visit www.lennysnewsletter.com

Episode summary

This AI-generated Shortcast summary may omit nuance. Use the original episode when context or exact wording matters.

Often I look at what people are building and think: you’re not quite getting it. If you really imagined models becoming roughly ten times better within a year—cheaper, faster, seamlessly multimodal—you would build very differently. Most activity online will be carried out by agents, so products need to handle that scale and economics, while we also invest much more in delightful human experiences.

I don’t think the future is everyone fiddling with loops and graphs forever. You want an extremely capable agent that works around the clock, understands your goals and preferences, learns from feedback, and is there through whichever screen—or no screen—you happen to be using. Walk into a room, pick it up in email, send it a text; it should help when needed and disappear when it isn’t. Carrying a laptop around like a brick is not the end state.

The shape of my agent team expands and contracts. As I push the frontier, I create more specialized agents; then a model breakthrough arrives, a larger agent can hold more context and learn, and suddenly I need fewer. We’re starting with one primary dot that knows you deeply, then you’ll be able to create a virtual team with specific roles. I have one for Twitter because that can genuinely be the work of an entire dot.

This should make work more natural, not turn every task into a solitary prompting adventure. I want an agent in the physical space with people: we’re talking, jotting something on a shared surface, it starts building quietly, and we keep having ideas together. We have to reduce configuration fatigue and the pressure to do more just because we can. A week fully disconnected changes how creatively I think; maybe fewer meetings and better rest make you more productive, not less.

The sleeper hit is the open ecosystem. A useful plug-in should earn discovery through retention and quality, not just the right words around it, and partners whose products see real use should share in the economics. We’re opening sign-in, extensions, discovery, and distribution because people will build things we never anticipated. That community feedback is humbling, inspiring, and necessary if we want technology that is actually useful for humans.

The technology is still clunky until, suddenly, it isn’t. Voice has changed my own behavior more than I expected; I dictate and call my agent constantly. I still care deeply about human creativity, taste, kindness, collaboration, and learning fast—roles are blurring, and this is a moment to build. But we also have a responsibility to harden safety, security, guardrails, and monitoring before giving powerful systems broad access. I want the app to reach this essence of simplicity. No model picker, no reasoning-effort homework, no needing a PhD in model pickers. Just talk to it.

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