The more AI can do, the more we need to ask what it should and shouldn’t do. In this episode, OpenAI researcher Jason Wolfe joins host Andrew Mayne to talk about the Model Spec, the public framework that defines intended model behavior. They discuss how the Model Spec works in practice, including how the chain of command handles conflicts between instructions, and how OpenAI evolves it based on feedback, real-world use, and new model capabilities.

Chapters

00:00 Introduction

01:10 What is the Model Spec?

03:55 How does the Model Spec work in practice?

06:26 Transparency: Where to read the Model Spec & give feedback

07:51 How did the Model Spec originate?

10:02 How does the spec translate into model behavior?

11:26 What is the hierarchy / chain of command?

13:35 Handling edge cases like Santa Claus

17:41 How does the Model Spec evolve over time?

19:59 What happens when models disagree with the spec?

22:05 How do smaller models follow the spec?

23:16 Is chain-of-thought useful for alignment?

24:16 Model Spec vs Anthropic’s Constitution

26:28 What surprised you most?

26:56 How do you define the scope of the spec?

27:44 What is the future of the Model Spec?

31:16 How should developers think about the spec?

34:44 Asimov’s laws vs Model Spec

37:16 Could AI write a Human Spec?

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Healthcare systems around the world are under strain, and both patients and clinicians are feeling the impact. OpenAI's Head of Health Dr. Nate Gross and Karan Singhal, who leads Health AI Research, discuss how AI can help address the biggest challenges. They cover how OpenAI is training models to handle sensitive health questions in collaboration with physicians, and how that foundation is unlocking a new generation of tools for patients, clinicians, and healthcare systems.

Chapters

00:00:38 – Origins of Nate and Karan’s interest in AI and healthcare

00:05:01 – Strategy for building AI tools for clinicians

00:06:57 – How AI models are trained for health use cases

00:10:15 – How OpenAI is able to score well on health evals

00:14:21 – Key challenges deploying AI in healthcare

00:21:05 – Collaboration with hospitals and healthcare systems

00:23:05 – Practical everyday uses of AI health assistants

00:26:43 – Biggest “wow” moment during development

00:28:46 – Feedback from clinicians and early users

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How should advertising work in an AI product? Asad Awan, one of the ad leads at OpenAI, walks through how the company is approaching this decision and why it’s testing ads in ChatGPT at all. He explains how ads are built to stay separate from the model response, keep conversations with ChatGPT private from advertisers, and give people control over their experience.

Chapters

00:00:29 — Mission and principles

00:04:01 — Separation between ads and answers

00:07:31 — Who will see ads

00:08:52 — Internal input and decision-making process

00:11:06 — Controls and how ads will work

00:15:53 — Guardrails for sensitive conversations

00:17:33 — Skepticism about ads

00:20:26 — Helping small businesses

00:24:13 — Future of ads

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OpenAI CFO Sarah Friar and Khosla Ventures founder Vinod Khosla argue the greatest challenges in AI right now are keeping up with demand and making sure more people get the benefit. They unpack what's driving big investments in compute and why this moment is different from other technology cycles — with meaningful advances in health, agents, and robotics still ahead.

Chapters

00:00:00 — What’s the AI story of 2026?

00:07:28 — AI in healthcare

00:12:01 — Scaling compute to match revenue

00:18:05 — Difference between now and dot-com bubble

00:27:41 — Ads in ChatGPT

00:30:05 — Will consumers have more than one AI subscription?

00:36:41 — Winning in enterprise

00:39:44 — How can startups succeed?

00:44:05 — Robotics and beyond

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What does it mean for an AI model to have "personality"? Researcher Christina Kim and product manager Laurentia Romaniuk talk about how OpenAI set out to build a model that delivers on both IQ and EQ, while giving people more flexibility in how ChatGPT responds. They break down what goes into model behavior and why it's an important, but still imperfect blend of art and science.

Chapters:

- 00:00:43 — GPT-5.1 goals and the shift to reasoning models

- 00:02:18 — Differences between GPT-5 and GPT-5.1

- 00:04:55 — Unpacking the model switcher

- 00:07:24 — Understanding user feedback

- 00:08:27 — Measuring progress on emotional intelligence

- 00:10:02 — What is model personality?

- 00:14:25 — Model steerability, bias, and uncertainty

- 00:21:59 — Advantages of memory in ChatGPT

- 00:25:27 — Looking ahead and advice for getting the most out of models

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AI is beginning to change how science gets done. Head of OpenAI for Science Kevin Weil and OpenAI research scientist Alex Lupsasca talk about the early signs of acceleration researchers are seeing with GPT-5—from surfacing literature across fields and languages, to speeding up complex calculations, to designing follow-up experiments. They unpack what’s possible today, what doesn’t work yet, and why the next few years could reshape the trajectory of scientific progress across physics, math, biology and beyond.

Chapters

- 00:00:40 — OpenAI for Science mission

- 00:06:00 — Literature search and intersections across fields

- 00:11:19 — A fusion physicist shows what GPT-5 can do

- 00:15:08 — GPT-5 Pro and black hole symmetries

- 00:19:02 — Getting the most out of the models

- 00:24:33 — OpenAI’s new research paper (https://openai.com/index/accelerating-science-gpt-5/)

- 00:29:59 — Looking ahead to the next 5 years

- 00:32:05 — Will predictions outpace experiments?

- 00:36:43 — The pace of model improvement

- 00:40:31 — What do scientific benchmarks look like?

- 00:44:16 — Fusion and the promise of abundant energy

- 00:48:07 — Closing: Science 2.0 moment

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How will the internet feel when your browser can actually help do things for you? OpenAI’s Ben Goodger and Darin Fisher, whose past work shaped some of the most popular modern browsers, dive into the making of ChatGPT Atlas. They explore how AI changes what a browser can be, from tabs you can talk to, to agents that take over tedious tasks. Learn more about the decisions they made along the way and what’s coming next.

- 00:00:45 What is Atlas?

- 00:03:34 The state of browsers and AI on the web

- 00:13:55 Under the hood: why browsers are hard (OWL, rendering)

- 00:22:00 Building with AI: Codex, cross-language, Swift on Windows

- 00:33:39 Search in Atlas: one box plus model response

- 00:41:28 Favorite features: scrolling tabs and tab search

- 00:45:23 Side Chat in action: summarize, shop, build forms

- 00:46:59 Real-world wins with Agent (cloud bill, medical results)

- 00:52:45 Why Chromium? Compatibility and extensions

- 01:07:57 Five-year vision: an agentic web and reduced toil

- 01:13:11 Power tips and closing remarks

Learn more about OWL

https://openai.com/index/building-chatgpt-atlas/

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Sam Altman and Greg Brockman from OpenAI sit down with Broadcom’s Hock Tan and Charlie Kawwas to discuss their new partnership—and what it means for the future of AI. From custom silicon to global-scale infrastructure, they share how compute innovation is shaping the road to AGI.

00:00 Announcing the partnership

03:06 The scale of AI infrastructure

06:03 Collaboration and innovation in chip design

08:49 Historical context and future vision

12:10 Role of compute in AI development

15:01 Optimizing for specific workloads

18:02 Journey towards AGI

21:00 Future of AI and compute capacity

23:50 Wrap-up and future projects

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