OpenAI Podcast

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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