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The a16z Show

How OpenAI Builds for 800 Million Weekly Users: Model Specialization and Fine-Tuning

The a16z Show

a16z

Science, Innovation, Business, Entrepreneurship, Culture, Disruption, Software Eating The World, Technology

4.41.1K Ratings

🗓️ 28 November 2025

⏱️ 53 minutes

🧾️ Download transcript

Summary

In this episode, a16z GP Martin Casado sits down with Sherwin Wu, Head of Engineering for the OpenAI Platform, to break down how OpenAI organizes its platform across models, pricing, and infrastructure, and how it is shifting from a single general-purpose model to a portfolio of specialized systems, custom fine-tuning options, and node-based agent workflows. They get into why developers tend to stick with a trusted model family, what builds that trust, and why the industry moved past the idea of one model that can do everything. Sherwin also explains the evolution from prompt engineering to context design and how companies use OpenAI’s fine-tuning and RFT APIs to shape model behavior with their own data.

Transcript

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0:00.0

We want ChatGPT as a first-party app. First-party app is a really great way to get 800 million

0:04.9

wow, or whatever now.

0:06.0

10th of the globe, right?

0:20.7

Yeah, yeah, 10% of the globe uses it. Every week, every week. Yeah, even with an open eye, the thinking was that there would be like one model that rose them all. It's like definitely completely changed. It's like, I'm increasing and clear. right out. There will be room for a bunch of specialized models. There will likely be a proliferation of other types of models. Companies just have giant treasure troves of data that they are

0:25.2

sitting on. The big unlock that has happened recently is with the reinforcement fine-tuning. With that

0:29.4

setup, we're now letting you actually run a RL, which allows you to leverage your data way more.

0:35.3

Open AI sells weapons to its own enemies.

0:42.8

Every day, thousands of startups build on OpenAI's API, many trying to compete directly with Chi-GPT.

0:44.1

It's the ultimate platform paradox.

0:46.3

Enable your competitors or lose the ecosystem.

0:49.3

Sherman Wu runs this highwire act.

0:51.5

He leads engineering for OpenAI's developer platform, the API that powers half of Silicon Valley's AI ambitions.

0:58.1

Before OpenAI, he spent six years at Open Door teaching machines to price houses where a single wrong prediction could cost millions.

1:05.2

Today, Sherwin sits down with A16Z general partner Martin Casado to explore something nobody expected,

1:12.4

that the models themselves are becoming anti-dist intermediation technology. You can't abstract them away. And every attempt to

1:18.0

hide them behind software fails because users already know and care which model they're using.

1:23.4

It's changing everything about how platforms work. Sherwood and Martine talk about why OpenAI abandoned the dream of one model to rule

1:30.0

them all, how they priced access to intelligence, and why deterministic workflows might matter

1:35.0

more than pure AI agents.

1:39.3

German, thanks very much for joining. So we're being joined by Sherman Wu.

1:42.4

It'd be great, actually, if you provided the long form of your background as we get into this just for those that may not know you. I mean, I've used Sherman as one at the top AI thought leader, so I've been really looking forward to this. Yeah, yeah, thanks for having me. I'm really excited to be on the podcast. Yeah, so a little bit more of my background. So maybe we can start from present and go backwards. So I currently lead the engineering team for OpenAIs developer platform. So the biggest product in there, of course, is the API.

2:04.2

Is there more for the... from present and go backwards. So I currently lead the engineering team for OpenAI developer platform.

...

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