Uncapped with Jack Altman
· Bret Taylor
[00:00:00] S1: There’s two almost independent areas of investment. They’re not independent, but they’re very different. One is the product and one is our go-to-market and partnership model. They’re both really intentionally built. On the product side, we’ve tried to balance ease of use and extensibility. When you serve really large companies that have been around for 200 years, you need to work with mainframes, you need to work with a thousand different systems. You’ve done 10 acquisitions. Enterprises are messy. That’s why most enterprise software designed for larger companies tends to be quite extensible. Often that extensibility comes at a cost, which is: is it easy to get up and running? As a product designer, one of the things I’ve spent a lot of time thinking about is: we’re trying to have our cake and eat it too. Can you go live in two months and still be maximally extensible? I’m really proud of the product that we built. Some of that is born from experience of what extensibility means. We have an opinionated view of what it means and have been able to accommodate some fairly exotic deployment requests and still do it fast. That’s really unique. The second thing is our go-to-market and partnership model. We knew when we started the company that we wanted to work with the largest companies in the world. Not only, but we wanted to be able to work with the largest companies in the world and we’ve focused on that. As a consequence, we have a really unique partnership model. There’s a fashionable thing to talk about: forward-deployed engineering in Silicon Valley. We don’t call it that, and it’s a very unique model because it’s not all about technology. Most of our clients build and maintain their agents themselves. It’s pretty easy to do. But we show up and we help you be successful. We’ll just show up. We’re not going to let you fail. I think that is very different. Because we have this outcomes-based pricing model, we don’t get paid unless it works.
· Jack Altman, Bret Taylor
[00:00:00] S0: How much of that is technical versus change management? [00:00:00] S1: It’s a mix of both. I don’t know if it’s 50-50. [00:00:00] S0: Do you think of it as two people or one person who does both? [00:00:00] S1: We have a mix of roles. We’ve evolved that. We try to hire really technical people in all roles though because part of our secret is we want to be your trusted partner in AI. So you want the person who is working with you every day to be the most knowledgeable AI person. [00:00:00] S0: It’s like a forward-deployed change management engineer. [00:00:00] S1: Yeah, exactly. What’s really neat about it, if you’re a really talented technical person who wants to transform an industry, you can do it at Sierra. We’re working with most of the healthcare insurance companies. If you want to change healthcare costs, what a cool vantage point to do it from. We’ve been able to attract some really remarkable people. [00:00:00] S0: You said that it’s not just support agents now. What else are you finding shoots in?
· Bret Taylor
[00:00:00] S1: I’ll give you one of my favorite relationships: Rocket. Based in Detroit, remarkable story. Their founder’s done more for Detroit than I think any one person’s done for any city. Remarkable company. They own Redfin, which is a home search site, Rocket Mortgage, which is the number one consumer mortgage originator in the country. They recently bought a mortgage servicing firm as well. You can go to redfin.com and use an AI agent to search for a house. You can go to rocket.com and finance that house with an AI agent. And then with the acquisition of the mortgage servicing firm, when you’re servicing your mortgage, you’ll talk on the phone with an AI agent as well. Everything from finding a house to originating the mortgage to servicing that mortgage, I think that’s pretty cool. They have an amazing CTO named Shawn Malhotra, pretty visionary. I love their CEO Varun too. It’s everything from finding a house all the way through servicing. It’s what we believe a lot of businesses will do, look at their entire customer lifecycle from purchase consideration—which is a fancy way of saying browsing. I think homes are probably one of the more considered purchases you could do—through executing the purchase, through having issues with it, all the way through retention. For a lot of our telecommunications customers, their AI agent is actually doing negotiations. You’ve probably negotiated your cable bill at some point. Our agents are doing billions of dollars of negotiations for everything from satellite radio subscriptions to cable television subscriptions. It’s pretty cool. Over a billion dollars of mortgage folders a month.
· Jack Altman, Bret Taylor
[00:00:00] S0: Basically all transactional communications eventually. [00:00:00] S1: The way I think about it is: a website is a technology, but your .com, the one with your brand at the top, is your website. We’re doing that for agents. Agents will do a lot of things. The one with your brand at the top that your customers go to, whether it’s buying or servicing, we’d like to help you make that. As agents go, they often interact with other agents. If you think about a home and auto insurance company, you may have a claim adjudication agent that’s quite complicated. Our agent that’s having the phone conversation when you’re in a fender bender will interact with that. But it is almost the intersection of all of that technology because it’s your front door. Our whole hypothesis is that every company needed a website in 1997. Every company needs an agent in 2027. We want to be that company. [00:00:00] S0: What’s the nuance about agent builders though? I know you have a view that just being a generic agent builder is not the right thing.
· Bret Taylor
[00:00:00] S1: I’ve been surprised by how many large incumbent enterprise software companies’ first foray into AI was an agent-building tool. It just feels like an inevitable commodity in my mind. Maybe making a website was hard in 1995, but today there’s a million ways to make a website. Most of them are open source. You have cool companies like Vercel, which I love, but it’s not like there’s a huge market for this stuff. In practice, I think the same will happen with agent building. OpenAI will have a great tool. Probably all the foundation model companies will. There’ll be open source packages like LangChain and LangGraph. The idea that you have the right to win there… I don’t know if anyone has the right to win there because it’s just a horizontal technology and I believe in open source. It’s going to become a commodity. My belief is that value is really going to be in agents that do things, hiring those agents and purchasing those agents for what they do. I believe in companies like Sierra, I believe in companies like Harvey. I really admire what they do. They have an agent that will do an antitrust review. I think there’ll be a finance agent that audits your financials. There’ll be one that helps you onboard a supply chain vendor. Just think about onboarding a new vendor. There’s a procurement process, a legal process, a contract review process. Whether or not it’s completely autonomous or human-in-the-loop, all of that could be augmented by AI. That’s a product. Agent building’s not a product. Agent building is a technology.
· Jack Altman
[00:00:00] S0: Speaking of the platforms, aside from being the founder of Sierra, you’re also on the board of OpenAI. You’re the chairman there. I wanted to ask you specifically about Codex. Over the last couple weeks, it’s been unbelievable. It’s like a curtain just came down. Did you expect this? Did you think that what has happened here was going to happen? When did you start to have an inkling that code was going to go vertical like this?