Uncapped with Jack Altman
· Bret Taylor
[00:00:00] S1: Yeah, that’s right. It feels like there’s too much capital available. Put another way, there’s obviously going to be competition in meaningful markets. It feels like there’s too many competitors that don’t necessarily have strong differentiation. I think it’s probably healthy though. There will be a culling as the market progresses. But it does feel quite competitive. I’ll give you a quick glimpse of the past couple years. We’ve had remarkable growth at Sierra. We closed $100 million in seven quarters, $150 million in eight quarters, which has exceeded my expectations. But this past year has felt like an inflection point. The first year of our company’s history, we would often go in and explain to clients what an “agent” was. The term was novel and it was part of our marketing, explaining what an agent was. Number two, people would be talking about, “Hey, AI is maybe non-deterministic.” They wouldn’t necessarily use that word, but that’s what they would be describing: “How can we trust this technology directly engaging with our customers or consumers? What are the risks?” Now the conversation is, “Clearly we need this yesterday.” Over a quarter of our companies have $10 billion or more in revenue. We’re talking about big companies. We serve most of the Fortune 20, as an example. These are big companies coming in saying, “We’ve evaluated, we know what we want. We’ve heard of you, we’ve done all this evaluation. Here’s an RFP. Let’s go.” As a consequence, because the market has matured—illustrated by the existence of things like RFPs—you end up in more competitive conversations. And then it’s a question of, why Sierra? I’m happy to talk more about that. Obviously I’d love to as an entrepreneur. I could tell you all the reasons we’re the greatest. But you end up in this world where you’re not explaining what the word “agent” is anymore. You’re saying, “Here’s why we’re the right partner for you”, which is a very different conversation.
· Jack Altman, Bret Taylor
[00:00:00] S0: So they’re like, “Yeah, I’m bought in on an agent. So why is it Sierra?” What have you found is the most important thing that makes you win? [00:00:00] S1: One thing we really did uniquely at Sierra—the reason why over a quarter of our customers have over $10 billion in revenue—is we’ve tried to serve more complex, more regulated industries. We serve most of the US healthcare insurance market, as an example. We serve US banks, Spanish banks, UK banks. These are companies that, if you know the industry, are regulated by everybody. It’s easy to make a demo in AI. That’s why you can go on X and see a thousand demos. Demos are cheap. But making an agent industrial-grade is hard. We’ve really uniquely been able to make agents that can have complex conversations. The other thing we do really uniquely is, in addition to having a really easy-to-use product, we help companies move faster. We went live with Cigna in two months. [00:00:00] S0: That’s crazy. [00:00:00] S1: Which is remarkable. [00:00:00] S0: How big is Cigna? [00:00:00] S1: It’s a Fortune 20 healthcare company. I was on stage with Sachin, who runs their AI practice, at the HLTH conference, and he was talking about this. Part of that is, how can you show up? We’re really great at AI, Cigna’s really great at healthcare. How do you bring those two together to move extremely fast? So for a lot of our clients, the reason they bring us on is, can you help us move quickly? That requires knowledge of AI, knowledge of business. I think we show up with a greater sense of maturity there.
· Bret Taylor, Jack Altman
[00:00:00] S1: It’s a Fortune 20 healthcare company. I was on stage with Sachin, who runs their AI practice, at the HLTH conference, and he was talking about this. Part of that is, how can you show up? We’re really great at AI, Cigna’s really great at healthcare. How do you bring those two together to move extremely fast? So for a lot of our clients, the reason they bring us on is, can you help us move quickly? That requires knowledge of AI, knowledge of business. I think we show up with a greater sense of maturity there. [00:00:00] S0: You mentioned that the pricing scheme was one of the difficult things in the past era. We don’t have to belabor it but obviously, going from just buying a license to a cloud subscription… and now usage-based is the future. What are you feeling is important as you’ve created, and probably continue to iterate, on pricing? What are the important levers for agent companies? [00:00:00] S1: We do something specific at Sierra that I’m an evangelist for, which is outcomes-based pricing. It turns out in our industry, the outcome is usually well-defined. In a service context, the outcome is: could the agent solve the problem? In a sales context—we do a lot of sales agents as well—could it make the sale? Your companies paid your salespeople commissions, right? [00:00:00] S0: Yeah.
· Jack Altman, Bret Taylor
[00:00:00] S0: Yeah. [00:00:00] S1: If you can measure the outcome, you want to incentivize the outcome. The interesting thing about agents is they’re autonomous, or can be autonomous. So if the outcome is measurable and trackable, what an interesting opportunity to actually charge for that. Look at the history of software. Let’s take advertising. We went from impression-based ads to cost-per-click ads to now, for mobile ads, you can do pay-per-install. At least that’s my understanding. Then you had enterprise software where you went from on-premises licenses to subscription-based software. Could outcome-based software be the next? What’s so neat about that is, for a company, what an interesting and accountable business model. There are some challenges to it because you obviously put some revenue at risk. But I don’t think most advertising tech people would say CPC ads put revenue at risk. It’s the opposite. The closer you get to the outcome, the more valuable it is for the companies. They’re actually willing to invest in it. My view is that, to the degree agents have a measurable outcome, outcome-based pricing feels like the secular business model for agents. I think it’s both disruptive and a huge step forward. [00:00:00] S0: Why is it better than token-based? If those are the two reasonable options now, why is an outcome better than token-based, even over the long term?
· Bret Taylor
[00:00:00] S1: Let’s say you had an AI agent to generate leads for your sales team. What do you care about? You care about the number and quality of the leads. You really don’t care how many tokens the model uses. In fact, it’s not obvious to me that there’s a correlation between used tokens and leads generated. In the same way, there’s no correlation in a SaaS product between their cost to serve and the quality of the product. You could have a really good engineer write it or a really bad engineer write it. What you really care about is the quality of the product. The reason why I don’t think token-based makes sense is that it’s charging for an input that is uncorrelated with the output that your clients actually care about. I’m a huge believer in applied AI, but I actually define applied AI as: can you describe your value proposition without mentioning models? Because if you think about, “Hey, we can answer the phone and solve 80% of phone calls without human intervention, with a CSAT score of 4.8 out of five”, you don’t mention models. Models are an input to that, not an output. If you have to mention token utilization, it’s probably a tool. It’s not an application of AI. It’s just a tool around AI. The closer you get to a business outcome, you should charge for the business outcome, which is uncorrelated with tokens. I also think it’s almost a measure of whether you’re actually an applied AI company, if you don’t have to talk about tokens.
· Jack Altman
[00:00:00] S0: Do you think there will be markets where things get so competitive that people have to price based on cost rather than value? Or maybe the other format would be where you can’t describe the outcome cleanly. For example with coding, which we both probably think is super important, it’s a little harder to say what the outcome is there versus usage. What are the conditions where tokens do make sense?