Bret Taylor on AI and the Future of Software | Ep. 42

Transcript

Clearly in three years, we could talk about what are the best practices to set up a software team that's optimized for this technology and we'll know what those best practices are. And right now we're just figuring them out in real time. And my hypothesis is the companies that figure it out first will move the fastest. It's fascinating to me. [SPEAKER_01] Brett, thanks a bunch for doing this with me. I'm super excited for it. [SPEAKER_01] Thanks for having me. So you're one of the best people to ask this following question, which is, what is your view on the SaaSpocalypse, if we can call it that? [SPEAKER_01] Sasmageddon. [SPEAKER_01] Sasmageddon. So it's, in public markets, all of these companies are trading way down. You go on X and everybody's talking about how software can now be written in two seconds. And so there's no moats anymore in software. And so it's leading a lot of people to ask, where does durability come from? And so I just wanted to start with this topic because you've built your own companies. You've been the co-CEO at Salesforce. You're now building one of the fastest growing AI startups there is. You're on the board of OpenAI. How do you see software in this moment on February 26th? [SPEAKER_00] So first, I think the market isn't necessarily reflecting an indictment of individual companies. I think it's more of a broad view of the bigger questions you were saying, i.e. every software stock is down. But I don't think that means every software company is equally disadvantaged. It's just anxiety about the future. I think it's a few things. We can talk about defensibility broadly. I think it's a really interesting question. I think if you look at the history of enterprise software, a lot of the value has gone to the big systems of record. So ERP systems, CRM systems, the core databases that Oracle famously powered in the early days of software. And then you end up with all the software as a service companies, SAP, Workday, Salesforce, ServiceNow. If you look at what a system of record is, it's essentially a database with a bunch of workflows around it. And to date, those workflows are manipulated by people clicking on buttons in a web browser or filling out forms. If you had to synthesize pre-AI, why were those businesses so good? Was it the source of truth thing and that there had to be some immutable thing? And so the database row, is that what it was? Was it the ecosystem of the integrations? What do you attribute the success of systems of record to? [SPEAKER_00] So I think the reason why a system of record has always been the most valuable is it is the anchor tenant of your technology deployments. You know, if you wanted to create a workflow for a quote to cash or something like that, you had to integrate with your ERP system and your CRM system. So as a consequence, the companies that owned those databases could either develop that functionality as an add-on, a new SKU, or if it was a third-party company, they would often be part of the ecosystem like Salesforce's AppExchange or whatever the marketplace equivalent is for SAP. And so you ended up with a lot of value in those systems, which meant switching costs were really high because that system plus all the partners that integrated with it created gravity and high switching costs. And then similarly, you just end up accruing a lot of value either by collecting rent from your ecosystem or developing premium add-ons on top. And so it became the sun and the solar system for each of the different lines of business that these systems of record were sold into. And then you'd end up where you'd get scale. So you'd get sales capacity scale, so the larger you grow, the more salespeople you have, you can reach more and more people. Then there's the proverb, no one gets fired for buying IBM, which is obviously a somewhat dated expression, but it was, hey, if you're going to put in a new ERP system, no one's going to blame you for choosing SAP because everyone chose SAP. If you choose something new and it doesn't work perfectly, big trouble. Then you're the, so all those things accrue. [SPEAKER_00] But then the question is now that all of a sudden a lot of those start getting chipped away with AI agents, you know, first, could you just code it in a weekend? So does it change build versus buy? So that's one risk. Does it change when you come up on that renewal? Are you going to make a different decision? Secondly, I actually think the more fundamental thing is what is the role of that system of record if AI agents are doing most of the work? So rather than people clicking around on an ERP system to onboard a vendor, if you just delegate to an AI agent to do it, all of that is invisible to you. And all of a sudden it goes from being an application to a database. Right. Similarly, if you imagine a CRM system and rather than having people staring at it all day to manage their leads, contacts, and opportunities, if you just say, hey, generate me some leads. In other words, does a system of record have a place in the world if nobody logs into it? And it does. [SPEAKER_00] But the real question is how valuable is it? How important is it? You know, when you go back to my metaphor on the solar system here, how important is that gravity versus the gravity of the agents running around it? And it's really interesting because if you imagine you're running a sales team, how much do you value the database of leads versus the agent that generates the leads? And three years ago, those are the same thing. But now you're, gosh, I actually probably care more about the lead generation and how it's stored and tracked is actually a more tactical part of it. So there's all sorts, and that's true of every system of record. This isn't, I just know CRM systems pretty well. And if you look at ITSM, which is where IT plays, or ERP systems, which is Workday, SAP, Oracle, all these questions start coming up. And so what's interesting, though, is I think every single one of those companies could transform and benefit from AI. I really do believe that. You know, you saw what Microsoft did in the cloud transformation, and they went from being dependent on Windows revenue to going to Active Directory, Azure and all those other things. But it was really awkward. I think folks like you and me back in the day used to probably dismiss Microsoft. I mean, I certainly did. [SPEAKER_00] And if you look at ITSM, which is now plays or ERP systems, which is Workday, SAP, Oracle, et cetera, all these questions start coming up. [SPEAKER_00] And so what's interesting, though, is I think every single one of those companies could transform and benefit from AI. [SPEAKER_00] I really do believe that. [SPEAKER_00] You saw what Microsoft did in the cloud transformation, and they went from being dependent on Windows revenue to going to Active Directory, Azure and all those other things. [SPEAKER_00] But it was really awkward. [SPEAKER_00] I think folks like you and me back in the day used to probably dismiss Microsoft. [SPEAKER_00] I certainly did. [SPEAKER_00] I didn't foresee them becoming as powerful and strong as they are today, but it was good leadership, good technology. [SPEAKER_00] But I don't think the market knows who is Siebel Systems and who is Microsoft in this landscape of software companies. [SPEAKER_00] Probably no one knows what Siebel Systems was. That was the company that Salesforce beat to become the cloud CRM. Yeah. [SPEAKER_01] So can you actually develop this ecosystem of agents around your platform? And will it become more valuable than the platform you had? And then on top of it, the existential risk of whether the value of software just going to zero? I don't necessarily believe that. But you look at all of that, if you're just an investor in public markets, you're like, I'm going to sit on the sidelines. Yeah, it makes sense. I'm going to let the market play out a little bit. And I think that's what's going on. Yeah, I mean, you can never know for sure who's going to turn into the next Microsoft, but you can try to think about who has the structural ability to expand. [SPEAKER_01] Like, who's got the right with customers to make the expansions and then which products will be easier? [SPEAKER_01] So in the database question, is it easier for today's databases to build agents on top? Or is it easier for a modern agent to go say, well, I'm going to build a database at some point because I can do that and I've got the customer relationship? And how do you think about what creates the rights to expand? I think all the incumbents have a right to win in a lot of ways. [SPEAKER_00] You know, in the same way we talked about why a system of record is powerful. [SPEAKER_00] I think you could say the same logic for all the agents right on top. The dynamic that plays out, though, not just with AI, is when a new technology comes out, like the web browser or the smartphone, rarely is the expertise on how to do exceptional things with that technology at the incumbents. So first, there's this thing in enterprise software, there's a phrase called best of breed and best of platform. Best of platform means, hey, we're a Microsoft shop. We just buy Microsoft stuff. And it sounds silly, but actually there's a lot of logic to it. Like, A, you get good procurement leverage. B, everything works together. You don't have to deal with a ton of people. There's probably some benefits. What ends up happening when new technologies come out is the pendulum swing from best of platform back to best of breed, because when the web browser came out. It's much easier to get a 10x experience. [SPEAKER_01] A hundred percent. And also just think of the pre and post web browser enterprise software. [SPEAKER_00] Like, you're running client server Windows software. And it's a completely different skill set to make a web application, as you and I know. Totally. And so at the time, there's this window of time where best of breed competitors are light years ahead of the incumbents. That's right. And it's a race. So can the best of breed upstarts turn into scale before the incumbents figure out the technology? And that's what's going on right now. So I would argue very few of the incumbents have any credible AI technology. But they will. It's inevitable they will. [SPEAKER_01] Why is that? What's the real reason for it? [SPEAKER_01] Because I see these companies that have infinite resources, roughly speaking. [SPEAKER_01] They ought to be able to hire who they want. [SPEAKER_01] They ought to know what the products could look like. [SPEAKER_01] They ought to be able to try them. [SPEAKER_01] Why is it so hard for legacy companies to catch up quickly versus an AI startup with 50 engineers seems to outperform teams that are 10 times bigger at a big company. [SPEAKER_01] Is it cultural? Is it systems? [SPEAKER_01] I like the phrase strategy tech. [SPEAKER_01] I don't remember who to attribute that to. [SPEAKER_01] We could pull up ChatGPT and ask. I think the idea is in these moments of big platform shifts, what were your strengths can become weaknesses. So let's just take Siebel Systems in the birth of the web browser. They have an on-premises CRM system. When you say, okay, let's compete with this cloud-native CRM system in Salesforce, you start to say, well, I don't want to start from scratch. Like, we've got all these assets. So how do we do it in a way that takes advantage of all of our assets? And so all of a sudden, you're like, okay, let's not just build a great product. Let's transition from this product to that product. And what if someone wants on-premises too? And that's our strength. We should play to that strength. And you start making all these decisions that sound really clever because you're playing to your strengths. [SPEAKER_00] And in practice, if the technology wave is bigger than the category, which I think the web was, as an example, you end up chipping away at doing a pure play value proposition. It can also happen with business models, though. So in that time, you'd have perpetual licensed software and moving to software as a service. That's a huge change for a business to make. For your customers, it goes from being CapEx to OpEx. For you as a company, it changes ratable revenue. I mean, Adobe, Shantanu did this at Adobe. Very few companies can make that transition. [SPEAKER_00] Yeah. And you have to sell it differently. [SPEAKER_00] You have to compensate salespeople differently. [SPEAKER_00] It can also happen with business models, though. So in that time, you'd have perpetual licensed software and moving to software as a service. That's a huge change for a business to make. For your customers, it goes from being CapEx to OpEx. For you as a company, it changes ratable revenue. Adobe, Shantanu did this at Adobe. Very few companies can make that transition. [SPEAKER_00] And you have to sell it differently. You have to compensate salespeople differently. [SPEAKER_00] Revenue recognition is different. So you have the product strategy tax. You have the business model strategy tax. You have even incentives of salespeople. There's a strategy tax because you don't want to just have your business collapse overnight. So you can't just pivot. It's easy for a clever Silicon Valley company to pivot. I'm like, yeah, if you're a public company, you have to go in front of your investors every single quarter and be like, "Hey, guys, I know our revenue just went off a cliff, but trust me, it's going to turn around next quarter." Like, you don't survive that. So you just compound all those things. And all of a sudden, you're like, why does a 50-person company succeed? Well, they have none of those. All of the advantages that you had all of a sudden become anchors that are holding you back from actually doing the right thing. And that's why I always like to remind our company, Sierra, that the wave that we're riding of large language models and this next generation of AI is greater than any company riding it. And so, don't fight AI. It's going to happen with or without us. And if you go back to the Internet, if we were talking in 1995, we'd probably be like, search is a category, e-commerce is a category. Digital payments, that's definitely going to happen. I don't know which. Google hadn't been founded yet. I guess Amazon probably had around then. PayPal, probably not founded yet. The categories are obvious. The categories are whether or not any of those founders existed, all of the would-be winners. And it's the same now. It is the same now. So everyone knows what's going to happen. And it's like you're competing for the privilege of winning. And so in a world where the technology is that remarkably powerful, the strengths of the incumbents start to wither in the face of the technical change. And that's why you tend to get new great companies. The companies that are enduring tend to be created in platform shifts more than any other time. I'd actually be curious on this topic of there's these obvious things. And within AI, I would say, not to discredit your insight, but support, I would count as an obvious thing, in a good way. Yeah. Like, it looks like it works. And you did it early enough that you were able to get to a place at the right time. But other people did, too. And so in some ways, I'm like, you have been playing in a very blue ocean, wide field. The incumbents are categorically different. And so it seems inevitable that we're going to have agents doing support. And then on the other side, a lot of other companies see the same thing. A lot of other people have been building it. So before getting into the specifics, I'm just curious, experientially, day-to-day, does your operation of the company feel competitive or wide open? It feels competitive and it feels like a really big market. So it doesn't feel particularly demand constrained, which is a really great feeling as a fellow entrepreneur. You don't get to. So you feel like there's lots of demand and there's a contest with each situation? Yeah, that's right. The way it feels, there's too much capital available. [SPEAKER_01] 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. I think that there will be a culling as the market progresses. But it does feel quite competitive. I'll just give you a quick glimpse of the past couple years. So 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. So in the first year of our company's history, we would often go in and be explaining 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 would be 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. I mentioned this to you earlier, but over a quarter of our companies have $10 billion or more in revenues. We're talking big companies. We serve most of the Fortune 20, as an example. And so these are big companies that are coming in and saying, we've evaluated it. We know what we want. We've heard of you. We've done all this evaluation. Here's an RFP. Let's go. And as a consequence, because the market has matured and by the illustration of the existence of things like RFPs, you end up in more competitive conversations. And then it's a question of, why Sierra? Why Sierra? And I'm happy to talk more about that. Obviously, 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. Let's go. And as a consequence, because the market has matured and by the illustration of the existence of things like RFPs, you end up in more competitive conversations. And then it's a question of why Sierra? Why Sierra? And I'm happy to talk more about that. Obviously, I love to. 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. Well, 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? [SPEAKER_01] So one thing we really did uniquely at Sierra, the reason why over a quarter of our customers have over $10 billion revenue is we've tried to serve more complex, more regulated industries. We want to serve most of the U.S. healthcare insurance market, as an example. And we serve U.S. banks, Spanish banks, U.K. banks. [SPEAKER_00] And these are companies that, if you know the industry, they're regulated by everybody. Yeah, yeah. It's easy to make a demo on AI. Why, you can go on X and just see a thousand demos. [SPEAKER_01] And demos are cheap. But making an agent industrial grade is hard. And we've really uniquely been able to make agents that can actually have complex conversations. The other thing that 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. That's crazy. Which is remarkable. Yeah. I mean, how big is Cigna? It's a Fortune 20 healthcare company. And I was on stage with Sitchin, who runs our AI practice there at the health conference, and he was talking about this. [SPEAKER_01] And part of that is how can you show up at a, we're really great at AI. Cigna's really great at healthcare. How do you bring those two together to move extremely fast? And so for a lot of our clients, the reason they bring us on is, can you help us move quickly? And that requires knowledge of AI and knowledge of business. And I think we show up with a greater sense of maturity there. You mentioned that the pricing scheme was one of the difficult things in the past. [SPEAKER_00] 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 as important in as you have created and probably continue to iterate on pricing? What are the important levers for agent companies? We do something specific at Sierra that I'm an evangelist for, which is outcomes-based pricing. So it turns out in our industry, the outcome is usually well-defined. So in a service context, could the agent solve the problem? [SPEAKER_00] In a sales context, we do a lot of sales agents as well. Could it make the sale? You probably your company has paid your salespeople commissions, right? That's where you can measure the outcome. You want to incentivize the outcome. [SPEAKER_00] The interesting thing about agents is they're autonomous or can be autonomous. And so if the outcome is measurable and trackable, what an interesting opportunity to actually charge for that. [SPEAKER_00] And if you 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. [SPEAKER_00] And then you had enterprise software. You went from on-premises licenses to subscription-based software. And could outcome-based software be the next? [SPEAKER_00] And what's so neat about that is, for a company, what an interesting and accountable business model. And I think there's 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, right? Because the closer you get to the outcome, the more valuable it is for the company. So they're actually willing to invest in it. [SPEAKER_00] And so my view is, to the degree agents have a measurable outcome, outcome-based pricing feels like the secular business model for agents. And I think it's both disruptive and a huge step forward. [SPEAKER_00] Why is it better than token-based? So if those are the two reasonable options now, why is an outcome better than token-based, even over the long term? [SPEAKER_01] 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, right? And so 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. And in fact, in the same way, there's no correlation in a SaaS product between the 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. But you really could have the quality of the product. The reason why I don't think token-based makes sense is it's charging for an input that is uncorrelated with the output that your clients actually care about. And I think this is actually, 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 5. That's, you don't mention models. Models are an input to that, not output. If you have to mention token utilization, it's probably a tool. It's probably not applied AI. It's not an application of AI. It's just a tool around AI. And I actually think that the closer you get to a business outcome, it's actually you should charge for the business outcome, which is uncorrelated with tokens. Because if you think about it, we can answer the phone and solve 80% of phone calls without human intervention with a CSAT score of 4.8 out of 5. That's something you don't mention models. Models are an input to that, but on output. If you have to mention token utilization, it's probably a tool. It's probably not an applied AI. It's not an application of AI. It's just a tool around AI. And I actually think that the closer you get to a business outcome, you should charge for the business outcome, which is uncorrelated with tokens. And 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. Do you think that there will be markets either where things get so competitive that people have to price based off of cost rather than value? Could that happen? Or maybe the other format for it would be if you can't describe the outcome plainly. [SPEAKER_01] Like, for example, coding, which we probably think is super important, obviously. It's a little harder to say what the outcome is there versus usage or something. So what are the conditions where tokens do make sense? [SPEAKER_01] Yeah. [SPEAKER_01] So there was this old Apple site where they had Apple folklore kind of thing. And I think there was this one boss at Apple that made people thought of for him saying, how many lines of code did you write? And this engineer infamously wrote a negative number because he had just refactored a bunch of stuff. It's the good historical analog for why tokens don't matter. Because he was doing it to say, you know, fuck the man. Your lines of code has nothing to do with my value. And he was doing it to piss off a middle manager to make that point. But it's interesting that in the world of software engineering, people truly understand that the customers right now are software engineers who intimately understand these models. So there's a customer product market fit aspect to it. It's a nuanced point, but I'll say where I see it might happen. Right now, if you're evaluating a software engineering agent, a coding agent, you're probably comparing it to the cost of a software engineer. If you fast forward five years, you probably will be comparing it to the cost of other coding agents. So I think the second order effect as AI becomes prevalent is your reference point for its value will change. The thing I would say is that's true where you're thinking about a cost center, but if you're thinking about top line revenue growth, that doesn't necessarily apply. And if you go to my example of an AI agent generating leads for your sales team, depending on what you're selling, a lead is a lead. And you probably will value quantity and quality of leads. And there's a math equation and that probably will remain independent of token costs. And so I think a large part of AI is productivity and reducing costs. There's a big part of it, but the other side of it is outcomes. So could you imagine a world in four or five years where there's one coding agent that can actually produce something of greater value for your company? Will you value that or just look at the token cost? I think probably you'll start looking for value. Will they all be the same? I don't know. Well, I was just reflecting that over the past year, there have been all these articles about whether AI progress has slowed down. And then in our world of software engineering, it's been the opposite. Every new model comes out and you're like, oh my gosh, it can write increasingly complex software. My theory of that is it depends on what you're testing. So if you're using ChatGPT for trip planning, you probably haven't seen a material change over the past year and a half because you reached sufficient intelligence for trip planning a long time ago. If you're using an AI to write Rust code, Codex is mind blowing right now. So I think one of the interesting things when I think about second, third order effects and the progress of AI is knowing where you'll pass the horizon where every model is sufficient in that task. And then there'll be some things where the frontier continues to move. Yeah. It's hard to imagine, but we're in a crazy time. Where are we at with support agents right now? Are there still edge cases and last mile things that AI can't do? [SPEAKER_01] Yeah, we are though. So I imagine a lot of the technical problems as opposed to product problems will become easier, but there are still a lot of them. [SPEAKER_01] So we at Sierra support most spoken languages in the world. And if you want to support Cantonese and Tagalog, most of the good voice models don't come from the traditional Western model companies. Similarly, one of our clients is SafeLight Autoglass. So it's roadside assistance. And it turns out that car horns, background noise, kids talking, are actually all fairly hard problems to solve. And even in some of the advanced voice model stuff, if you are in a noisy environment, it constantly thinks it's being interrupted. So you end up having to build proprietary voice activity detection, multiple speaker detection, all these other things. We develop all this technology because we need to be the best now. And I think we are the best now. And okay, that's probably going to be a commodity in two years, one year from now. I mean, who knows? You have to do it because you need to be the best at every stage of your company's existence. And I think the way we think about the world is we have a product called Agent Studio or Agent OS. And in three years, we'll judge ourselves by our product. Right now our clients judge us by the technology. But if you go back to 1996, I remember when Netscape had a web server and Apache was new. No one cares how you serve web pages now. It's a commodity. But at the time, that was what you sold. And now you have increasingly higher order website building like Shopify. So I just think the AI agent market is going to take that progression. We're going from a tech-centric sales cycle to a product-centric sales cycle. [SPEAKER_00] It's interesting that you're obviously having to be the best at something that you know is going to get commoditized. Yeah. But if you go back to 1996, I remember when Netscape had a web server and Apache was new and done it. No one cares how you serve web pages now. It's a commodity. But at the time, that was what you sold. And now you have increasingly higher order website building like Shopify. So I just think the AI agent market is going to take that progression. We're going from a tech-centric sales cycle to a product-centric sales cycle. It's interesting that you're obviously having to be the best at something that you know is going to get commoditized. [SPEAKER_01] I mean, for that to be true, you just have to be in the middle of an insane rate of change. But that means you have teams who are putting a lot of their life force for two years into something that everybody knows is just for two years, but it still matters nonetheless. It's crazy. I mean, if you look at traditional enterprise software, consumers a little different. But you think about you're building up this asset, your intellectual property is a fancy name for it. It's a platform that we're building. And we took so many years to build it. It's got all these features. And now you're like, I'm building this and I'm 100% certain we'll throw it away in the next 40 months. It's the same castle. But I have to build it because if I don't, I can't serve the bank that has big business in Hong Kong or whatever it might be where we need Cantonese support. So that is the reality right now. And so I actually think I've been thinking a lot about this because I think it was Toby Lukey who said something provocative around when generating the code is easy, it's almost like the system and the prompts that are actually the durable asset. Put another way, could you terraform your software from scratch? It's the prompts that led to it. I do think that is the software of the future in a lot of ways where how do you encode the infinite number of little product decisions that you made? Because so much of that is encoded in code today. I mean, if you think about a product requirements document versus the code, what percentage of the emergent product that comes out of it is in code? Almost 90%. A lot of the little details are in there. I think software companies of the future and the products that they make are just going to take a really different shape in the future. And I'm so excited to be a part of it. I mean, I think it's really fascinating. I think there's something really interesting about AI impacting the software engineering industry almost first and most because we're disrupting the craft of making what we're building in real time. And it's fascinating. It's a fascinating time. I think there's a prevailing idea in tech that AI is moving so fast that young founders have this massive advantage. And I mean this with no offense. You're not old, but you're also not the youngest. [SPEAKER_01] You're telling me I'm old. I got it. No, you're not the youngest founder. And you have one of the most successful AI startups there is. And it does seem like you've brought a lot of your previous experiences to what you're doing. But I can tell from talking to you that you also are rethinking everything. And so I'm curious about your own experience for yourself and for other founders you look around at. Do you think by and large young founders have the advantage? What does it take for more experienced founders to have the advantage? [SPEAKER_01] You know, I'm always a big believer. I don't know if it's a real quote, but some VC said, why was this founder able to conquer this market where so many others had failed? And they said, well, he was too naive to know it couldn't be done. And there's a certain element of that that I love because you end up with this naivete that is actually a form of principled first principles thinking that a lot of young founders have. You just don't know why this messy, bad product dominates the market. You think there's a better, faster, cheaper way to do it. And because you don't have any of the hard-won lessons that can end up as oversimplified analogies, keeping you from actually taking that leap, you can end up with Tony making DoorDash and not caring about WebVan's Monzo or whatever it was. I can't remember all the dot-com bubble companies. But I do think, especially in enterprise software, the experience that some of our team members bring, including me and Clay, bring to it really does matter. Part of the reason we're able to serve so much of the Fortune 100 is we can go into a bank or a healthcare payer or a healthcare provider or a revenue cycle management firm or a big telecommunications company and understand their business. We're working with one large medical device company consolidating 40 of their call centers into one. And we can have a discussion about the change management of doing that. And that's not really a tech problem, but it does require understanding business. And I think there's a Venn diagram at Sierra where there's a circle of people who understand the next generation of AI and people who understand business. And we're the company right in the middle of that, maybe the only one. Yeah. [SPEAKER_01] And that matters because there's that infamous MIT study saying all these AI projects fail. None of ours do. And that's our value proposition. We can actually help you go live. And I think the experience has benefited us. Yeah. I'm curious if you can point to what has created the lead you have so far. And obviously, I know you're just getting started, but at the moment you do have pulled away in a big way. And I'm sure there's a lot of daily blocking and tackling. But I'm curious if there are any foundational decisions that you've made or strategic approaches that over the last couple years you look back at and you're like, that was pretty essential to make this happen. [SPEAKER_01] I think 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. And they're both really intentionally built. And obviously, I know you're just getting started, but at the moment you do, you've pulled away in a big way. And I'm sure there's a lot of daily blocking and tackling. [SPEAKER_01] But I'm curious if there are any foundational decisions that you've made or strategic approaches that over the last couple years you look back at and you're like, that was pretty essential to make this happen. [SPEAKER_01] I think there's two almost independent areas of investment. [SPEAKER_01] They're not independent, but they're very different. [SPEAKER_01] One is the product and one is our go-to-market and partnership model. And they're both really intentionally built. On the product side, we've tried to balance ease of use and extensibility because 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. There's all the enterprises are messy. And so that's why you tend to have most enterprise software that's 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? And so as a product designer, one of the things I've just 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? And I'm really proud of the product that we've built. And some of that is born from experience of what does extensibility mean? And I think 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. [SPEAKER_00] Because we knew when we started the company, we wanted to work with the largest companies in the world. [SPEAKER_00] Not only, but we want to be able to work with the largest companies in the world. [SPEAKER_00] And I focused on that. [SPEAKER_00] And as a consequence, we just have a really unique partnership model. [SPEAKER_00] There's a fashionable thing to talk about forward deployed engineering in Silicon Valley. [SPEAKER_00] We don't call it that. [SPEAKER_00] And it's a very unique model because it's not all about technology. [SPEAKER_00] Most of our clients build and maintain their agents themselves. [SPEAKER_00] It's pretty easy to do. [SPEAKER_00] But we show up and we help you be successful. [SPEAKER_00] So we'll just show up. [SPEAKER_00] We're not going to let you fail. [SPEAKER_00] And I think that is very different, because we have this outcomes model, outcomes-based pricing model. We don't get paid unless it works. And so— How much of that is technical versus change management? [SPEAKER_00] It's a mix of both. [SPEAKER_01] I don't know if it's 50-50. [SPEAKER_01] Do you know it as two people or it's one person who does both? We have a mix of roles. We sort of evolved that. [SPEAKER_01] 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 you know. It's a forward-deployed change management engineer. Yeah, yeah, exactly. It's crazy what we're doing. [SPEAKER_01] And what's really neat about it is if you're a really talented technical person who wants to go transform an industry, you can do it at Sierra. [SPEAKER_01] We're working with most of the healthcare insurance companies. You want to change healthcare costs? What a cool vantage point to do it. So we've been able to attract some really remarkable people, too. You said that it's not just support agents now. Yeah. What else are you finding shoots in? [SPEAKER_01] I'll give you one of my favorite relationships with Rocket. [SPEAKER_01] Based in Detroit, remarkable story. [SPEAKER_01] Their founder has done more for Detroit than I think any one person has done for any city. Remarkable company. But they own Redfin, which is a home search site, Rocket Mortgage, which is the number one consumer mortgage originator in the country. And then they bought a mortgage servicing firm recently as well. And 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 you can, with the acquisition they've done to this mortgage servicing firm, when you're servicing your mortgage, you'll talk on the phone with an AI agent as well. So everything from finding a house to originating the mortgage to servicing that mortgage, I think it's pretty cool. And they have an amazing CTO named Sean Mohotro, pretty visionary. And I love their CEO of Rune, too, but 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 that you could do. So they're executing the purchase, they're having issues with it all the way through retention. For example, a lot of our telecommunications customers, their AI agent is actually doing negotiations. You've probably negotiated your cable bill at some point. Probably. Probably. [SPEAKER_00] And so our AI agents are doing billions of dollars of negotiations for everything from satellite radio subscriptions to cable television subscriptions. [SPEAKER_00] It's pretty cool. [SPEAKER_00] It's over a billion dollars of mortgage folders a month. All transactional communications, eventually. 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 sort of doing that for agents. [SPEAKER_01] Agents will do a lot of things. [SPEAKER_00] The one with your brand at the top that your customers go to, whether it's buying or servicing, we would like to help you make that. And I think it's interesting, as agents go, it's often interacting with other agents, right? If you think about a home and auto insurance company, you may have a claim adjudication agent, which is quite complicated. So our agent that's having the phone conversation when you're on the fender bender will interact with that. We're doing that for agents. [SPEAKER_01] 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 would like to help you make that. And I think it's interesting, as agents go, it's often interacting with other agents, right? If you think about a home and auto insurance company, you may have a claim adjudication agent that's quite complicated. So our agent that's having the phone conversation when you're on the fender bender will interact with that. But it is almost the intersection of all of that technology because it's your front door. [SPEAKER_00] And our whole hypothesis is every company needed a website in 1997, every company needs an agent in 2027. And we want to be that company. What's the nuance about agent builders, though? Because I know you have a view that just being a generic agent builder is not the right thing. Yeah, I mean, I've been surprised how many large-income enterprise software companies, their first foray into AI was an agent building tool. [SPEAKER_01] It just feels, inevitably, to be a commodity in my mind because maybe making a website was hard in 1995. [SPEAKER_01] But today there's a million ways to make a website. Most of them are open source. And you have cool companies like Purcell, which I love. [SPEAKER_00] But it's not like there's a huge market for this stuff. [SPEAKER_00] And in practice, I think the same will happen with agent building. [SPEAKER_00] I think OpenAI will have a great tool. [SPEAKER_00] Probably all the foundation model companies will. [SPEAKER_00] There will be open source packages like Langchain and Langgraph. [SPEAKER_00] The idea that you have the right to win there, I don't know if anyone has the right to win there just because it's a technology. It's a horizontal technology. And I just believe in open source. And it's just going to become a commodity. So my belief where there's value is really going to be in agents that do things. And you'll hire those agents and purchase those agents for what they do. So I believe in companies like Sierra. I believe in companies like Harvey. I really admire what they do. And they have an agent that will do an antitrust review. I think there will be a finance agent that audits your financials. There will be one that helps you onboard a supply chain vendor. There will be one that if you just think about onboarding a new vendor, it's like there's a procurement process. There's a legal process, there's a contract review process. Whether or not it's completely autonomous or human in the loop, all of that could be augmented with an AI. And that's a product. Agent building is not a product. It embraces a technology. [SPEAKER_01] Yep. Speaking of the platforms, aside from being the founder of Sierra, you're also on the board of OpenAI. You're the chairman there. [SPEAKER_01] I wanted to ask you specifically about Codex. [SPEAKER_01] Over the last couple of weeks, it's been unbelievable. [SPEAKER_01] A curtain just came down. [SPEAKER_01] 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? I'll say yes. [SPEAKER_01] I expected it just because, being on the board of OpenAI, we talk a lot about it and all the labs, Anthropic and OpenAI in particular, talk a lot about using coding agents to help build AI. [SPEAKER_01] And certainly building an AI researcher is an important part of building an AI lab. The weird part about, for me, as someone who is a software engineer, I didn't feel it until I used it. You can talk about it all the time. And then the first time you one shot something and it turns out really good and not slop, but really good. It's an emotional experience. For me, it was just, this is real. Yeah. As you said, it's really over the past three months that it has felt really materially different to me. And I've been thinking about it a lot. I was thinking about the past 20 years of software engineering. I remember the first time I worked on an engineering team that had real CI CD where you'd check in code and it would just automatically end up into production. And I remember if you've ever worked on an engineering team that did that versus one that did manual releases, it's completely different because to have something that can safely go from commit to production. There's so many things that have to happen to make that work. You end up relying a lot on testing. Both unit testing, integration testing and canary testing, because the last thing you want is someone clicking a button and taking down the service. And it's almost impossible for a team that is doing manual releases to convert into CI, like true continuous delivery, because there's so many implied processes that are incompatible with that. It's easy to start that way and very hard to work. So I've been asking myself clearly in three years, we're going to talk about what are the best practices to set up a software team that's optimized for this technology. And we'll know what those best practices are. [SPEAKER_00] And right now we're just figuring them out in real time. [SPEAKER_00] And my hypothesis is the companies that figure it out first will move the fastest. [SPEAKER_00] Yeah. [SPEAKER_00] And the other part of that is the companies that don't will move much more slowly. [SPEAKER_00] It's fascinating to me. [SPEAKER_00] And Andre Karpathy, he had a really interesting post about this too. I think a lot of folks who are in deep here have been thinking about it. [SPEAKER_00] And it's fun to see the industry you love flipped on its head in real time. Well, it's interesting because I think people, software engineers on one end and then say somebody who's in some part of the country where AI has not yet gotten fully extended. There's a wide gap in people's current comprehension of what AI is going to do. [SPEAKER_01] And so there's a lot unknown. [SPEAKER_01] There's a lot of blog posts going on right now that are breathlessly saying it's all over. [SPEAKER_01] I think I'm probably more in the camp of maybe software is, I don't know, people use the word software is solved. Well, it's interesting because I think people like software engineers on one end and then say somebody who's in some part of the country where AI has not yet gotten fully extended. There's a wide gap in people's current comprehension of what AI is going to do. [SPEAKER_01] And so I think it's unknown. There's a lot of blog posts going on right now that are breathlessly saying it's all over. I think I'm probably more in the camp of maybe software is solved. I don't know if it's that, but I'm curious if you have a view on if Codex and Cloud Code and the latest in coding is going to change the way companies are built. One easy strongman question there would be people have been claiming there's going to be 10, 10 person billion dollar companies. Are we at the precipice of that? Does that make sense? Are there other changes? What's going to happen now? There probably will be a 10 person billion dollar company, but I don't necessarily think it will be the norm. And the reason for that is competition. If you imagine the mobile phone market in the United States, there's three main competitors: Verizon, AT&T, T-Mobile. And they're all competing for a fixed pie of mobile subscribers. And it's why it's extremely competitive. There's promotions, there's ads. They can't make more of us. They can build up their network. They can do other pricing and packaging. And it's a really complex business to run. All of them have access to AI. Every single one. So the idea that you could deploy AI and not have to do things you're doing currently because of AI is probably true. But if any one of them figures out a way to use AI to gain market share against the other one, they're going to do it. And then as a response, their competitors will do it too. And that's how, when automated teller machines were introduced to banks, the teller job went away. But there's no fewer bank branches and no fewer people in those bank branches. And it's because someone figured out, hey, if we put financial advisors in there and other things, we can actually make more revenue per branch. My personal take is in a competitive market, and that's the key, you need competition. So people can't just pass the cost savings on to shareholders or dividends. The second order effect of the efficiencies of AI will be investment to compete. Lower prices or customer acquisition or whatever it might be. So we want to have fewer engineers per company. They'll just be way more productive. And so you just end up with way better software. [SPEAKER_01] Or you might have fewer engineers and more of something else, or you might have more engineers. I'm not sure, but the idea that it will be what it is today, but just more efficient, I think is a lack of imagination in my opinion. The interesting thing though is the other part of this. Software engineering does feel special. And I think people extrapolating from software engineering is a bit simplistic. The same thing might not happen to every other function. I'll just be really simple about it, which is finance and software engineering might be limited by intelligence. Meaning they're largely digital. They are largely manipulating digital things, and you could imagine AI automating that. Most of the economy isn't digital exclusively. So if you need to ship a t-shirt from Vietnam to here, you could automate some of that stuff. But at the end of the day, that cargo ship still needs to be in the water. And I always bring this up. Just imagine you run a pharmaceutical company. You can think about how to make a therapy. You probably need a wet lab. That intersects the real world. Maybe you could do robotics, but then you need a clinical trial. And so a lot of the economy is real. Yeah. And so it definitely will change the way companies are built. But I think when people say everything will be 10 people, it's maybe just the stuff that lives in bits. Yeah, that's right. Which is a lot of the economy, but not the economy. [SPEAKER_01] I mean, it's easy to talk about this, but you're right. If you just move around the physical world and get off of this podcast and this computer I'm sitting in front of, all this stuff, and you get into the world and there's trucks moving dirt around and people who need a building that has lights in it. There's a lot of physical things. [SPEAKER_01] And I kind of tend to think that the value of that stuff is all going to go up until maybe robots happen. But in general, I think the value of bits goes down, the value of stuff goes up potentially. [SPEAKER_01] I think you're probably right. And some of it, robotics will have a big impact as well. But I think people are thinking about this a bit simplistically. That's my take. And I think intelligence is clearly on the cusp of going up exponentially, but it doesn't mean adoption of that can't be absorbed by the economy perfectly exponentially. And so I just think people are a little bit simplistic. Do you think there's any cognitive things that are immune from intelligence? So Dylan Field, when he was on this podcast, gave an example of Brat Summer as something where he was just like, that would have been such an insanely hard call for an AI to make. And you need so much context and taste and opinion. Where my head was going is, OK, so coding is whatever's happening there is happening there. But what about brand or storytelling? And I'm asking you this both as an operator and as somebody who's very deep with OpenAI. Do you think that these other parts of intelligence also go the way of AI? [SPEAKER_01] I don't know if taste is necessarily related to intelligence. You know, it might be, but I've got three kids, including a 16 year old and a 15 year old. And when they decide what they're going to wear to school, I don't think they would consider ChatGPT's opinion. [SPEAKER_01] But what about brand or storytelling? [SPEAKER_01] And I'm asking you this both as an operator and as somebody who's very deep with OpenAI. [SPEAKER_01] Do you think that these other parts of intelligence also go the way of AI? [SPEAKER_01] I don't know if taste is necessarily related to intelligence. [SPEAKER_01] You know, it might be, but I've got three kids, including a 16 year old and a 15 year old. [SPEAKER_01] And when they decide what they're going to wear to school, I don't think they will. They would consider ChatGPT's opinion. They care more about what the person in class next to them is wearing. Similarly, if you go to the most elite competitive college preparatory school or the worst school in the world, there's always going to be the smart kid in class and the dumb kid in class and the strong kid and the fast kid and all these other things. And it's all relative and it's all very local and it's all very human. And so I think the idea that because AI is smart, it takes something away from us as humans, I don't necessarily subscribe to. You all see these things that go around online where people are lamenting older technology, the bicycle. And we've been weaker than machines for my entire life. Yeah. And I don't think it makes me feel weak as a person. And I think this is the first time we have computers that are going to be more intelligent than us. The emotions I had about code writing code that was high quality, it wasn't experienced because I might have some of my identity tied up in that task. Yeah. And the next day I woke up and I'm using it as a tool and now I can make better software. I'm like, this is great. [SPEAKER_00] Probably actually a good self-actualization to go through that and be like, oh, I'm not my ability to code. [SPEAKER_00] I think there's something interesting. I think people's vocations and their identities are often very intertwined. But I think once you absorb the technology, I don't think it's actually your identity. [SPEAKER_01] Yeah. And so I think I actually am quite optimistic that we will be human, we will all be status-seeking animals, we will all compete for real estate here in San Francisco. And even though our standard of living will go way up, we will all be jealous of people still, we will all compete. And as a consequence, I think humanity will be just fine. That's my view on it. And I think it's just hard to imagine, but it doesn't mean it's going to be catastrophically bad. I think it will be largely good for humanity. I have a friend who believes that as this kind of progress happens, everybody's already completely addicted to their phones and it's a disaster. Now you have all this AI happening. A friend of mine was saying that he basically thinks that it'll actually become a status signal to become increasingly offline. [SPEAKER_01] And I'm like, actually, that might be an interesting call. [SPEAKER_01] I do think that people will hit a tipping point with a lot of this stuff where all of it will happen. [SPEAKER_01] Intelligence will get so good and then people will just be like enough of all of this. [SPEAKER_01] And hopefully there's a big screen time reduction. [SPEAKER_01] You saw parents revolting on social media about social media for their kids and a bunch of schools and all the parents like nobody take a phone, everybody agree to it. [SPEAKER_01] So I think that'll be an interesting thing of whether humanity, whether there's an essential humanity that gets sharpened. [SPEAKER_01] I hope so. [SPEAKER_01] I actually, one of the things, I love the iPhone. It's one of the greatest inventions of this century. [SPEAKER_01] I hope we're not staring at a glowing rectangle. It can't be the right way to do it. In 10 years, now that AI can talk to you and human computer interfaces. This is my point. I actually think hopefully humanity can become more self-actualized as a consequence of this. [SPEAKER_00] And that is the purpose of technology. [SPEAKER_00] Just like the industrial revolution had Luddites and globalization led to job loss in the Rust Belt of the United States, but certain goods got less expensive and other parts like these. [SPEAKER_00] There's not going to be no issues. [SPEAKER_00] I think it would be callous and insincere to imply otherwise. [SPEAKER_00] But I think it will largely accelerate humanity in a really positive way. [SPEAKER_00] And for me, if you're thinking about how this impacts you, have a more flexible view of your own identity. How you do it every day doesn't define you. The metaphor because it was so obvious before and after is imagining being an accountant before Microsoft Excel and after Microsoft Excel. So much of the act of being an accountant was adding up numbers and things, and now it's building a model. The value you provided didn't change, but the act of doing it is completely different. The skill set is completely different. And so I think a lot of us are just going to go through that in a very compressed period of time. And it's okay. [SPEAKER_01] It's just a little anxiety-ridden. Yeah, it makes sense. My last question about AI, there was a shot from Anthropic at OpenAI around the Super Bowl commercial about the ads. They were good ads, they were funny. But I think it sparked a debate around the whole topic of what is the role of these foundation labs and how should they bring AI to the masses or not. [SPEAKER_01] What's the appropriate business model? [SPEAKER_01] What are the trade-offs of all of this? [SPEAKER_01] You obviously have experience with social networks and a lot of different pricing models. You know OpenAI well, you know how to consume AI. [SPEAKER_01] So I'm curious how you think about this and what is the right thing when you consider a lot of these dimensions. [SPEAKER_01] I'm very optimistic about ads done in a tasteful way. [SPEAKER_01] I started my career at Google. [SPEAKER_01] I arrived the day AdWords came out. So it was interesting because when I started there, everyone in my family, when they found I was working there was like, how did they even make money? And I laughed because I was like, I think I listened to the Acquired podcast. It's literally the most profitable business ever created. But as a consequence, Google is widely available for free for people who want to use it and has created an economy around it for demand fulfillment advertising. [SPEAKER_01] I'm very optimistic about ads done in a tasteful way. I started my career at Google. I think I arrived the day AdWords came out. [SPEAKER_00] So it was just interesting because when I started there, you'll laugh at this, but everyone in my family, when they found I was working there was like, how did they even make money? [SPEAKER_00] And I laughed just because I was like, I think I listened to the Acquired podcast is literally the most profitable business ever created. But as a consequence, Google is widely available for free for people who want to use it and has created an economy around it for demand fulfillment advertising. I think there's reasonable criticisms of advertising, if it starts to get in the way of the sanctity of what the AI is recommending you, which was the backhanded implication. [SPEAKER_00] But I just think it's not true. [SPEAKER_00] And so I actually think if ads are clearly labeled and not getting in the way of the experience, I think it's really aligned with the OpenAI mission because our mission is to ensure artificial general intelligence benefits humanity. [SPEAKER_00] Obviously, the most important part of that mission is safety. [SPEAKER_00] But after you get back the Hippocratic Oath, first do no harm, the job of a doctor is to cure you. [SPEAKER_00] So then after you say, okay, it's safe, how do we widely distribute it? [SPEAKER_00] And I think we have an obligation being a mission driven company. I'm the chair of the foundation and on the PBC board. Our mission matters and being able to offer it for free widely is a huge part of that. And we need to be able to afford that. But I think it's not only inauthentic. I find it inauthentic. This is an incredible opportunity to provide this at scale to society. And I think the idea that it will somehow take away from the experience is wrong. I grew up in a suburb of St. Louis and it's a whole different world than what we're in now. When I think about people I grew up with or from other parts of the country, 20 bucks a month is a lot. And I think it's easy to forget in our ecosystem that not everybody wants or can spend $20 a month on stuff, but they really want these services. [SPEAKER_01] If the whole world had to pay for Google, that'd be a worse world. [SPEAKER_01] It's really good that everybody has access. [SPEAKER_01] I just think it's important we do it well. [SPEAKER_01] Yeah. [SPEAKER_01] Yeah. And we will. People want good ads. I like good ads. If people bring me the right product, I'm like, that's really nice. [SPEAKER_01] This is the other part of it. [SPEAKER_01] You want businesses to be able to grow from scratch. [SPEAKER_01] There's such a purpose to it. It just needs to be done in the right way. So I find the discussion not particularly authentic. Yeah. [SPEAKER_00] Yeah. [SPEAKER_00] The last thing I wanted to ask you about was how you've chosen to finance the company. And I guess I'm curious about three parts, which are how you got started, working with Peter Fenton and then what you've done since then to date and what's been important for you. And then I'm curious, as you think about the future, what's important to you as you think about other partners or capitalizing. I'm asking just because this podcast has a lot of VC in it. [SPEAKER_01] So I got to have a little flourish. [SPEAKER_01] Yeah, totally. [SPEAKER_01] Absolutely. [SPEAKER_01] We have three members of our board, which represent our three rounds of investments. Peter Fenton from Benchmark, Ravi Gupta, who just left Sequoia, though he's still a venture partner there. And Neil Mehta from Green Oaks. A fantastic group of people. I chose them all, both for the firm and the person. But notably, Peter, I've worked with at both my previous companies. Our first round of financing, I didn't talk to anyone else and introduced him to Clay, my co-founder who hadn't spent time with him. And we talked once. He sent me a term sheet. I signed it. No edits. It was a trust relationship. And it is interesting. One of the things I really have appreciated about Silicon Valley, there's some downsides to it and how insular the community is. One of the great parts, though, is the relationships you can forge over years. For me, it meant Peter and I could start on third base just because we've worked together a lot before. And you just don't end up with a lot of funny business in the fundraising process. No funny business. The boardroom is just like, let's get to work. And it's fun. It was fun to get the band back together. But the fun part for me is I had never worked with Ravi nor Neil before. And Clay and I, it's just a great board. Yeah. It's people we seek out advice from as opposed to people we report to every quarter. So it's amazing. How do you think about it because you're both known for, when OpenAI won't go back to the story, but when OpenAI had its moment. Sam was right. You got to be a board member. And then you've also got a board that you're on, so you're in both roles at once. How do you make the most out of the board? [SPEAKER_01] Obviously you've got these particular relationships. [SPEAKER_01] But what do you expect that relationship to look like? First, I really prefer written documents for boards over presentations, both as a board member and as a founder of a company, because you end up letting people synthesize information ahead of the board meeting. [SPEAKER_01] So you end up with more substantive discussions in the boardroom. [SPEAKER_01] I've done this for the last two companies I've started. And it's been great to send out a board document. Sometimes people will comment ahead of the meeting. But I think the main thing is it's been read and it's been read ahead of time. [SPEAKER_00] And then you end up with a meeting about the actual meat and potatoes of the topics. [SPEAKER_00] You're not staring at a bunch of sales numbers for the first time. You're not running through slides. You're not running through slides. [SPEAKER_01] So you end up with more substantive discussions in the board room. [SPEAKER_01] I've done this for the last two companies I've started. And it's just been great to send out a board document. Sometimes people will comment ahead of the meeting. [SPEAKER_00] But I actually think the main thing is it's been read and it's been read ahead of time. [SPEAKER_00] And then you end up with a meeting about the actual meat and potatoes of the topics. [SPEAKER_00] You're not staring at a bunch of sales numbers for the first time. You're not running through slides. You're not running through slides. And I find it to be incredibly valuable. I think most companies should be run this way. The other thing that is really interesting is don't write it with AI. It's funny to have to say that now. But I find that the process of the writing is a process of clarifying your thoughts. And so for Clay and me, this is a process by which we synthesize what's been happening. And you know it, you talk about it, but to actually write it and write it eloquently and concisely is incredibly important because it's essentially a way of—what's that famous quote? If I had more time, I would have written a shorter letter. Spend the time because that's actually how you can show respect to your stakeholders that you're thinking about the strategic issues going on in your business. And the last thing I'd say is board members aren't single issue voters, but everyone has their strengths. And at OpenAI, we've recruited a pretty diverse set of skills. Zico Coulter is a professor at CMU who specializes in, among other things, jailbreaking. So one of the experts on some of the more subtle safety aspects. Nicole Seligman was a great attorney and she's an expert in a lot of legal issues. And what's really nice is when you grow your board beyond your initial investors too, is find people that your management team will want to go to for advice. Obviously, the audit committee chair and your CFO have a really unique relationship, but you really want folks like, who's your head of sales going to go talk to? Do you have someone who's been there or done that? Because you want them to have that kind of support. I always think of it as, who are the advisors you want to surround your management team? Well, and I think a functional board really has those relationships. And then when you're in a board discussion, you have all these board members who have had lots of engagement with the company, but in a really valuable targeted way. So I think of the board as a collection of people. Don't look at the individuals. The whole should be greater than the sum of its parts. [SPEAKER_00] Anything this year you're particularly excited about that you can share? I think the real exciting part is going to be adoption in regulated industries. I think we are moving beyond the early adopters to everyone. [SPEAKER_01] And so if we talk a year from now, you're going to be doing the hard stuff. It's going to be the really hard stuff. That's awesome. And I have a hot take for you. I think my intuition is regulators will start asking for agents. The idea that you have a human set of controls over a regulated process will start to feel like a risk rather than the risk being AI. And that's my prediction. I don't know what happened this year, but I think that will happen. Well, I'll call you in a year and we'll do take two of this. That sounds great. Thanks so much for doing this, Brett. [SPEAKER_00] This was great. [SPEAKER_01] Thanks for having me. And you have, like, cool companies like Purcell, which I love. But it's not like there's a huge market for this stuff. And in practice, I think the same will happen with agent building. I think OpenAI will have a great tool. Probably all the foundation model companies will. There will 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 just because it's just a technology. It's a horizontal technology. And I just believe in open source. And it's just going to become a commodity. So my belief where there's value is really going to be in agents that do things. And you'll hire those agents and purchase those agents for what they do. So I believe in companies like Sierra. I believe in companies like Harvey. I really admire what they do. And, you know, they have an agent that will do an antitrust review. You know, I think there will be a finance agent that audits your financials. There will be one that helps you onboard a, you know, supply chain vendor. There will be one that, you know, if you just think about onboarding a new vendor, it's like there's a procurement process. There's a legal process, there's a contract review process. Whether or not it's completely autonomous or human in the loop, all of that could be augmented with an AI. And I'm like, that's a product. Yeah. Agent building is not a product. It embraces a technology. Yep. 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. Like over the last, you know, couple of weeks, it's been unbelievable. It's like, you know, a curtain just came down. Did you expect this? Like, did you think that what has happened here was going to happen? Like, when did you start to have an inkling that like code was going to go vertical like this? I'll say yes. I expected it just because, you know, being on the board of OpenAI, we talk a lot about it and all the labs, Anthropic and OpenAI in particular, talk a lot about using coding agents to help build AI. And certainly like building an AI researcher is an important part of building an AI lab. The weird part about, for me, as someone who is a software engineer, I didn't feel it until I used it. So you like, you can talk about it all the time. And then like the first time you one shot something and it turns out like really good and not like slop, but like really good. It's an emotional experience. I think, I mean, for me, it was, it was just sort of like, holy shit. Like, this is real. Yeah. As you said, it's really over the past three months that it has felt really materially different to me. And I've been thinking about it a lot. Um, I was thinking about the past 20 years of software engineering. Um, I remember the first time I, uh, worked on an engineering team that had real CI CD where you'd check in code and it would just automatically end up into production. And I remember how I'll just like, if you've ever worked in engineering team that did that versus one that did manual releases, it's completely different because to have something that can safely go from commit to production. There's so many things that have to happen to make that work. You end up relying a lot on testing. So both unit testing, integration testing and canary testing, because the last thing you want is someone clicking a button and taking down the service. And it's almost impossible for a team that is doing manual releases to convert into CI, like true continuous delivery, because there's so many implied processes that are incompatible with that. It's like easy to start that way and very hard to work. So I've been asking myself clearly in three years, we're going to, like, if we were talking, we could talk about what are the best practices to set up a software team that's optimized for this technology. And we'll know what those best practices are. And right now we're just figuring them out in real time. And like my hypothesis is the companies that figure it out first will move the fastest. Yeah. And the other part of that is the companies that don't will move much more slowly. It's fascinating to me. And Andre Karpathia, he had a really interesting post about this too. Like, I think a lot of folks who are sort of like in deep here have been thinking about it. And it's fun to see the industry you love sort of flipped on its head and yeah. In real time. Well, it's interesting because like, I think people like, you know, software engineers on one end and then like say somebody who's like, you know, in, you know, some part of the country where AI has not yet kind of like gotten fully extended. Like there's like a wide gap in people's current sort of comprehension of like what AI is going to do. And so I think, you know, it's like, it's a little bit unknown. Like, you know, there's a lot of blog posts going on right now that are breathlessly saying like it's all over. I think, you know, I'm probably more in the camp of like maybe software is like, I don't know, people, you know, use the word software is solved. I don't know if it's that, but I'm curious if you have a view on like if Codex and Cloud Code and sort of like the latest in coding, is that going to change the way companies are built? You know, like one easy strongman question there would be like, you know, people have been claiming that there's going to be my brother, you know, these 10, 10 person billion dollar companies. You know, is that are we at the precipice of that? Does that make sense? Are there other changes? Like what's going to happen now? There probably will be a 10 person billion dollar company, but I don't necessarily think will be the norm. And the reason for that is competition. If you imagine like the mobile phone market in the United States, there's three main competitors, Verizon, AT&T, T-Mobile. And they're all competing for a fixed pie of mobile subscribers. And it's why it's extremely competitive. There's promotions, there's ads. They can't make more of us. They can't make more of us. They can build up their network. They can do other pricing and packaging. And it's a really complex business to run. All of them have access to AI. Every single one. So the idea that you could deploy AI and, you know, not have to do things you're doing currently because of AI is probably true. But if any one of them figures out a way to use a person to gain market share against the other one, they're going to do it. And then as a response, their competitors will do it too. And that's how, you know, we spoke about this earlier, but it's the reason why when automated teller machines were introduced to banks, the teller job went away. But there's no fewer bank branches and no fewer people in those bank branches. And it's because, I don't know if it was JPMC or someone figured out, hey, if we put financial advisors in there and other things, we can actually make more revenue per branch. My personal take is in a competitive market, and that's the key, by the way, you need competition. So people can't just pass the cost savings on to shareholders or dividends. The second order effect of the efficiencies of AI will be investment to compete. Lower prices or customer acquisition or whatever it might be. So we want to have fewer engineers per company. We'll just, they'll be way more productive. And so you just end up with way better software. Or you might have fewer engineers and more of something else, or you might have more engineers. You know, I don't, I'm not sure, but it's, it's the idea that like it will be what it is today, but just more efficient, I think is like a lack of imagination. In my opinion, the interesting thing though, is the other part of this software engineering does feel special. And I think people extrapolating too much from software engineering or it's a bit simplistic. You're like the same thing might not happen to every other function. I'll just be really simple about it, which is finance and software engineering might be limited by intelligence. Meaning they're largely digital. They are largely like manipulating sort of digital things to, and, and you could imagine AI automating that. Most of the economy isn't digital, like exclusively. Uh, so, you know, if you need to ship something, a t-shirt from Vietnam to here, yeah, you could automate some of that stuff. But at the end of the day, like that, that cargo ship still needs to be in the water. And I always bring this up, you know, like just imagine you run a pharmaceutical company, you know, you can think about, you know, how to make a therapy. You probably need a wet lab. So, okay, well that's intersects the real world. Maybe you could do robotics, but then you need a clinical trial and then, you know, so just a lot of the economy is like real. Yeah. And so it definitely will change the way companies are built. But I think when people say everything will be 10 people. It's like maybe just the stuff that lives in bits. Yeah, that's right. Which is a lot of the economy, but not the economy. I mean, you know, it's easy to like to talk about this, but you're right. Like if you just like move around the physical world and you get off of, you know, this podcast and, you know, this computer I'm sitting in front of all this stuff and you got into the world and there's like, you know, trucks moving dirt around and people who need a building that has lights in it. And there's like a lot of physical things. And I kind of tend to think that the value of that stuff is all going to go up until maybe robots happen. But in general, I think, you know, the value of bits goes down, the value of stuff goes up potentially. I think you're probably right. And and some of, you know, like robotics will have a big impact as well. But I think people are thinking about this a bit simplistically is my my take. And I think intelligence is clearly on the cusp of going up exponentially, but it doesn't mean adoption of like that can't be absorbed by the economy perfectly exponentially. And so I just think people are a little bit simplistic. Do you think there's any cognitive things that are immune from intelligence? So like Dylan Field, when he was on this podcast, gave an example of like Brat Summer as something where he was just like, that would have been such an insanely hard call for an AI to make. And you need so much context and taste and opinion. You know, where my head was going is, OK, so coding is, you know, whatever's happening there is happening there. But what about like brand or storytelling? Like and I'm kind of asking you this both as an operator and as, you know, somebody who's very deep with open AI. Like, do you think that these other parts of intelligence also, you know, go the way of AI? I don't know if taste is necessarily related to intelligence. You know, it might be, but I've got three kids, including a 16 year old and a 15 year old. And when they decide what they're going to wear to school, I don't think they will. They would consider chat GPT's opinion. They care more about what the person in class next to them is wearing. Similarly, if you go to the most like elite competitive college preparatory school or the worst school in the world, there's always going to be the smart kid in class and the dumb kid in class and the strong kid and the fast kid and all these other things. And like, it's all relative and it's all very local and it's all very human. And so I think the idea that because AI is smart, it takes something away from us as humans, I don't necessarily subscribe to. I don't, you know, you all see these things that go around online where people are sort of lamenting older technology, like the bicycle. And, you know, we've been weaker than machines for my entire life. Yeah. And I don't, I don't think it like, it doesn't make me feel like weak as a person. And I think we, this is for the first time we have computers that are going to be more intelligent than us. I think there will, you know, the emotions I had about codecs writing code that was high quality, it wasn't experienced because, you know, I might have some of my identity tied up in that task. Yeah. And the next day I woke up and I'm using it as a tool and now I can make better software. I'm like, this is great. Probably actually like a good like self-actualization anyway to go through that and be like, oh, I'm not my ability to code. I think there's interesting, I think people's vocations and their identities are often very intertwined. But I think once you absorb the technology, I don't think it's actually your identity. Yeah. And so I think I actually am quite optimistic that we will be human, we will all be status-seeking animals, we will all compete for the real estate here in San Francisco. And even though our standard of living will go way up, we will all be jealous of people still, we will all compete. And as a consequence, I think humanity will be just fine. That's my view on it. And I think it's just hard to imagine, but it doesn't mean it's going to be catastrophically bad. I just think it's actually, I think it will be largely good for humanity. I have a friend who believes that like as this kind of progress, you know, we're already, everybody's already completely addicted to their phones and it's a disaster and whatever. Now you have all this AI happening. A friend of mine was saying that he basically thinks that it'll actually become a status signal to become increasingly offline. And I'm like, actually, that might be an interesting call. Like, I do think that like people will kind of hit a tipping point with a lot of this stuff where like all of it will happen. Like intelligence will get so good and then people will sort of just be like enough of all of this. And like hopefully there's a big screen time reduction, you know? And it's like, you saw like parents were revolting on social media, like about social media for their kids and like a bunch of schools and all the parents like nobody take a phone, like everybody agree to it. So I think that'll be an interesting thing of like, does humanity, like, is there like an essential humanity that like gets sharpened? I hope so. I actually, one of the things, you know, I love the iPhone is one of the greatest inventions of this century. I hope we're not staring at a glowing rectangle. It can't be the right way to do it. In 10 years and, you know, now that AI can talk to you and human computer interfaces. Like, so this is my point. I actually think hopefully humanity can become more self-actualized, you know, as a consequence of this. And that is the purpose of technology. So, you know, just like the industrial revolution had Luddites and globalization led to job loss in the Rust Belt of the United States, but certain goods got less expensive and other parts like these. There's not going to be no issues. I think it would be callous and insincere to imply otherwise. But I think it will largely just really accelerate humanity in a really positive way. And I think that for me, and I think for like, if you're thinking about how does this impact me is like, have a more flexible view of your own identity. Like the what, how you do it every day doesn't define you. I was like the metaphor because it was so obvious before and after imagining being an accountant before Microsoft Excel and after Microsoft Excel. So much of the act of being an accountant was like adding up numbers and things, you know, and now it's like building a model. And it's not like what you did, like the value you provided didn't change, but actually the act of doing it is completely different. Like the skill set is completely different. And so I think it was just like a lot of us are just going to go through that in a very compressed period of time. And it's okay. It's just a little anxiety-ridden. Yeah, it makes sense. My last question about AI, there was a shot from Anthropic at OpenAI around the Super Bowl commercial about the ads, which is, they were good ads, they were funny. But then I think sparked like a debate around sort of like the whole topic of like, what is the role of these foundation labs and how should they sort of like bring AI to the masses or not? What's the appropriate business model? What are the trade-offs of all of this? You've obviously like, you know, you have experience with social networks and a lot of different pricing, you know, models, you know, OpenAI well, you know, you know, how to consume AI. So I'm just curious how you think about this and like, what is the right thing when you consider like a lot of these dimensions? I'm very optimistic about ads done in sort of a tasteful way. You know, I started my career at Google. I think I arrived like the day AdWords came out. So it was just interesting because when I started there, you'll laugh at this, but like everyone in my family, when they found I was working there was like, how did they even make money? And I laughed just because I was like, I think I listened to the Acquired podcast is literally the most profitable business ever created. But as a consequence, you know, Google is widely available for free for people who want to use it and has created an economy around it for demand fulfillment advertising. I think there's reasonable criticisms of advertising, you know, if it starts to get in the way of the sanctity of what the AI is recommending you, which was sort of the, you know, backhanded implication. But I just think it's not true. And so I actually think if ads are clearly labeled and, you know, not getting the experience, I think it's really aligned with the opening eye mission because our mission is to ensure artificial general intelligence benefits humanity. Obviously, the most important part of that mission is safety. But after you get back the Hippocratic Oath, first do no harm, the job of a doctor to cure you. So then after you say, okay, it's safe, how do we widely distribute it? And I think we have an obligation being a mission driven, you know, I'm the chair of the foundation and on the PBC board. Like our mission matters and being able to offer it for free widely is a huge part of that. And we need to be able to afford that. But I think it's not only I just I find it inauthentic. Like I'm like, this is an incredible opportunity to provide this at scale to society. And I think the idea that it will somehow take the experience is wrong. You know, like I grew up in like suburb of St. Louis and, you know, so it's like a whole different world than like, you know, what we're in now. And it's like when I think about like, you know, people, you know, that I grew up with or, you know, from just other parts of the country, 20 bucks a month is a lot. And I think, you know, it's easy to forget in our ecosystem that like not everybody wants or can spend $20 a month on stuff, but they really want these services. Like, you know, if the whole world had to pay for Google, like that'd be a worse world. Like it's really good that everybody has access. I just think it's important we do it well. Yeah. Yeah. And we will. People want good ads. Like I like good ads. Like I would actually, if people bring me the right product, I'm like, that's really nice. This is the other part of it. It's like you want businesses to be able to grow from scratch. There's such a purpose of it. It just needs to be done in the right way. So I, I find the discussion not, not particularly authentic. Yeah. Yeah. The last thing I wanted to ask you about was how you've chosen to sort of like finance the company. And I guess I'm curious about three parts, which are how you got started and, you know, working with Peter Fenton and then like what you've done since then to date and what's been important for you. And then I'm curious, just like, as you think about the future, like what's important to you as you think about other partners or capitalizing and, you know, I'm asking just because this is a podcast has a lot of VC in it. So I got to have a little flourish. Yeah, totally. Absolutely. We have three members of our board, which are sort of represent kind of like our kind of three rounds of investments. So Peter Fenton from Benchmark, Ravi Gupta, who just left Sequoia, though he's still a venture partner there. And Neil Mehta from Green Oaks. Just a fantastic group of people. And chose them all, both for the firm and the person. But notably, like Peter, I've worked with both my previous companies. So, you know, our first round of financing, I didn't talk to anyone else and introduced him to Clay, my co-friend who hadn't spent time with him. And we talked once. He sent me a term sheet. I signed it. No edits. And it was like a very much a trust relationship. And it is interesting, like one of the things I really have appreciated about. So there's some downsides to Silicon Valley and our, you know, how insular the community is. One of the great parts, though, is just like the relationships you can forge over years. And for me, it meant Peter and I could sort of start on third base just because we've worked together a lot before. And so you just don't end up with a lot of the there's no no funny business in the fundraising process. No funny business. The boardroom is just like, let's get to work. And it's fun. It was fun to, you know, sort of get the band back together. They're there. But the fun part for me is I had never worked with Ravi nor Neil before. And like Clay and I just it's like it's just it's just a great board. Yeah. Like it's just like people we seek out advice from as opposed to people we report to, you know, every quarter. So it's amazing. How do you think about because you're both like known like, you know, when when opening I won't go back to the story, but like, you know, when opening I had it's like, oh, my God moment. Like Sam was like, you know, right. You got to like you're like the board member. And then you've also got a board that you're so you're you're in both roles at once. How do you like make the most out of the board? Like, you know, obviously you've got these particular relationships. But like, what do you expect that relationship to look like? First, I really like written documents for boards over presentations, both as a board member and as like a founder of a company, because you end up letting people synthesize information ahead of the board meeting. So you end up with more substantive discussions in the board room. I've done this for the last two companies I've started. And it's just been great to send out a, you know, a board document. Sometimes people will comment ahead of the meeting. But I actually think the main thing is it's been read and it's been read ahead of time. And then you end up with a meeting about the actual meat and potatoes of the topics. You're not like staring at a bunch of sales numbers for the first time. You're not running through slides. You're not running through slides. And I find it to be incredibly, I think most companies should be run this way. The other thing that is really interesting is like, don't write it with AI. It's so funny to have to say that now. But I find that the process of the writing, the process of the writing is a process of clarifying your thoughts. And so for Clay and me, this is a process by which we synthesize what's been happening. And you know it, you talk about it, but to actually write it and write it eloquently and concisely is incredibly important because it's essentially a way of, you know, it's like, what's that famous? If I had more time, I would have written a shorter letter, like spend the time because that's actually how you can show respect to your stakeholders that you're thinking about the strategic issues going on in your business. And the last thing I'd say is board members aren't sort of single issue voters, but everyone has their strengths. And, you know, at OpenAI, we've recruited a pretty diverse set of skills. Zico Coulter is a professor at CMU who specializes in, among other things, jailbreaking. So just like one of the experts on some of the more subtle safety aspects, Nicole Seligman was a great attorney and, you know, she's an expert in a lot of like legal issues. And what's really nice is when you grow out of board, you know, beyond your initial investors too, is find people that your management team will want to go to for advice. Obviously, the audit committee chair and your CFO have a really unique relationship, but you really want folks like, who's your head of sales going to go talk to? Do you have someone who's like kind of been there or done that? Because you want them to have that kind of like, I always think of it as like, who are the advisors you want to surround your management team? Well, and I think a functional board really has those relationships. And then when you're in a board discussion, you have all these board members who have had lots of engagement with the company, but in a really valuable kind of targeted way. So I like to think of the board as a collection of people. Don't look at the individuals. It's a, it's a, the whole should be greater than the sum of its parts. Anything this year you're particularly excited about that you can share? I think the real exciting part is going to be adoption and regulated industries. I think we, we are moving beyond like the early adopters to everyone. And so I think if we have, if we talk a year from now, you're going to be doing the hard stuff. It's going to be like the really hard stuff. That's awesome. And I have, if you want like a hot take, you know, I think my intuition is regulators will start asking for agents. The idea that you have a human set of controls over a regulated process will start to feel like a risk rather than the risk being AI. And that's my, I don't know what happened this year, but I think that will happen. Well, I'll call you in a year and we'll do take two of this. That sounds great. All right. Thanks so much for doing this, Brett. This was great. Thanks for having me.