Uncapped #42 | Bret Taylor from Sierra

Bret Taylor is the founder and CEO of Sierra, an AI agent company transforming customer service. Bret’s legendary career includes being CTO of Meta, co-CEO of Salesforce, chairman of the board at OpenAI, co-creating both Google Maps and the Like button, and founding three companies. We unpacked the so-called “SaaS-pocalypse” and what AI agents mean for the future of enterprise software. We talked through the shift from systems of record to autonomous agents, outcome-based pricing, platform transitions, Codex and the transformation of software engineering, and who is structurally positioned to win in the next era of AI. --- Timestamps: (0:00) Intro (0:20) The SaaS-pocalypse and systems of record (12:34) Sierra's competitive landscape (17:05) Outcomes-based pricing (24:22) The rapid evolution of AI support technology (28:21) Young founders vs. experienced founders (34:12) Beyond support: The full customer lifecycle (38:47) Codex and the future of software engineering (51:49) OpenAI and advertising (54:59) How to run a board --- Links: https://x.com/btaylor https://x.com/jaltma https://uncappedpod.com/ --- Email: [email protected]

• 0:00Speaker 00

  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 like, my hypothesis is the companies that figure it out first will move the fastest. It's fascinating to me.

• 0:20Speaker 01

  Brett, thanks so much for doing this with me. I'm super excited for it.

• 0:23Speaker 00

  Thanks for having me.

• 0:24Speaker 01

  So you're one of the best people to ask this following question, which is, what is your view on the SaaS apocalypse? If we can call it that.

• 0:31Speaker 00

  SaaS McGeaden.

• 0:32Speaker 01

  SaaS McGeaden. So basically, it's like, you know, in public markets, all of these companies are trading way down. You know, you go on X and everybody's talking about how like, you know, 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, like, where does durability come from? And so I just wanted to sort of start with this topic because, you know, you've built your own companies. You've been the co-CEO at Salesforce. You're now building like one of the fastest growing AI startups there is. You're on the board of OpenAI. How do you see software like in this moment in February 26?

• 1:07Speaker 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 like 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 basically anxiety about the future. I think it's a few things. We can talk about sort of 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, like the core databases that Oracle, you know, sort of famously powered in the early days of software.

• 1:49Speaker 00

  And then you end up with all the software as a service companies, SAP, Workday, Salesforce, ServiceNow.

• 1:54Speaker 01

  Yep.

• 1:54Speaker 00

  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.

• 2:05Speaker 01

  If you had to like synthesize pre-AI, like, 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 and the integrations? Like, what do you attribute the success of systems of record to?

• 2:20Speaker 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, you know, create a workflow for quote to cash or something like that, you had to integrate with your ERP system and your CRM system. So as a consequence, you know, the companies that sort of owned those databases could either develop that functionality as an add-on, like a new SKU. Or if it was a third-party company, they would often be a part of the ecosystem like Salesforce's App Exchange 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 just really high

• 2:59Speaker 00

  because it was sort of this, that system plus all the partners that integrated with it sort of 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 sort of became the sun in the solar system, you know, 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 a scale. So you'd get sales capacity scale, you know, 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, you know, obviously is somewhat dated, you know, expression. But it sort of was like, hey, if you're going to put in a new ERP systems, no one's going to blame you for choosing SAP.

• 3:44Speaker 00

  Because everyone chose SAP.

• 3:46Speaker 01

  If you choose something new and it doesn't work perfectly, big trouble.

• 3:49Speaker 00

  Then you're, you're the same. So all those things sort of accrue. But then the question is now that all of a sudden that a lot of those start getting chipped away with AI agents. You know, first, could you just vibe 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.

• 4:20Speaker 01

  Yeah.

• 4:21Speaker 00

  All of that is sort of invisible to you. And all of a sudden it goes from being an application to sort of a database.

• 4:26Speaker 01

  Right.

• 4:26Speaker 00

  Similarly, if you imagine a CRM system and rather than having people People staring at it all day to manage their leads, contacts and opportunities. If you just say, hey, generate me some leads.

• 4:34Speaker 01

  In other words, like, does a, does a system of record have a place in the world if nobody logs into it?

• 4:40Speaker 00

  And it does, but the real question is like, how valuable is it? How important is it? You know, and you go back to my metaphor on a solar system here. How, how important is that gravity versus the gravity of the agents, you know, running around it? And it's just really interesting because if you imagine you're running a sales team, you know, how much do you value the database of leads versus the agent that generates the leads? And along like ancient history, three years ago, those are the same thing. But now you're like, gosh, I actually probably care more about the lead, the lead generation. And how it's stored and tracked is actually maybe a more tactical part of it. So there's all sorts, and that's true of every system of record. This isn't, you know, I just know CRM systems, you know, pretty well.

• 5:18Speaker 00

  And if you look at ITSM, which is like the place Source Now plays, or ERP systems, which is Workday, SAP, Oracle, et cetera. There, 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 and Azure and all those other things. But it was really awkward, you know? I think folks like you and me back in the day used to probably dismiss Microsoft. I mean, I certainly did. I didn't, I didn't foresee them becoming as powerful, as, as strong as they are today. But it was good leadership, good technology. But I don't think the market knows like who is Siebel Systems and who is Microsoft?

• 6:00Speaker 00

  In this like landscape of software companies, probably no one knows that Siebel Systems was, that was the company that Salesforce beat to become the cloud CRM. So can you actually develop this ecosystem of agents around your platform? And, you know, will it become more valuable than the platform you had? And then on top of it, the existential risk of, you know, is 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 gonna sit on the sidelines. And so you're like, I'm gonna let the market play out a little bit. And I think that's sort of what's going on.

• 6:31Speaker 01

  Totally. Yeah, I mean, you can never know for sure who's going to turn into the next Microsoft. But you can kind of try to think about like, who has the structural Ability to expand, like who's got the right with customers to make the expansions? And then which products will be easier? So like, you know, 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 go build a database at some point? Because I can, I could do that and I've got the customer relationship. And how do you think about like, what creates the rights to expand?

• 7:03Speaker 00

  I think all the incumbents sort of have a right to win in a lot of ways. You know, in the same way, we talked about, you know, why a system of record is powerful. I think you could say the same logic for all the agents running 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, if you, 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 sort of good procurement leverage, B, everything works together.

• 7:45Speaker 01

  You don't have to deal with the kind of people.

• 7:46Speaker 00

  There's probably some benefits, all sorts of things.

• 7:49Speaker 01

  Yep.

• 7:49Speaker 00

  What ends up happening when new technologies come out as you, the pendulum swing from best of platform, best of back to breed? Because when the new, listen, when the web browser came out.

• 7:58Speaker 01

  It's much easier to get a 10x experience.

• 8:00Speaker 00

  A hundred percent. And also just think of the like pre and post web browser enterprise software. Like you're running like client server, Windows software. And like, it's a completely different skill set to make a web application, as you and I know.

• 8:12Speaker 01

  Totally.

• 8:12Speaker 00

  And so at the time, like, there's this window of time where best of breed competitors are light years ahead of the incumbents.

• 8:18Speaker 01

  That's right.

• 8:19Speaker 00

  And it's a race. So basically, can the best of breed upstarts?

• 8:23Speaker 01

  Yep.

• 8:24Speaker 00

  Turn into get scale before the incumbents figure out the technology? And that's what was going on right now. So like, I would argue, very few of the incumbents have any credible, like decent AI technology, but they will. It's like inevitable, they will.

• 8:38Speaker 01

  You don't understand, why is that? Like, what's the real reason for it? Cause like, I see these companies that have, let's call it infinite resources, roughly speaking. They ought to be able to hire who they want. They ought to know what the products could look like. They ought to be able to try them. They ought to be like, why is it so hard for like, let's say legacy companies to like catch up quickly? You know, versus like an AI startup with 50 engineers seems to, you know, outperform, you know, the teams that are 10 or whatever times bigger at a big company. Is it cultural? Is it systems? Is it?

• 9:11Speaker 00

  I like the phrase strategy tax. I don't remember who to attribute that to. We could pull up chat GPT and ask. I think the idea is like, in these moments of big platform shifts, what were your strengths can become weaknesses? So let's just take Siebel Systems and the birth of the web browser. They have a, you know, on premises CRM system. When you say, okay, like, 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.

• 9:53Speaker 00

  And what if someone wants on premises too? And you know, that's our strength. We should play to that strength. And you start like, basically making all these decisions that like, you know, sound really clever because you're playing to your, your strengths. And in practice of the technology wave is bigger than the category, which I think the web was as an example. You end up sort of basically chipping away at sort of doing a pure play value proposition. It can also happen with business models, though. So, you know, 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.

• 10:35Speaker 00

  I mean, Adobe, Sean Toney did this at Adobe. Very few companies could make that transition.

• 10:39Speaker 01

  Yeah.

• 10:39Speaker 00

  And you have to sell it differently. You have to compensate salespeople differently. Revenue recognition is different. So you have the product strategy tax, you have the business model strategy tax. You have even like incentives of salespeople, there's a strategy tax because you know, you don't want to just have your business collapse overnight. So you can't just, it's so easy for a clever or Silicon Valley, like just pivot. I'm like, yeah, if you're a public company, you have to, you know, 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 there, 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

• 11:23Speaker 00

  that are holding you back from actually doing the right thing. And that's why. You know, I always like to remind our company, Sierra, that, you know, 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 like, don't fight AI. It's gonna happen with or without us. And if you go back to the internet, if we were talking in 1995 or something, and we probably like, search is a category, e-commerce is a category, oh, digital payments, that stuff is gonna 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

• 12:04Speaker 00

  categories are like, whether or not any of those founders existed, all of the would be winners.

• 12:09Speaker 01

  And it's the same now.

• 12:10Speaker 00

  It is the same now. So like, everyone knows what's gonna 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 it's, you tend to get new, new great companies, like the companies that are enduring tend to be created in platform shifts more than any other time.

• 12:34Speaker 01

  I actually be curious on this topic of sort of, you know, there's these obvious things. And within AI, I would say, you know, not to discredit your insight, but support, I would count as an obvious thing, like in a good way. It looks like it works. And you did it, you know, early enough that you were able to get, you know, to a place, you know, at the right time. But other people did too. And so in some ways, I'm like, you have been playing both in a very blue ocean, you know, wide fields, like, you know, the incumbents are sort of like categorically different. And so like, it seems like inevitable that we're gonna have agents doing support. And so there's that. And then on the other side, you know, 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, like, experientially,

• 13:19Speaker 01

  day to day, does, does your sort of operation of the company feel competitive or like wide open?

• 13:26Speaker 00

  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. It's like, you don't get to.

• 13:36Speaker 01

  So you feel like there's lots of demand and there's like a contest with each sort of situation?

• 13:42Speaker 00

  Yeah, that's right. The way it feels, it feels like there's sort of too much capital available. Put it another way, there's obviously gonna be competition in meaningful markets. It feels like there's sort of too many competitors that don't necessarily have strong differentiation.

• 13:58Speaker 00

  I think it's probably healthy, though. I think that, you know, there will be a culling, you know, just as the market progresses, but it does feel, you know, quite competitive. I'll just sort of give you maybe like a quick glimpse of the past couple of years. So we've had a remarkable growth there at Sierra. We, 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 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, was novel and it was part of our marketing, explaining what an agent was. Number two, people will 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.

• 14:41Speaker 00

  You know, 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 saying, we've evaluated it. We know what we want. Uh, we've heard of you. We've done all this evaluation. Here's an RFP, you know, like, let's go. And as a consequence, because the market has matured and, you know, by the illustration of the existence of things like RFPs, you end up in more competitive conversations. And then it's a question of like, why Sierra? You know, why Sierra?

• 15:23Speaker 00

  And, you know, I'm happy to talk more about that. I mean, obviously love to as a product. All the reasons are 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.

• 15:35Speaker 01

  Well, what, I mean, so like, you know, they're like, yeah, I'm bought in on an agent. It's like, why is it Sierra? Like, what have you found is like the most important thing that makes you win?

• 15:42Speaker 00

  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. You know, we want, we serve most of the US healthcare insurance market as an example. And we serve US banks, Spanish banks, UK banks, like, and these are companies that, you know, as you, if you know the industry, they're regulated by everybody.

• 16:06Speaker 01

  Yeah, yeah.

• 16:07Speaker 00

  It's easy to make a demo in AI. It's why like you can go on X and just see a thousand demos and like demos are cheap. But making an agent sort of 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, I think, having a really easy to use product, is we help companies move faster. We went live with Cigna in, in two months.

• 16:32Speaker 01

  That's crazy.

• 16:33Speaker 00

  Which is remarkable, yeah.

• 16:35Speaker 01

  I mean, how big is Cigna?

• 16:36Speaker 00

  It's a Fortune 20 healthcare company. And I was on stage with Sichin, who runs our AI practice there at the health conference. And he was talking about this. And part of that is like, how can you show up at a, like, we're really great at AI. Cigna is really great at healthcare. How do you bring those two together to move extremely fast? And so for a lot of our clients, like, the reason they bring us on is like, can you help us move quick, move quickly? And that requires knowledge of AI, knowledge of business. And I think we sort of show up with a greater sense of maturity there.

• 17:05Speaker 01

  You mentioned like, you know, that the pricing scheme was one of the difficult things, you know, in the past.

• 17:10Speaker 00

  Yeah.

• 17:11Speaker 01

  You know, we don't have to like belabor it, but obviously, you know, going from, you know, just buying a license to a cloud subscription and now usage based is like the future, like, what are you feeling as important in, you know, as you have created and probably continue to iterate on pricing? Like, what are the important levers for agent companies?

• 17:31Speaker 00

  We do something specific at Sierra that I'm sort of an evangelist for, which is outcomes based pricing. So it turns out our industry, the outcome is usually well defined. So in a service context is could the AI agent solve the problem? In a sales context, we do a lot of sales agents as well. Could it make the sale? You probably, your company's paid your salespeople commissions, right? Like, that's where you can measure the outcome. You want to incentivize the outcome. 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. And if you look at the history of software, like 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.

• 18:17Speaker 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? 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 know, 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 like the opposite, right? Because the closer you get to the outcome, the more valuable it is for the companies. They're actually willing to invest in it. And so my view is to the degree agents have a measurable outcome, outcome based pricing feels like the secular business model for agents.

• 19:00Speaker 00

  And I think it's quite both disruptive and I think a huge step forward.

• 19:03Speaker 01

  Why is it better than token based? So like, you know, if those are like, you know, I guess sort of like the two reasonable options now. Why is an outcome better than token based even over the long term?

• 19:16Speaker 00

  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 like, 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 their cost to serve and the quality of the product. You can have a really good engineer write it or a really bad engineer write it. No, you really care about 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.

• 20:01Speaker 00

  And I think this is actually. You know, I'm a huge believer in applied AI, but I actually define applied AI as can you describe your value proposition without 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 4.85. That's you don't mention models. I mean, models are an input to that, but not 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 sort of like a tool around AI. And I actually think that the closer you get to a business outcome, like it's actually,

• 20:44Speaker 00

  you should charge for the business outcome, which is uncorrelated with tokens. And I also think it's almost a measure of are you actually an applied AI company?

• 20:51Speaker 01

  Yeah.

• 20:52Speaker 00

  If you can, if you don't have to talk about tokens.

• 20:54Speaker 01

  Do you think that there will be markets either where things get so competitive that people have to price based off of like cost rather than value? Like, could that happen? Or maybe the other format for it would be if you can't describe the outcome cleanly? Like, for example, code coding, which we probably think is super important, obviously, it's like a little harder to say what the outcome is there versus like usage or something like that. So like, what are the conditions where like tokens do make sense?

• 21:22Speaker 00

  Yeah, so I mean, there was this old Apple site where they had sort of like 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 just like refactored a bunch of stuff. It's my, it's like the good analog, historical analog for why tokens don't matter. Because it was, he was, it was his way of saying, you know, fuck the man. Like, your lines of code has nothing to do with my value. And he was doing it to sort of like, you know, piss off a middle manager to make that point. But it's interesting is like, in the world of software engineering, people truly understand, like the customers of those right now are software engineers who intimately understand these models. So there's a little bit of a. The customer product market fit.

• 22:07Speaker 00

  So it's a nuanced point, but I'll say like where I see it might happen. So 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 of fact is AI becomes prevalent is you, you know, you're, you're just, you're, you're the 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 is a lead.

• 22:50Speaker 00

  And you probably will value quantity and quality of leads. And there's a math equation and that probably will be remain independent of token costs is my guess. And so I think a large part of AI is productivity and reducing, you know, costs. And there's a big part of it. But the other side of it is outcomes. And so could you imagine a world in four or five years where, you know, there's one coding agent that could actually produce something of greater value for your company? Will you value that or you just look at the token cost? I think probably you'll start looking for value is my guess. Will they all be the same? I don't know. You know, it's like the, well, I was just reflecting on over the past year,

• 23:32Speaker 00

  there have been all these articles about has like AI progress slowed down? And then in our world of software engineering, it's been the opposite. Like every new model comes out, 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 chat GPT for trip planning, you probably haven't seen a material change over the past year and a half because you reached sort of sufficient intelligence for trip planning a long time ago. If you're using AI to make, write Rust code. Codex is like mind blowing right now. So I think the, one of the interesting things when I think about like second, third order facts and like the progress of AI is, you know, where you, will you pass the horizon where like every model is sufficient in that task?

• 24:16Speaker 00

  And then there'll be some things where like the frontier continues to move and it's hard to imagine, but it's just like, we're in a crazy time.

• 24:22Speaker 01

  Where are we at with support agents right now? Like, are there still edge cases, last mile things like that AI can't do still?

• 24:30Speaker 00

  Yeah, we are though. I imagine a lot of the technical problems as opposed to product problems will become easier, but there, there's a lot of them still. So, you know, we at Sierra support most spoken languages in the world. And, you know, if you want to support Cantonese and Tagalog, most of the good voice models, you know, don't come from like the traditional Western model companies. Similarly, one of our clients is Safe Light Auto Glass. So it's like roadside assistance. And it turns out that like car horns, background noise, kids talking background, you know, are actually all fairly hard problems to solve.

• 25:10Speaker 00

  And even in some of the advanced voice mode stuff, if you are in a noisy environment, it constantly thinks it's being interrupted and things like that. 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 you're like, okay, that's probably going to be a commodity two years from now, one year from now. I mean, who knows? But you have to do it because you need to be the best at every stage of your company's existence. And I think then you're, the way we think about the world is we have a product which is called Agent Studio or Agent OS. And we're to make the, in three years, they'll judge us by our product. And right now we're probably, our clients will really put this way, judge by the technology.

• 25:52Speaker 00

  But if you go back to 1996, I remember when Netscape had a web server and Apache was new and done it like no one cares how you serve web pages now, like 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 tax centric sales cycle to a product centric sales cycle.

• 26:14Speaker 01

  It's interesting that you're obviously having to be the best at something that you know is going to get commoditized.

• 26:20Speaker 00

  Yeah.

• 26:20Speaker 01

  Which is probably not something, I don't know if you ever had to experience something like that in your, 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 like, you know, a lot of their life force for two years into something that everybody knows is just for two years, but it still matters nonetheless.

• 26:37Speaker 00

  It's crazy. I mean, you look at traditional, I'll just say enterprise software, consumer's a little different, but you think about you're building up this asset, your intellectual property is a fancy name for it. It's like, look at this platform that we're building and like, 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 a hundred percent certain we'll throw it away in the next 48 months. But I have to build it because if I don't, I can't serve the bank that has a big, you know, business in Hong Kong or whatever it might be where they, we need Cantonese support. So that is the reality right now. And so I actually think, I've been thinking a lot about this actually, just because I think it was Toby Lukew sort of said something provocative around, you know, when generating the code is, is easy.

• 27:20Speaker 00

  It's almost like the, the system and the prompts that are actually the durable asset, uh, you know, put it another way, could you sort of terraform your software from scratch? You know, it's the prompts that led to it. I do think that is sort of 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. Uh, I mean, if you think about like a product requirements document versus the code, what percentage of the emergent product that comes out of is in code? Almost like 90%, like a lot of the little detail.

• 27:52Speaker 01

  Yeah.

• 27:52Speaker 00

  Are in there. I think a little bit, it's like software companies of the future and the products that they make are just going to take a really different shape, uh, in the future. And I, I'm so excited to be a part of it. I, 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 like we're disrupting the craft of making what we're building in real time. And it's fascinating. It's like a fascinating time.

• 28:21Speaker 01

  I think there's a prevailing idea in tech that AI is moving so fast that like young founders have this massive advantage. And I mean this with no offense, you're not old, but you're also you're not

• 28:31Speaker 00

  You're telling me I'm old.

• 28:32Speaker 01

  No, you're 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 just rethinking everything. And so I'm curious, your own experience for yourself and for other founders you look around at, like, do you think by and large, young founders have the advantage? What does it take for more experienced founders to have the advantage?

• 28:57Speaker 00

  You know, I'm always a big believer, there was, I don't know if it's a real quote, but I, some VC said, you know, like, why was this, you know, founder able to, you know, 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 kind of naivete that is actually sort of a form of principled first principles thinking that a lot of young founders have. You know, you just don't know why this messy, bad products, you know, dominates the market. You think there's a better, faster, cheaper way to do it. And because you, you don't have any of the hard win lessons that can end up, you know,

• 29:39Speaker 00

  oversimplified analogies, keeping you from actually taking that leap, you can end up with, you know, Tony made DoorDash and didn't care about, you know, say Web Vans, Monzo, or whatever it was like. I can't remember all the, the, the dot com bubble companies. But I do think especially in enterprise software, the experience that, that some of our team members bring, including the old man, me and Clay, bring to it really does matter. You know, part of the reason we're able to serve, you know, so much of the Fortune 100 is We can go into a bank or a healthcare payer, healthcare provider, or revenue cycle management firm, or a big telecommunications company and understand their business.

• 30:22Speaker 00

  We're working with one large medical device companies consolidating 40 of their call centers into one, and we can have a discussion about like the change management of doing that. And that's not really a tech problem, but it does require, you know, understanding business. And I think if there's like, we always joke at Sierra, it's like the Venn diagram, like there's a circle of people understand like next generation of AI and people understand business. And we're like the company right in the middle of that, maybe the only one.

• 30:49Speaker 01

  Yeah.

• 30:50Speaker 00

  And that matters because I don't know, there's that sort of infamous MIT study saying all these AI projects fail. It's like none of ours do. And that's our value proposition. Like we can actually help you go live. And I think the experience has benefited us.

• 31:02Speaker 01

  Yeah. I'm curious, like, 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, you know, you've, you've, you've pulled away in a big way. And I'm sure there's a lot of just like daily blocking and tackling, but I'm curious if there are any like foundational decisions that you've made or strategic approaches that, you know, over the last couple of years you look back at and you're like, that was pretty essential to make this happen.

• 31:28Speaker 00

  I think there's two almost independent areas of investment. Not, not, they're not independent, but they're like very different. One is the product and one is our sort of 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 with very, that have been around for 200 years, you know, you need to work with mainframes, you need to work with a thousand different systems, you've done 10 acquisitions, there's all the like enterprises are messy. And so that's why you tend to have, you know, most, I'll say enterprise software, this design for larger companies tends to be quite extensible.

• 32:10Speaker 00

  Often that extensibility comes at a cost, which is, is it easy to get up and running? And so as a product designer, like one of the things I've just spent a lot of time thinking about is like, we're trying to have our cake and eat it too. Like, can you go live in two months and still be maximally extensible? And I'm really proud of the product that we 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 like 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. Because we knew when we started the company, we wanted to work with the largest companies in the world. Not only, but we want to be able to work with largest companies in the world. And it focused on that.

• 32:53Speaker 00

  And as a consequence, we just have a really unique partnership model. There's sort of a fashionable thing to talk about forward deployed engineering in Silicon Valley. We don't call it that, and it's a very unique model because it's not all about technology. Like, most of our clients build and maintain their agents themselves. It's pretty easy to do, but we show up and we help you be successful. And so it's like, we'll just show up like, we're not going to let you fail. Like, and I think that is a very different, because we have this outcomes model, outcomes based pricing model. We don't get paid unless it works.

• 33:23Speaker 01

  And so How much of that is technical versus like change management?

• 33:27Speaker 00

  It's a mix of both. You know, I don't know if it's 50 50.

• 33:30Speaker 01

  Do you do it as two people or it's one person who does both?

• 33:32Speaker 00

  We have a mix of roles. We've sort of evolved that. We try to hire really technical people in all roles, though, because part of our, our secret is we want, we want to be like, 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.

• 33:51Speaker 01

  Like a forward deployed change management engineer?

• 33:53Speaker 00

  Yeah, yeah, exactly.

• 33:54Speaker 01

  It's crazy what we're doing.

• 33:55Speaker 00

  And so, and what's really neat about it is if you're like a really talented technical person who wants to go transform an industry, you can do it at Sierra. I mean, you can go in and like, we're working with most of the healthcare insurance companies. Like, you want to change healthcare costs? And, you know, like, what a cool vantage point to do it. So we've been able to attract some really remarkable people, too.

• 34:12Speaker 01

  You said that it's not just support agents now.

• 34:15Speaker 00

  Yeah.

• 34:15Speaker 01

  It's like, what else are you finding shoots in?

• 34:18Speaker 00

  I'll give you one of my favorite relationships with Rocket. So based in Detroit, remarkable story. You know, their founder's done more for Detroit than I think any one person's done for any city, just like remarkable company. They own Redfin, which is a home search site. Rocket Mortgage, which is like 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 did of this mortgage service firm, you can then, when you're servicing your mortgage, you'll talk on the phone with an AI agent as well. So like everything from finding a house

• 35:02Speaker 00

  to originating the mortgage, to servicing that mortgage. I think it's pretty cool. And like, they have an amazing CTO named Sean Mohotro, like pretty visionary. And I love their CEO of Rune too, but it's like everything from finding a house all the way through servicing. It's kind of what we believe a lot of businesses will do is like, look at their entire customer lifecycle from, you know, also a purchase consideration, which is a fancy way of saying like browsing. I think homes are probably one of the more considered purchases that you could do. Through executing the purchase, they're having issues with it all the way through, you know, retention. And for a lot of, for example, a lot of our telecommunications customers, their AI agent is actually doing negotiations. So like you've probably negotiated your cable bill at some point, you know, probably.

• 35:46Speaker 00

  And so our AI agents are doing billions of dollars of negotiations for everything from, you know, satellite radio subscriptions to cable television subscriptions. It's pretty cool. I mean, it's like really, you know, over a billion dollars of mortgage.

• 36:02Speaker 01

  Basically just like all transactional communications eventually.

• 36:05Speaker 00

  The way I think about it is website is a technology, but your dot com, the one with your brand at the top is your website. We're sort of doing that for agents. It's sort of like 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, it's an interesting, as agents go, it's often interacting with other agents, right? If you think about a home and auto insurance company, you know, you may have a claim adjudication agent, you know, that's quite complicated. So our agent that's having the. Phone conversation when you're on the fender bender.

• 36:44Speaker 01

  Yeah.

• 36:45Speaker 00

  Will interact with that, but it is almost the intersection of all of that technology because it's sort of your, your front door. And our whole hypothesis is every company needed a website in 1997. Every company needs an agent in 2027 and like, we want to be that, that company.

• 37:00Speaker 01

  What's the nuance about like agent builders though? Cause I know you have like a view that like, just being like a generic agent builder is not the right thing.

• 37:07Speaker 00

  Yeah. I mean, I've been surprised how many like large incumbent enterprise software companies, like their first for rand AI was you can, an agent building tool. It just feels inevitably to be a commodity in my mind because uh, you know, maybe making a website was hard in 1995, but today there's like a million ways to make a website. Most of them are open source. So you have like cool companies like Purcell, which I love, but it's not like there's a huge market for this stuff. And, and in practice, I think the same will happen with agent building. I think OpenAI will have a great tool, probably all of the foundation model companies will, there will be open source packages like Langchain and Langgraph.

• 37:50Speaker 00

  The idea that you, 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 of where there's value is really going to be in agents that do things and you'll uh, 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'll be a finance agent that audits your financials. There will be one that helps you onboard a, you know, supply chain vendor.

• 38:30Speaker 00

  There'll be one that uh, you know, if you just think about onboarding a new vendor, it's like, there's a procurement process, the 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.

• 38:44Speaker 01

  Yeah.

• 38:44Speaker 00

  Agent building is not a product. Agent building is a technology.

• 38:47Speaker 01

  Yep. Speaking of the platforms, um, 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 or like, when did you start to have an inkling that like code was going to go vertical like this?

• 39:10Speaker 00

  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,

• 39:18Speaker 00

  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 AGI 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.

• 39:57Speaker 00

  As you said, it's really over the past three months that 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 engineering time 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.

• 40:40Speaker 00

  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 gonna, 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.

• 41:20Speaker 00

  And like my hypothesis is the companies that figure it out first will move the fastest.

• 41:26Speaker 01

  Yeah.

• 41:26Speaker 00

  And and the other part of that's the companies that don't will move much more slowly. It's fascinating to me. And Andre Karpathy, he had a really interesting post about this too. Like, I think a lot of folks 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 in.

• 41:44Speaker 01

  Yeah.

• 41:45Speaker 00

  Real time.

• 41:46Speaker 01

  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 its tentacles 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, salt, 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 club code and sort of like the the latest in coding. Is that going to change the way companies are built?

• 42:26Speaker 01

  You know, like one easy straw man 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?

• 42:40Speaker 00

  There probably will be a 10 person billion dollar company, but I don't necessarily think it'll be the norm. Uh, 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.

• 43:04Speaker 01

  They can't make more of us.

• 43:05Speaker 00

  They can't make more of us. They can build up their network. They can do other pricing, packaging. Uh, 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 are 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.

• 43:32Speaker 01

  Yeah.

• 43:32Speaker 00

  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.

• 43:56Speaker 01

  Yeah.

• 43:56Speaker 00

  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 of fact of the efficiencies of AI will be investment to compete. Lower prices or customer acquisition or whatever it might be.

• 44:13Speaker 01

  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.

• 44:18Speaker 00

  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 are, it's a bit simplistic.

• 44:41Speaker 01

  You're like, the same thing might not happen to every other function.

• 44:44Speaker 00

  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. 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 cargo ship still needs to be in the water. And I always bring this up, you know, like, just imagine you're on 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

• 45:28Speaker 00

  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. And so it definitely will change the way companies are built. But I think when people say everything will be 10 people.

• 45:41Speaker 01

  Right. It's like maybe just the stuff that lives in bits.

• 45:43Speaker 00

  Yeah, that's right. Which is a lot of the economy, but not the economy.

• 45:46Speaker 01

  Yeah, I mean, I, 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 all, there's like a lot of physical things. And I, I kind of tend to think that the value of that stuff's 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.

• 46:13Speaker 00

  That's, I think you're probably right. And, and some, 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 bit, a little bit simplistic.

• 46:38Speaker 01

  Do you think there's any cognitive things that are immune from intelligence? 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, okay, 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, you know, deep with OpenAI. Like, do you think that these other parts of intelligence also? You know, go the way of AI.

• 47:17Speaker 00

  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 into at 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.

• 48:02Speaker 00

  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, I was, 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.

• 48:23Speaker 01

  Yeah.

• 48:24Speaker 00

  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 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 codex writing code that was high quality wasn't experienced because, you know, I, I might have some of my identity tied up in that task.

• 48:45Speaker 01

  Yeah.

• 48:45Speaker 00

  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.

• 48:50Speaker 01

  Probably actually like a good like self actualization anyway to go through that and be like, ah, not my ability to code.

• 48:55Speaker 00

  I think there's, 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.

• 49:06Speaker 01

  Yeah.

• 49:07Speaker 00

  And so I think, I actually am quite optimistic that we will be human. We will all be status seeking animals. We all compete for the real estate here in San Francisco. And even though our standard of living will go way up.

• 49:18Speaker 01

  Yeah.

• 49:18Speaker 00

  We will all be jealous of people still. We will all compete. And as a consequence, I think humanity will be just fine. Uh, that's my view on it. And I think it's just hard to imagine.

• 49:28Speaker 01

  Yeah.

• 49:28Speaker 00

  But it doesn't mean it's, it's going to be catastrophically bad. I just think it's actually, I think will be largely good for humanity.

• 49:35Speaker 01

  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.

• 49:48Speaker 00

  Yeah.

• 49:48Speaker 01

  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, so 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, does it, is there like an essential humanity that like, gets sharpened?

• 50:18Speaker 00

  I hope so. Actually, one of the things, you know, I, I love the iPhones, one of the greatest inventions of this century. I hope we're not staring at a glowing rectangle.

• 50:28Speaker 01

  It can't be the right way to do it.

• 50:30Speaker 00

  And, 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.

• 50:40Speaker 01

  Yeah.

• 50:40Speaker 00

  You know, as a consequence of this, and that is the, a purpose of technology. Um, so, you know, just like the industrial revolution had leadites and globalization led to job loss in the Rust Belt of the United States, but certain goods got less expensive and other parts of like, these, there's not going to be no issues.

• 50:59Speaker 01

  Yeah.

• 50:59Speaker 00

  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 always liked the metaphor because it was so obvious before and after. Imagine being an accountant before Microsoft Excel and after Microsoft Excel.

• 51:30Speaker 01

  Yeah.

• 51:30Speaker 00

  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.

• 51:49Speaker 01

  Yeah, 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, open AI. 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?

• 52:31Speaker 00

  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, and 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, I think I listened to the acquired podcast. It's 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,

• 53:12Speaker 00

  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 creating the experience. I think it's really aligned with the 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

• 53:53Speaker 00

  free widely is a huge part of that. And we need to be able to to afford that. Yeah, 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

• 54:10Speaker 01

  It's funny, 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.

• 54:38Speaker 00

  I just think it's important we do it well.

• 54:40Speaker 01

  Yeah, yeah, no, 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.

• 54:47Speaker 00

  This is the other part of it is 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.

• 54:58Speaker 01

  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.

• 55:24Speaker 00

  Yeah, totally. We have three members of our board, which are sort of represent kind of like our kind of through rounds of investment. So Peter Fenton from Benchmark, Ravi Gupta, who Just left Sequoia, there's still a veteran partner there. And Neil Metta 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-founder, 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.

• 56:09Speaker 00

  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, man, Peter and I could sort of start on third base just because we'd 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 in the boardroom, it's just like, let's get to work. And it's fun, it was fun to, you know, sort of get the band back together there. But the fun part for me is I had never worked with Ravi nor Neil before. And like Clay and I, it's like, it's just, it's just a great board. Like it's like people we seek out advice from as opposed to people we report to, you know, every quarter. It's so, it's amazing.

• 56:54Speaker 01

  How do you think about, because you're both like known, like, you know, when, when OpenAI, we won't go back through the story, but like, you know, when OpenAI had its like, oh my God moment, like Sam was like, you know, right, you gotta, 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 a board? Like, you know, obviously you've got these particular relationships, but like, what do you expect that relationship to look like?

• 57:17Speaker 00

  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 boardroom. I've done this for the last two companies I've started and it's just been. Great to set 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.

• 57:55Speaker 01

  You're not running through slides.

• 57:56Speaker 00

  You're not running through slides and I find it to be incredibly, I, 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.

• 58:09Speaker 01

  The process of the writing?

• 58:10Speaker 00

  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 line? If I had more time, I would have written a shorter letter, like spend the time. Cause 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, 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.

• 58:53Speaker 00

  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 two of 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.

• 59:33Speaker 00

  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.

• 59:48Speaker 01

  Anything this year you're particularly excited about that you can share?

• 59:51Speaker 00

  I think the real exciting part is going to be adoption in regulated industries. I think we, we are moving beyond like the early adopters to everyone. And so I think if we, if we talk a year from now.

• 1:00:05Speaker 01

  You're gonna be doing the hard stuff.

• 1:00:06Speaker 00

  It's gonna be like the really hard stuff.

• 1:00:07Speaker 01

  That's awesome.

• 1:00:08Speaker 00

  And I have, if you want like a hot take, you know, I think my intuition as 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 if it'll happen this year, but I think that will happen.

• 1:00:28Speaker 01

  All right, well, I'll call you in a year and we'll do take two of this.

• 1:00:30Speaker 00

  That sounds great.

• 1:00:31Speaker 01

  All right, thanks so much for the spread. This is great.

• 1:00:33Speaker 00

  Thanks for having me.