AI办成事才收钱，转人工免费：Bret Taylor谈Agent如何重写软件生意

id="podcast-transcript" data-framer-component-type="RichTextContainer" style="transform:none">Pat Grady: Next up, we have Bret Taylor. He was part of the, I think, first APM program at Google, where he famously rewrote all of Google Maps in a weekend. Then he founded a company, then he went ahead and was just CTO of Facebook for a while. And then he founded another company, which we’re lucky enough to be in business with him on, which is redefining the front door for businesses. And Bret will be joined by our partner Ravi, who used to deliver groceries and now gives people money. About the same. Please welcome Ravi and Bret. [applause] Ravi Gupta: Yeah, but a lot of groceries. Okay. I thought Pat was saying I was the legend, so I was pretty upset when apparently it was Bret. Bret Taylor: You’re a legend to me. Ravi Gupta: Thank you. I really appreciate you saying that. Having Jeff Dean and then Bret Taylor is like having LeBron and Steph of engineers. It’s amazing. Or Roelof, two random rugby people that only you know. You know, like, that’s maybe an analogy you’d get. All right, I want to ask you a question. There’s very few people that have been described as 10,000-x engineers—probably in general—but also extremely, extremely few people who’ve done that and also been good at enterprise sales. Okay? And I think one of the things that will be fun today is we can be, like, highfalutin and talk about where the world’s going, but we can also talk about, like, how to sell things. And so the question I have before we get to tactical advice on that is like, what made you even think that you could do something other than just be an amazing engineer? Bret Taylor: Yeah, I actually think this is one of the greatest challenges to overcome as an entrepreneur. This is really reductive, but I think if you talk to an entrepreneur, they often have some unique insight on the business they’re creating. So maybe it’s a technical insight. If they come from a background in, say, business development, maybe they see an opportunity in the market that they can take advantage of as a partnership or business opportunity. In the financial services industry, maybe you see an inefficiency in the market you can take advantage of. The issue I see with a lot of entrepreneurs is you sort of become single-issue voters. It’s like every time there’s a problem in your business, if you’re a product person, you go change the product. There’s always the famed redesign, like the dead cat bounce before your company gets destroyed. And it turns out that as you’re growing your business, at any given point, you may have a go-to-market problem, you may have a product problem, you have a competitive problem. And I think the hardest thing is when you come out of business with what you’re comfortable with, you regress to sort of what makes you comfortable. For me, my most vulnerable moment was when I was 29 I became the CTO of Facebook. I was one of the older people at Facebook at the time. [CROSSTALK] Bret Taylor: I didn’t know at the—I actually was about to cuss. I shouldn’t cuss. I didn’t know what I was doing. You told me this was recorded. [CROSSTALK] Ravi Gupta: I think that you should not give away state secrets about OpenAI. Bret Taylor: Yeah. Ravi Gupta: You can curse. It’s fine. It’s good. Doing what the job demandsBret Taylor: And I wouldn’t have self described that I was sort of struggling in my job, but I think I was. I was sort of trying to do everything myself. And Sheryl Sandberg, who was the chief operating officer at the time, took me aside and kind of had a sort of come to Jesus conversation with me, essentially saying, “You need to hold your team to as high of a standard as you hold yourself. You need to stop trying to do the work yourself, and you need to identify the people who aren’t meeting your needs, replace them, but you’re not scaling the way you’re operating effectively.” And it was kind of the conversation I needed to have at that moment. I felt really shitty for about an hour, and then woke up the next day with kind of a fire in my belly. And I realized upon reflection—she didn’t sort of diagnose it this way, but upon my reflection, I was going into work every day and trying to say, “How do I conform this job to me and my strengths?” Instead of thinking, “What’s the most important thing to do in this job today, even if it’s not something I find delightful or interesting?” So I sort of came at the job, and I always modeled it as giving myself advice. Like, I was sort of my own board of directors. And sometimes it would be people, sometimes it would be business, sometimes it would be technology. I was the CTO, so hopefully it wasn’t that some of the time. And interestingly enough, I got more joy from it. I realized at that point I actually just appreciated having an impact more than I appreciated any act of doing my job. And so I ended up with this really nice reinforcement of, wow, I’m better at my job than I was last month because I’m not just doing what I like or what I feel comfortable doing. And that ended up a really virtuous cycle. So I’ve been a little bit of a chameleon. You know, it’s interesting. If I meet people from Facebook, they think of me as an engineer. If I meet people from Salesforce, they think of me like a suit, you know? Like, or I don’t know, generously I don’t know, something, the boss? And I’m not any one of those things. I just sort of showed up every day to, you know, to have an impact. And as I said, I just gained a ton of joy from it. And the reason I bring it up for the entrepreneurs in the room is I think at every stage of your company, at the beginning, product probably is all that matters, you know, finding your first n happy customers. As you scale, what you need to be great at changes. And I think having the self awareness and self reflection to actually change what you spend your time on is actually, I think, one of the greatest challenges of not having your company sort of get away from you and continuing to be an effective leader at that company. Ravi Gupta: I would tell you, I think it’s something—just so you have it, it’s something I have taken and share with my kids, which is like, don’t let something you’re good at become who you are, right? And I think that that is something I’ve learned from you that I really appreciate and I think you’re doing in the day to day. So tell people about Sierra. Why did you and Clay start it? What’s the vision? What are you guys up to? The vision for SierraBret Taylor: At Sierra, we help companies build customer-facing AI agents. We started on the hypothesis that every company’s main digital interface will be an AI agent, you know, and maybe 20 years ago your main digital presence was your website, your dot.com. Remember listing on Yahoo directory was the bee’s knees back in the day? Ravi Gupta: I do. I do remember that. Bret Taylor: Thank you, old man. Ravi Gupta: Yeah, thank you for noticing. Bret Taylor: And then for a lot of brands, whether it was your social profile or your mobile app, you know, companies have a lot of different digital touch points today. Our hypothesis—I don’t know if you measured it, like, what percentage of digital interactions happen on a touchscreen now versus a keyboard? It never replaces, but it certainly sort of displaces. Our hypothesis as you fast forward five years, the vast majority of digital interactions will happen via an agent. And as a consequence, every company will need their singular agent—not plural—the one that has their brand at the top that represents the whole of their customer experience. And so we’ve worked with a lot of different companies from ADT Home Security to Sirius XM to help them build their primary customer-facing AI agent. A lot of it is AI and it’s an agent, but a lot of it is also business. You know, like, what is the customer experience you’re providing for ADT Home Security? Your alarm might be going off, your alarm might be broken. For Sirius XM, someone might want a better price on their plan because their promotional period expired. So it’s actually really interesting because just like your website, I don’t think most people think of websites as a piece of technology nowadays, right? It’s almost just an expression of your brand and your business. That’s actually kind of the agents that companies are building on our platform. But I hope, you know, if we’re successful, if you run across a branded AI agent in the wild, I hope it’s powered by our platform. That’s what we’re trying to do. The application layerRavi Gupta: And one of the things that comes up a lot is like, what are the foundation models going to do versus what are the application layer companies going to go do, right? And I think you have probably the most unique vantage point on this, being the chair of OpenAI as well as building an application layer company. So can you help our founders here think about what is going to belong to them versus the foundation models? Bret Taylor: Yeah, I’ll say a strong opinion loosely held on this. So I think there’s really three big markets that I see, and I’ll end with the one I think is the most exciting. First you have the foundation models, and Jeff said something similar to this. But I think there’s going to be a ton of consolidation in the foundation model market. It’s fundamentally just a capital intensive business, just like building data centers—effectively, it is building data centers, you know, at the core of the expense. And as a consequence, if you have large scale CapEx, you can generate more CapEx and it sort of benefits scale. And as a consequence I think it will end up a little bit like the cloud infrastructure market: a handful of players, relatively low margin, but very, very high scale, and sort of collecting taxes from everyone in the AI ecosystem. I think the next market is really making tools—the proverbial pickaxes in the gold rush. And I think a lot of companies created prior to large language models like Databricks and Snowflake will sort of be in that category, but a lot of new ones as well. There’s a lot of nuance there. I think that will be a market that can really be threatened by the foundation model companies. I imagine every cloud infrastructure company has some—there’s probably an AWS or Azure equivalent to what they do. And so you end up with a naturally sort of more challenging, but it can be very high scale, but it’s just you definitely are closer to the sun, you know, the closer you are to the models themselves. And then there’s the applied AI market, and I actually think this will manifest its form as agents. So, you know, there’s companies like Harvey that make an agent for the legal profession. There’s companies like Sierra that make it for customer experience. There’s companies that make it for marketing, there’s companies that do it for visual effects. My view is this is sort of the new software as a service. The form factor of purchasing AI will be purchasing an agent that does a job. I think it’s a really exciting time. I assume a lot of folks in this room are working on sort of applied applications in AI. The reason I think it’s exciting are sort of twofold. One is I think it’s the way software should be consumed. I think right now a lot of particularly large enterprises in the excitement after ChatGPT licensed a lot of models. And as we all know, software is like a lawn, you have to tend to it. So I think there’s a lot of buyer’s remorse right now from a lot of spend and a lot of proofs of concept, but not a lot of value. The second thing is I think it changes the markets. You know, there’s these markets where selling enhanced productivity to attorneys is not a huge TAM. And so you run up against just a natural thing. Like, even if you get, you know, 80 percent market share, how big could this company be? But if you’re actually selling antitrust review or something, I don’t know much about the law, so I just made—does this sound credible? [CROSSTALK] Bret Taylor: You know, that has a ton of value because you’re essentially providing something that very high cost labor produced before. And as a consequence, I think if you look at the addressable market of all these vertical specific, domain specific agents, the market is gigantic. And actually it’s interesting, if you look at the public markets, if you look at the top five software companies that dominate the S&P 500, that dominate the stock market, none of them are sort of pure play software as a service companies. Obviously, Microsoft has some enterprise software, Amazon has AWS, but they’re infrastructure companies, they’re consumer. And if you look at the software as a service companies: ServiceNow, Salesforce, SAP, Oracle, they’re all sort of in that sort of $200- to $300-billion market cap range. You wonder, in this new world of agents, will we see our first trillion dollar sort of applied enterprise software company? And I think the answer is yes, because you’re going from selling productivity enhancement to selling outcomes. And outcomes are valuable. Some outcomes are extremely valuable. And so I think there’s been a little—understandably a little too much excitement around the models themselves. Not that—I mean, obviously at OpenAI we’re very excited about it, but as an entrepreneur I think that it’s sort of the pickaxes are obvious, but actually the value is elsewhere in my mind. I think the value is taking this amazing next generation technology, solving a very valuable business problem that was high cost before, and selling something valuable for an order of magnitude less money than the current cost is really fucking easy. So I just think it’s a great business, and I’m super excited about the future of the software industry as a consequence. Outcomes based pricingRavi Gupta: What do you think is the right way to price those outcomes when you think about them, right? I think that there’s all the former seat-based models, right? And now Sierra obviously does it differently. Maybe talk about Sierra’s pricing model, and then also talk about how applicable you think that is or isn’t to other agent companies. Bret Taylor: Yeah, at Sierra we do, we call it outcomes based pricing. So for our median customer, that typically means when the AI agent resolves the issue for the customer autonomously, there’s a pre-negotiated rate for that. And if we do have to escalate to a person, it’s free. We do that just to align with the business model of our customers. And I actually view it as sort of a natural evolution of software. We went from box software with a perpetual license to, you know, once you delivered software in a browser, everyone’s on the same version, so you needed to sort of invent a new business model to sustain R&D, which led to software as a service subscription-based business. And we just thought from first principles and said, “Hey, if you’re selling software that completes a job, what is sort of the secular business model for that?” And it felt like let’s pay for a job well done. You know, salespeople get paid a sales commission. Why not the AI as well? It does really disrupt the way you build a software company in my mind, though. If you look at particularly the enterprise software ecosystem, there tends to be sort of an arm’s-length relationship between software vendors and customers. Typically, you’ll sell a piece of software and be done. Then you’ll have systems integrators come in and spend for large-scale enterprise software deployments, sometimes six months or a year to implement that software. And I mean, by the time the software is being used, the vendor has probably not gone, they’re probably selling more things, but effectively gone for six to twelve months. So as a consequence, there’s almost like an active disassociation with the outcomes. And so you end up with a confluence of, I think, a lot of different factors that I think are interesting. There was a question just before I walked up here about agents that can code. What will that do to the professional services industry broadly? There’s a question of if the right thing for AI software is outcomes, how do you actually align your company with that kind of accountability? I think it sort of blows up a lot of the model. But that’s why, as Steve Jobs said, it’s more fun to be a pirate than it is to be in the navy. And I think it’s a really good time to be a startup, because most people in this room are not encumbered by a business model, which is a funny way of thinking about it. But if you look at the history of software, Salesforce beating Siebel Systems, ServiceNow beating the plethora of ITSM companies that came before, it’s actually much—closing a technology gap in your product is hard, but not impossible. Changing your business model is really hard. And you look at Microsoft transitioning from Windows to Azure, and how incredibly awkward that transition was. And Satya deserves a bunch of credit. Shantanu did a great job at Adobe going to ratable revenue, but there’s like a graveyard of CEOs who’ve been fired because they couldn’t make that transition, in part because public company investors are horribly impatient in these things. And so I just think that what’s exciting about AI is I think it’s going to give rise to new delivery models, new technology models, but as importantly, new business models. And I think that if you think about what are the opportunities for startups relative to incumbents, don’t lose sight of the business models. I actually think it’s usually one of the greatest advantages that startups have relative to incumbents. What’s different about building a company now?Ravi Gupta: Yeah, I think historically speed has been something, but I think on this point it’s like you also have this enormous benefit of you’re not encumbered by the old business model. You referenced the previous companies that you’ve been in and you started. One of the things we’ve talked about is like, there are things that are similar about building a company now and there are things that are different. What are some of the things that are the same as the previous companies that you’ve built that you’re doing now, and what are some of the things that are different? Bret Taylor: Well, at FriendFeed, my-not-so successful social network, we built our own servers. [laughs] Ravi Gupta: Can you tell the story about the Facebook IPO real quick? Just about FriendFeed for everyone, where you got recognized? Bret Taylor: I’ll do that at the end. I’ll do it at the end. Ravi Gupta: All right. It’s a good story. Bret Taylor: It’s a good story. Ravi Gupta: We stand between these people and drinks, man. You gotta make them laugh. Like, let’s go! Hit them with something. Bret Taylor: You’re pulling out the deep cuts. Ravi Gupta: Okay. Bret Taylor: You know, I think a lot has changed just in the infrastructure world. You know, I think literally we built our own servers at FriendFeed and, you know, like, brought them into the colo. We brought our site down once by tripping over a power wire in the colo. Ravi Gupta: [laughs] Bret Taylor: That was Sanjeev’s fault. We love him. So it’s just a different era. You know, I do think it is, as we’ve virtualized infrastructure and built just the software development lifecycle we have today from cloud infrastructure like Azure and Amazon Web Services, to GitHub and GitHub Actions, and all the incredible open source libraries, and then you have sort of the virtual infrastructure to help support your companies like Ramp, you know, and Rippling, you end up where there’s a certain—like, there’s a very different level of focus now in starting a company. It used to be you just had to do all these things to, like, build the scaffolding of your company—and it was actually like a non-trivial amount of work. And the thing I find just so exciting about, like, the future of entrepreneurship is there’s just so little overhead now in terms of just, like, intellectual overhead. And I remember actually just how hard it was to get credit cards for our employees. Like, they had to all get a credit check. I’m like, are you kidding me? It’s our bank account. And now you can print a virtual credit card with things like Ramp. It’s so easy. So I think we’ve just seen every aspect of starting a company that was about sort of like the operational scaffolding infrastructure do so. Many startups that you all have funded are now doing that. And so as a consequence, you can focus on just purely what defines your company and what makes it different. My color commentary on that is I actually think one of the mistakes a lot of smaller companies make is spending their resources and time on things that aren’t core to their business. And it’s more than a hidden cost. I think, like, every ounce of time you’re spending on something that fundamentally should be a commodity to your business is time you’re not spending on, like, selling your product to more customers or, like, working on, like, true differentiation. And it takes a lot of discipline, because a lot of those things are like catnip. You know, it’s like fun to work on that part of your business. And I always like to say, like, you know, Clay, who’s somewhere around here, we always talk about, like, what will make us happy a year from now. And that’s always our metric. And then you could take it to 10 years if you want to be like—no one knows what the hell is going to happen in 10 years, by the way. Ravi Gupta: If you don’t know what’s going to happen in 10 years, nobody knows what’s going to happen in 10 years. Bret Taylor: And I do think it’s very clarifying. And I just think it’s—it always surprises me how much I tend towards some of those things that are, you know, wholly undifferentiated at this point. What incumbents have to doRavi Gupta: Okay. Well, you mentioned some of the companies that Sierra works with, right? And some of those are companies that have been around for a long time, right? They are established companies. What does the “T” in ADT stand for? Bret Taylor: Telegraph. Ravi Gupta: Telegraph. Okay, so how do established companies … Bret Taylor: It’s cool, by the way—home security over telegraph. I actually imagine someone coming to, like, the Sequoia of that day. It’s like, “Home security over telegraph.” Ravi Gupta: [laughs] Bret Taylor: Like YouTube for cats, you know? And they’ve built that business. It really was. And now they’re actually doing home security with AI agents. What a cool privilege. I think it’s awesome. Ravi Gupta: And, you know, it’s a better acronym than ADAI, you know? Okay, but what do they have to do? What are the ones that are going to succeed? What are they going to do in a world of changing technology? And what are the ones that are not going to succeed? What is holding them back? And how can this group help all of those established companies succeed? Bret Taylor: Yeah, so I think it’s a really interesting opportunity for companies in competitive markets like home security, or a company like Sirius XM that’s got incredible unique original content, but they have a lot of cord cutting and a lot of competition around them. You have this technology and AI that drives incredible amounts of productivity in departments that had previously been incredibly underserved by software—everything from large scale contact centers to—we talked about things like legal departments, large operations departments. And as a consequence, companies that lean into this can really change the cost structure of their business. If you think about—I mean there’s companies that have, like, 20,000-person contact centers and, you know, this cost hundreds of millions of dollars every single year. And if you can take all of that OpEx and put it back into your business, you can lower prices, you can invest in growth. And so it’s really interesting. I think it is one of those opportunities where these shovel-ready applications of AI, even if it’s indirect, because it can drive such structural changes to essentially the unit economics of so many companies’ businesses, I think it will change market share. And so I think that it’s a little bit like the birth of the internet, you know? And Walmart did very well since the birth of the browser even in the face of Amazon. There were a lot of retailers like Blockbuster who did not. And so I think because most executives running these companies now lived through the web browser era, saw the birth of the smartphone and saw the growth of things like Instacart and DoorDash and others, they see this and they’re modeling what is the future of our industry going to look like. And you mentioned enterprise sales. I think the key thing about selling anything is speaking the language of your customer and having empathy. I think one of the things I see a lot with entrepreneurs is they’ll go into a meeting and sell their product. If you ever see a really good salesperson, the first thing you’ll see them do is ask a lot of questions. But then the next thing you need to do is actually listen and understand what they’re saying and then reflect the value that your technology provides to the problems that they just described. And I actually think that actually a lot of the technologies in AI will immediately benefit a lot of these businesses, but they’re being pitched by 20 AI vendors every single day, and they all sound the same. They literally all sound the same. You could see, like, the first call deck of startups that do completely different things and there’s, like, the same words on the slides. And so this is the—I think the real opportunity right now is how do you actually stand out in such a saturated market? Clay and I talk a lot about this because we both started web design companies in high school. You know, like, during the dot com bubble. I went door to door to flower shops. He did more, like, graphical things. Ravi Gupta: I think he made a little more money than you did in high school. Bret Taylor: He did. [CROSSTALK] Bret Taylor: He also got sued by the California Raisins, but that’s a whole ’nother story. So true story. His name’s Clay. He named his company Claymation. Bad luck. Sorry, Clay, I didn’t know if this was public. Public now. Love you, man. Ravi Gupta: [laughs] This guy doesn’t know anything about the law. Bret Taylor: Yeah, we talk a lot about the experience that we were young and not in the center of it during the dot com bubble where you didn’t just have Google, you had AltaVista, AlltheWeb. You had Inktomi, which was a B2B search player that we respected quite a bit. You had Amazon.com and you had Buy.com and Half.com, and you had eBay and you had PayPal and all the other folks pursuing payments. I think now, like, victors write the history books, so you look at all these magnificent companies coming out of that era and you forget that it was like a fight to the death. The idea that hey, maybe we should search the internet was not exactly novel, but the actual detailed execution of those ideas was paramount. And I think going back to how do you help companies like ADT succeed, the first thing you need to do is show up as a partner to them and help them solve their acute business problems. And that’s an uncomfortable sort of conversation because I think a lot of people don’t feel equipped to do it. One trick that I would just recommend is before you meet a customer, do deep research on them. And by that I mean the actual feature deep research in ChatGPT. Show up educated in these conversations, and I think you find the more you spend researching your customer and understanding their needs and less time you thinking about the next feature going to launch, the better that conversation will go. And I think you’ll end up finding that sweet spot between, like, where is the intersection of what you do differently and actual business value. Ravi Gupta: That’s awesome. Let’s go to audience questions. I just realized that I’ve taken up a lot of Bret’s time, so please go ahead. Building vertical agentsAudience Member: Thank you. Hi, I’m Robin. What are your learnings in building branded AI agents for specific verticals? And how is it different to building horizontally? Bret Taylor: I really believe in verticals in AI. I think that if you think about what the job proverbially of an AI agent is for a telecommunications company, and you think about what’s important to them versus, say, a commercial bank versus, say, a residential bank versus an insurance company who might be concerned about claims processing versus a health insurance company, that’s answering things like explanation of benefits, every single one of those applications is actually quite specialized. And right now, I think that the companies that can actually provide value quickly around these core workflows of these businesses that are actually valuable to them, actually sort of when I talk about coming into those conversations and actually providing value really quickly, just have a leg up. I am fairly skeptical of horizontal AI platforms. It doesn’t mean they won’t succeed, by the way. There’s always an exception to every rule. But things like LangChain, I think, probably will succeed. They’re open source, and you need to sort of develop a horizontal business in a different way. But just pure play enterprise business, I think it’s very hard to go in with a horizontal platform because there’s just lots of good enough, there’s lots of homegrown solutions, there’s lots of not invented here. And having a slightly better mousetrap is rarely—doesn’t pass the vitamin painkiller threshold, generally speaking. So my rule of thumb is the closer you get to solving a problem for a company, the more successful your business will be, assuming you’re talking about an enterprise business. The other thing that I really learned from Marc Benioff at Salesforce is, like, if you have one successful customer, make it two, and if you have two, make it 10, and if you have 10, make it 100. I do think there’s a certain amount of tactical excellence that comes in when you’re building a B2B software business. And ivory tower cleverness rarely wins. It doesn’t mean you shouldn’t have a long-term strategy, by the way, but if you focus on making your customers successful, that’s where the truth is and where your product should go. Sometimes you can be led astray by that method if you’re like, the first one was not representative. That’s rarely the concern, though. Usually it’s being very, very clever and sort of ivory tower with your strategy. So that’s why I love verticals. Ravi Gupta: Maybe one more. Pricing and the details of the buying cycleAudience Member: Hey Bret, I was really interested in the question around how you price AI agents. Specifically, have you seen customers being more open to you taking a cut of cost savings or of incremental revenue that you’ve created? And what are the main kind of pushbacks that you’re hearing from customers? Because impact pricing has been historically quite hard, so wondering what you’re seeing there. Bret Taylor: Yeah, we see interest in both. You know, if you’re owned by a private equity firm and have a big bunch of debt, you probably say the word EBITDA, like, 20 times a day. It’s like what you do at private equity-owned companies. And you probably care a lot about cost savings. Ravi Gupta: That’s basically all you do. You just walk around, “EBITDA. EBITDA.” He actually really simplified it. He got it. Bret Taylor: It’s like, see, I know finance too. And the law. Ravi Gupta: You have not ever let an ossified version of yourself slow you down. Bret Taylor: And in contrast, if you’re in a very competitive market, like, if you talk to any CEO, they generally care more about growth than they do cost savings. And in fact, I think one of the counterintuitive things—there’s lots of talk about with models becoming cheaper, will demand for infrastructure go down? No, in fact, demand will go up just because new use cases will emerge. I think the same will be true of most cost savings in AI. I think most sophisticated companies will recoup those cost savings and reinvest in growth. And so it won’t actually be cost savings necessarily, it will actually flow to other parts of the business. Just because that’s what capitalism does, right? It’s like saving a lot of money for what reason? Like, you want to grow, you want to beat your competitors. So sort of first principles and our lived experience is that top line matters more. There’s just no doubt about it. And if you can drive a measurable top line outcome, that’s always more valuable. But cost savings do matter because fundamentally, if you look at sort of productivity growth in the world over the past 30 years, it hasn’t been as dramatic as I think many people thought it would be after the ’90s where we saw a huge spike in productivity growth. So fundamentally, just like in the economy, we’re driving efficiency and productivity in the economy. And so the answer is definitely both. The interesting thing about cost savings is I assume those will be compressed over time. You know, right now, most of your AI startups are being compared to the labor costs. Ten years from now, when it’s all AI agents, you’re going to be compared to other AI agents. So the other thing about cost savings is it’s a temporary drug because the costs of actually all these things are going to change because of the presence of technology. So it’s a little bit like your mobile phone plans or—actually, I always think about it as, like, the computers we used to buy growing up in the ‘80s and ‘90s: they would get cheaper and better every single time. And that’s sort of where we are in this AI market. So our view has been, like, figure out what the outcomes are that your customers want. And it really depends on the application, honestly. Even how you price it is interesting. One of my favorite stories—I don’t know if this is actually true, but I heard it, and even if it’s not true, it changed the way I think, which was when LinkedIn was at one point trying to grow the recruiting business, they started out with some usage-based model, but it turns out HR departments don’t have a lot of license to spend in a variable amount, so making it a subscription model just helped with the procurement process. I love that example because it’s a really nuanced and insightful go-to-market point, which is that department, HR is generally a cost center in most companies, unlike marketing departments which have money flowing from the ceiling, this is a department that has to go through a pretty rigorous procurement department. So actually going to a subscription model was necessary to actually sell a product into that department. It’s that type of thing I think is where it’s like, is it cost savings or top line? Yes. Both. But also, like, who are you selling to? How do they buy? Who are the gatekeepers to approving how they spend? That’s how you grow an enterprise software business. You really need to understand who your decision makers are, who’s approving it, and actually, like, how do they budget? And I have a lot of counterintuitive things, but it’s sometimes easier for companies to prepay for things than to pay on demand. Counterintuitive, but just I think that’s like, you really need to get into the details of your buying cycle to answer that in an accurate way. Ravi Gupta: I’m going to wrap us up. Bret, thank you. They say you should do business with people you like, trust and admire. And you are that for me. So I really appreciate you doing this and all of us do as well. Thank you. Bret Taylor: Thank you. [applause] Mentioned in this episodeMentioned in this episode: The dead cat bounce: a small, brief recovery in the price of a declining asset (i.e., “even a dead cat will bounce if it falls from a great height”) <div class="framer-mcvrsd" id="