# Why Model Providers Will Kill Many Startups Moving into the Application Layer Why Deepseek is not a Threat to OpenAI & Why OpenAI Beats Anthropic · Apps vs Models vs Infrastructure: Where is Value in AI with Sridhar Ramaswamy, Snowflake CEO 20VC · Feb 10, 2025 · 55 min · 9,896 words Speakers: Sridhar Ramaswamy, Harry Stebbings Source: https://www.996.fm/episodes/20vc--ep-fe07d2a1/ ## Cold open **Sridhar Ramaswamy** [0:00]: I think it is terrifying to be a startup building on top of OpenAI. The line between an infrastructure provider and application provider today is super blurry. There's basically no guarantee that OpenAI or Anthropic or Microsoft or Google are not going to go create. You're not going to switch from ChatGPT to DeepSeek. It's a product, it's not a model. There's a big difference, Harry. There's a reason why Anthropic hasn't done as well because it operates sort of at the model level. It's all of the additional things that go into ChatGPT that I think has staying power. **Harry Stebbings** [0:36]: This is 20 VC ## Intro **Harry Stebbings** [0:37]: with me, Harry Stebbings. Now today we answer the core question, where will value be generated in the next generation of AI? Will model providers become application providers? And so much more. Joining me for this incredible discussion, we have Sridhar Ramaswamy, CEO of Snowflake. Snowflake is a $60,000,000,000 public company with $3,500,000,000 in revenue, growing 30% per year. Before Snowflake, Sridhar spent fifteen years at Google playing a central role in the growth of AdWords and Google's advertising business from $1,500,000,000 to over a $100,000,000,000 in revenue. ## Sponsor read **Harry Stebbings** [1:12]: But before we dive in today, here are two fun facts about our newest brand sponsor, Kajabi. First, their customers just crossed a collective $8,000,000,000 in total revenue. Wow. 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Banking services provided by Choice Financial Group, column NA, and Evolve Bank and Trust, members of the FDIC. The provider of this testimonial was not compensated and is a client of Mercury Advisory LLC. You have now arrived at your destination. ## Conversation **Harry Stebbings** [4:24]: Sridhar, I'm so excited to have you on the show, man. It has been so long since we saw each other last as well. So thank you for doing this with me. **Sridhar Ramaswamy** [4:32]: Thank you, Harry. Amazing to be here. Twenty VC is absolutely one of the iconic names in investing. Excited for this. **Harry Stebbings** [4:42]: Dude, you're very, very kind. Listen, I spoke to Margaret before the show, and she said, like, you'd be really missing a trick with Sridhar if you went straight to AI and straight to actually, like, CEO ship. And so she was like, you gotta just get a little bit more personal. And so I was like, okay, Margo. Tell me more. And she said, start with, as your younger self in college or in your first job, did you ever imagine yourself becoming a CEO and why? **Sridhar Ramaswamy** [5:09]: No, I did not. Certainly not when I was getting a bachelor's, certainly not when I was getting a PhD. In fact, I think when I was getting a PhD, becoming a professor sounded more like the ideal. But at some point I was not that excited about doing research, and that's when I switched over to software engineering. And even in software engineering, it's very much of aspire big, but take little steps. And, you know, when you're at the right place at the right time, great things happen. **Harry Stebbings** [5:40]: My question to you is, when you look at graduates coming out today and entering the workforce, I know you also have two boys who Margo told me about. What would you advise twenty, twenty one year olds coming into today's workforce who are bluntly scared in some ways looking at AI going, where is there gonna be long term jobs? Where is there not? What would you advise a 20, 21 year old entering the workforce? **Sridhar Ramaswamy** [6:05]: My kids and I used to talk a lot, they're 25 and 23, about what they should work on. Roughly my advice to them was find something that you're passionate about that society values. I was like, yeah, don't pick these noble professions that we all pretend we value, but in fact we don't. I was like, being a teacher, it's really hard. Like, God bless them, but hopefully by the time you have graduated, you have skills and passion in something that society values. Obviously, everything is undergoing a lot of change. The best advice I have for navigating the environment is be open, be nimble about where change is coming, embrace change, don't be one of those people that's like, yeah, the internet is never gonna be a thing, it is, AI is. And so embracing the change, seeing what is possible, putting in the time, putting in the dedication to both excel at the job, but be thinking about where things can go. I think that core formula of drive and malleability is the advice that I give to a 21 year old. Honestly, it's the thing that I look for when I am trying to hire a senior exec into Snowflake. **Harry Stebbings** [7:17]: Totally agree with you in terms of the importance of being nimble and being flexible, something that most HBS grads struggle with, I found in venture. To be quite honest, I see so much of the debate going around about, hey, software engineering and, like, engineering, it's like the first place that AI is gonna really dominate, and you're starting to see that with Copilot and a lot of the tools that we see around that. Do you disagree and say, no, there is immense value in software engineering moving forwards? Do do it, students, keep going. Or do you go, no, that is actually the first to be impacted? **Sridhar Ramaswamy** [7:50]: I think all kinds of knowledge professions are going to be impacted in a big, big, big way. The simplistic, but fairly accurate description of what AI can do, it is this incredible translation layer between all kinds of knowledge. Unstructured, structured, you can make sense of it all in a way that only humans were able to. So I would say any knowledge worker, absolutely, including software engineers should embrace and see where this technology is going to go. I think it is too early to jump to conclusions on does this mean then that even software engineering becomes an apex profession or becomes like a thinned out profession. After the internet, there was not a particularly good reason for every city in every country to have like foreign bureaus sitting in Washington. Why? Because the big ones, the New York Times can reach every part of the world. You get pretty good coverage, maybe you don't like them, maybe you want some other viewpoint, but it became a handful. So things like journalism went from being a broad based profession to one that was narrow. Same thing happened to music. It is, I would say a little hard to predict how much impact it is going to have, but to the extent that software will continue to be a huge part of everything that we do, I still see tons of opportunity in applying, you know, software and AI to more and more areas. So I'm kinda not down on software engineering as a profession any more than say I am down on analysts or CEOs as a profession. I joke to people, I'm an email machine, that's all I do. I talk and I write and I read. And so embracing the future, seeing where it can go, being nimble is what it's going to take. I don't think software engineering is going to disappear anytime soon. **Harry Stebbings** [9:43]: I love the simplicity, I'm an email machine. People always think that you just get better over time in CEO ship and you're just phenomenal with the years that go by and you present this wonderful facade. Can I ask a weird one? What have you got worse at over time? Oh, it's a good question. **Sridhar Ramaswamy** [9:58]: You know, like, look, physical skills are harder as you grow. Yes, once upon a time, I would not think twice about a 20 mile run, no prep. I was like, yeah, okay, let's go run for a bit. Not going to happen today. But I think the mental thing is very much that is under your control. And that's the part that I'm happy about. I'm relentless in terms of pushing myself both to learn, to measure, to adapt. When it comes to physical stuff, it is harder. Now, other thing that we have to be realistic about as you grow older is your ability to just sink a huge amount of time into a brand new area is kind of limited. You have to have the humility about stuff like that. I joked, you know, my sons, one of them is like 23 years old. I'm kinda like, yeah, you're not really going to be a concert pianist in your life. That part is done. And so we have to accept what is changeable and what is not changeable. But especially when it comes to mental things, I would say for the agile driven person, the world's your oyster. I mean, and now you have all of these like language models that can create custom programs for you and do just amazing things that you'd never be able to do before. So in that sense, I think there is even more opportunity than before when it comes to the mental stuff. **Harry Stebbings** [11:12]: You said about 20 mile runs, you said about relentlessness. By the way, I think you're still an Adonis, so I don't know what you're talking about, but I spoke to many of your friends, and they said you operate with an intensity that is incredible. And I'm like, gosh. It's another just, you know, praise of Sridhar. And they said, but no. People around you struggle to keep up. And I'm by no means running 20 miles and, you know, as athletic as you, but I am intense and people struggle to keep up with me too, and I struggle with that. What advice would you have for me and other high intense CEOs who need to bring people with them, but it's difficult. **Sridhar Ramaswamy** [11:51]: I think making sure that people understand the big picture, the fleeting nature of opportunity, and how quickly it can disappear. You know, I run a company that is making, call it 3,500,000,000 roughly a year. If you think about things like the world GDP, inflation adjusted, it grows by what, one, two, 3% a year. It is a hundred years, if something is growing at a percent for it to kind of double or a little bit less than that, give or take. You're talking about doing that in two years. I think the first thing that I tell people is we are extraordinarily lucky to be in environments that can generate this much value and this much growth. And to sustain it and accelerate takes extraordinary people. It's not for everyone, and I'm okay with that. But let me tell you what it takes to succeed at Snowflake. The expectations are high because the returns are high, the opportunity is big, and the opportunity cost is even bigger. And so I think it's a question of what do people want to be a part of? At Snowflake, we absolutely want to be that data engine for every single enterprise on the planet. I think that's a pretty amazing mission. Plus we get to build an iconic company along the way. It takes special people. I don't have to make excuses for that. **Harry Stebbings** [13:14]: When you hire someone thinking that they are able to scale through different stages of company development and you are wrong, why have you been wrong? These things **Sridhar Ramaswamy** [13:24]: are unpredictable. Life is very long and people also change over time. There is a certain something that take your pick, $1,050,000,000 pounds is going to do to people. Part of the reason why I joined Google in 2003, a year before the IPO. Honestly, part of the reason why I succeeded, because a bunch of people that joined in two thousand and one and two, all of a sudden were worth $50,100,000,000 dollars and they said, life's great, I'm up. Honestly, yeah, I don't blame them, but that's part of what it takes to have a driven team. Not everybody can scale. I've had lots of conversations with people about what does it take to double your team. And roughly my advice has always been, listen, every time your team doubles in size, all of the things that used to make you wonderful for your previous team are typically massive inhibitors for you to succeed in your new job. And it requires a lot of reinvention for what people have to be and how they have to operate. You know, there are quite a few people that can make these transitions that will adapt and that will thrive. I almost see it as my duty, my job, my responsibility to give people those kinds of opportunities. But look, I'm relentless and cutthroat in that I give people time, I give people opportunity. One of the things I've learned as an adult is how not to shirk from unpleasant conversations. I talk to people about what is working and what is not working. I give them time, and if it doesn't work, it doesn't work. I have demoted people, given them half their job and said, this is better for you, one of the hardest things you **Harry Stebbings** [15:01]: can do **Sridhar Ramaswamy** [15:01]: in your life. **Harry Stebbings** [15:02]: Do you have any tips on how to actually force the hard conversations? Don't laugh. Whenever I have an email that I don't want to send or don't know how to send it, I force myself to go in the lift in my apartment building and whatever I've written by the time I get to the other end gets sent. And that's the deal with myself. Do you have any tips on how to actually force that? **Sridhar Ramaswamy** [15:22]: Yeah. I mean, the first thing to remember is that conflicts do not resolve themselves. You kinda have to internalize that postponing things is going to make them worse. The more you postpone, the worse it gets. Telling yourself that is important. And the other thing is avoiding the hard conversation. It's typically also doing the other person a disservice because you're not helping them. Not all hard conversations need to be like, you're out of your job. They can be much more of here are areas where I think things need to go better. And let me tell you why. Let me tell you what my expectations are. And I think it's also important to be respectful, and I find it important to be just painfully humble in these conversations, where I will typically go into the conversation, and I'll go, listen, this is going to be a difficult and unpleasant conversation for us. I'm just coming out and telling you, and I'm not pretending I know all the answers. This is super awkward for me to have this conversation, but I feel it's important that we have the conversation. To me, that combination of you know, respect, straightforwardness, and humility goes a long way. **Harry Stebbings** [16:34]: I agree totally, especially on the humility side. Final one before we move to AI, you mentioned like the demotion element there. That's a really hard thing to do. If you're willing to demote someone, does that not just mean you should fire them? Someone once said to me, if you're willing to take less, you should never do the deal. And I kind of apply that here. If you're willing to have them but give them less, should they not just go? **Sridhar Ramaswamy** [16:54]: No. Remember, all of these are fast moving environments. An area that you thought could be done fine with 20 engineers blew up. All of a sudden it needs a 100 people. And the person that did the job fine with 20 now is holding a portfolio of like 40 people needing to grow to 100 and they're struggling. And the business can't wait. It's not that they're bad people. It's not that they were incapable of doing a good job. But to me, finding the right context, finding the right framework to help somebody succeed at a given point in time, it's okay to have those sorts of conversations. I had one director who accidentally became in charge of two different areas. And part of what I went and told them was, I am taking one of these areas away. By the way, the thing that you have in your hands is going to grow to be, I think I promised him a $40,000,000,000 business. I was like, in five, six years, this was Google Shopping. This is what we are looking at. There's a big opportunity, but you get to focus on a single job. That person took the job, eventually became a VP, was enormously successful. That's a lot of selling men because people are like, whenever you have a conversation like that, the first reaction people have is like, I'm a failure. No, you're not. You've been given an impossible job. Let's shape it to make you succeed. Again, that is real leadership. Going and selling something that people don't want and painting a vision for the future and getting them **Harry Stebbings** [18:27]: to stay, that's hard. My question to you, final one, I promise before we do AI, but it's just, do you think richer leaders make better leaders because you are more convicted, you're not so worried about downside, you're not fearful about bluntly, what happens if I lose my job or if something happens? Do richer leaders make better leaders? **Sridhar Ramaswamy** [18:49]: No, I think it can make them callous. It can make them a little too tolerant of massive amounts of risk. It's a balance. You always have different constituents. And it's important to remember that as a leader, like it's not just you, it's the employees in your company, it's your shareholders, it's your customers. We went through a pretty difficult time as a company last year. That's when it sort of clearly came into focus. This affects a lot of different people. It isn't always about swinging for the fences. Yes, sometimes you have to make that dramatic 90 degree left turn to get to some place. But I don't think that being in positions where you're personally unaffected by the outcome from a dollar perspective is necessarily a positive thing. **Harry Stebbings** [19:44]: I think it does actually shape investor mentality. I think you can be less fearful of downside and more see upside opportunity. I wanna move into the world of AI as if we would. I wanna first just get your advice on a seat. You know, we walked around High Park together, and I'm looking at this market today as an investor going, where is their sustainable value going to be generated? It seems like models get commoditized faster than the thing. DeepSeek has shown that in the last few weeks. A lot of application layer material seems pretty light in terms of just building on top of commoditized models. How do you think about where sustainable value is in today's AI market? It's a good **Sridhar Ramaswamy** [20:23]: question. I had a conversation with some folks from OpenAI, an application company, one of these coding platforms. And what this conversation was about is the line between an infrastructure provider and application provider today is super blurry. In a weird way, if there is a, let's say a brand new application to be created, there's basically no guarantee that OpenAI or Anthropic or Microsoft or Google are not going to go create. All of these at this point are driven motivated companies and they pretty much go like, Oh, coding assistant that's taking off. Oh, that's fine. I'll do a coding assistant or something else. Oh, I see, people are generating much better legal documents. Ah, maybe we should release like a legal ChatGPT, something. To me, I think that is part of what makes value creation in today's environment, like really tricky to figure out. I would say that the place that absolutely is value creation is with companies that have a set of customer relationship, deliver clear value and are willing to embrace AI fast enough that a disruptor is not going to unseat them. This is why I feel good about Snowflake because we are a data platform. We help people collect data, make sense of data, run analytics on the data, run predictive things like machine learning on top of the data. I see AI as a massive accelerant for the data life cycle and also for data access. Will somebody that starts with these foundational new capabilities as the starting point be better than Snowflake? But starting from zero mind you, the bet is that they won't be. So I see like AI clearly creating value. You see, for example, Salesforce doing this with some pretty cool work with agent force. They're very much going, we have relationships, we are going to disrupt ourselves, we are going to be out there. But all new value creation, I had to tell you, it looks very, very murky in terms of long term value. There's value in product. It's really important to understand that OpenAI, I think will be successful not because they are always going to be the best and cheapest at creating foundation models, because they have a product experience that by some accounts has half a billion loyal users. That is really hard to create. **Harry Stebbings** [22:53]: Do you think they're loyal? I mean, DeepSeek gets to number one in the charts in a day. **Sridhar Ramaswamy** [22:58]: You're not going to switch from ChatGPT to DeepSeek, and OpenAI is not stupid. If they can host DeepSeek to power some of ChatGPT, they will shamelessly do it as they should. Why would you not switch **Harry Stebbings** [23:08]: to DeepSeek? It's free. **Sridhar Ramaswamy** [23:10]: So is ChatGPT. And it comes with a bunch of additional features. It's a product, it's not a model. There's a big difference Harry. There's a reason why Anthropic hasn't done as well because it operates sort of at the model level. It's all of the additional things that go into ChatGPT, that ability to create images, that ability to do that little upload, that ability to run that little bit of code. It is a put together product that I think has staying power. **Harry Stebbings** [23:38]: I've had Sam on the show and he was like, you know, we will steamroll startups. He put on a 20 VC jumper, which made me very happy. I was thinking branding. And then he first thing was like, we're gonna steamroll startups. And I'm like, oh God, oh no. That's not great for my venture fund. But my question to you is, if you were Sam then today, what would you do? We had the founder of Grok on the show last week, and he said he has to open source. **Sridhar Ramaswamy** [24:03]: Sam is succeeding, as I said, in terms of having a consumer product that is approaching, let's face it, like Meta and Google scale. Yes, some of it is because of the incredible publicity machine that Sam and OpenAI are. But dude, which was the last company that you heard about that got to 500,000,000 users without really paying for advertising in recent years? That's not a social network. Like none, what is happening is truly remarkable. There's always been a little bit of mystique around OpenAI and their closed source models. And it's also now becoming clear that they are good at misdirection in terms of where they tell people hard problems are. And it is good that people like DeepSeek, went and busted some of those myths. But I would separate out the success of OpenAI, the company, from what's going to happen tomorrow. Obviously there are other things that they want to do, but so big on AGI, you know, there's the new company that's in the mix. But one point that Sam made to you, I completely agree with. I think it is terrifying to be a startup building on top of OpenAI. **Harry Stebbings** [25:14]: My question then is, to me, there was like two points where I'd be like, what happens there? Which is like, number one, when you look at Nvidia beneath you in the stack, I'd be concerned that they start to build a Snowflake competitor. To what extent do you worry, consider Nvidia moving into your segment and being a competitor? **Sridhar Ramaswamy** [25:32]: I have to have the same worry about the CSPs. I always have to be watchful about things like that. AWS has Redshift, Microsoft has Fabric, Google has BigQuery, Oracle has their data warehousing platform. You should always be worried about being a little mouse in the land of giants. If they sneeze, might get blown off. I mean, I get it. But on the other hand, I tell people, it's OpenAI and Anthropic that have created the best models on the planet for the last three years. It's not Microsoft. It's not Amazon. It's not Google. You know, Gemini is good, but let's face it. It's at best a fast follow. The thing that I tell people, and you know this better than anyone else Harry, a startup with product market fit is like a living breathing thing. It's magic, man. It's not like you and I know how to just create it just with some words and with some ideas. Snowflake is a manifestation, is a realization of that magic. It is hard to create a data product by copying. You have to keep innovating. Obviously, it's like Databricks has come up in the last five years as a very credible player in the data space. More kudos to them. But there are things that we at Snowflake are very proud of and very different from how Databricks operates. We need to continue to innovate and be up there. But, dude, money doesn't buy you amazing foundation models, doesn't buy you Snowflake. **Harry Stebbings** [26:56]: My question on Nvidia was one side of that. The other side you mentioned was Databricks. And I spoke to friends, board members, investors, and he said that potentially Databricks might be ahead in AI workloads with Mosaic, with MLflow, direct model hosting. How do you think about that? Do you think Snowflake is behind in that respect? **Sridhar Ramaswamy** [27:15]: So we should separate out machine learning from AI. I joke to people that all of the machine learning people branded themselves as classic AI. Look, they were first to market, that was their sweet spot, and they've been good at it for a while. We were very much in catch up mode. But AI is a much younger field, Didn't really exist, let's call it pre ChatGPT. There, I feel incredibly confident that we are not only cutting edge, but ahead of them on a number of fronts. We have thought of both methodically, but very quickly made AI into a reality at Snowflake in everything from how do you do data transformations, data engineering better, to how do you make sense of unstructured data, and how do you get reliably to structured data. And then we are putting all of this into this agentic framework called Snowflake Intelligence that is coming out. When it comes to AI, I feel very good about where Snowflake is. That isn't an issue. I have work to do in terms of getting the word out there, getting more and more customers. We have amazing marquee names, a ton of them that are using Snowflake AI in production. I feel good about where we are on that side. And it's a fast moving space. The thing that I pride myself on and the AI team, many of whom I've worked with for a lot of time is in fast moving spaces, my attitude is I can run as fast as anyone else, bring it. **Harry Stebbings** [28:40]: I love you, ChatGPT. I'm like, okay, I'm not gonna fight. Like, don't worry. I'm not gonna bring it. That was fantastic. You kind of remind me of Nick from Revolut, which is like, when you're talking, you're like, you know what? I don't wanna fight you. You you do you. I'm gonna support you. I'm a believer, dude. Keep going. So, yes, I completely get you. Can I ask which structure do you think aids innovation better and aids winning better? Being a super late stage private today, like Databricks, or being a public company, like Snowflake? **Sridhar Ramaswamy** [29:17]: Innovation is not an option. It's just something that we have to do. Do I have more constraints than Databricks being private? Absolutely. I mean, it's very clear that they're buying a bunch of business, that they don't have to worry about things like free cash flow. They have doubled the number of salespeople that we have. But as I also tell people, you know, it's easy to lose a lot of money. It's very easy to be uncalibrated about spending money. You should be careful what you wish for. Do we operate under constraints? Absolutely. But that's what innovation is about is how can you drive in the face of constraints. And you know this, in some ways like DeepSeek is yet another illustration that, you know, having rich uncles is not always a good thing. **Harry Stebbings** [30:01]: Where have the constraints helped you and why have they hurt you? **Sridhar Ramaswamy** [30:05]: With AI, for example, we said we were not going to be unreasonable about how large that team is. I didn't ask for a blank check. We said, we know what we need to do. We need to have clarity around the things that we need to build, and we need to be very good at doing it. With a modest investment, we were able to very quickly catch up in AI. I think having those constraints drives clarity. You're not trying to do everything and you're not also trying to chase every possible unscalable kind of business. Constraints can be problematic. There are dramatic market reactions, for example, because people can over interpret changes that happen quarter to quarter in numbers. And I would say in some ways, like the Snowflake stock journey, the ups and the downs, and then the ups are a reflection of the scrutiny that a public company faces. In an ideal world, I am able to tell my team and investors, we got this covered, just don't worry about it, everything will be great. Absolutely you have to worry about it it because people are making mortgages based on what their stock is worth. And so you get into externalities that are difficult to manage. It raises the bar on operating responsibly. That's sort of what we had to learn quickly last year, but that's an example of something where being a public company, you don't have to worry about dramatic reactions because they can end up having a bunch of second order consequences. **Harry Stebbings** [31:31]: If you could, would you rather take the company private and remove the constraints? **Sridhar Ramaswamy** [31:35]: I think the visibility is a good thing. You don't get to bullshit anyone. It provides for liquidity. Being able to grade yourself, I think is an important part. It is very easy to fool yourself into thinking that things are gonna be great and you don't get actually get any feedback. We are in the world of almighty dollars. They are well calibrated. Either you make money or you don't, either there's free cash flow or there's not. I think that dose of reality is actually helpful. Even if you look at the competitor that we talked about, for a few months, was all about like amazing AI is going through the roof. I haven't heard much from them about AI recently. All of a sudden, amazing, it's equal going through the roof. It feels like a bit of three card Monte to me. And I think being a public company forces you to be open and show your work all along the way. **Harry Stebbings** [32:23]: I wanna touch on two areas, which is kind of enterprise adoption of AI first. You know, I was sitting with a bunch of CEOs at a summit the other day, as painful as they can be as we both know, and they were like, hey. We're still waiting on you fuckers from technology land to actually deliver much ROI. And my question to you is, do you think we've seen, like, excitement and then we're gonna plateau like we did with self driving, Or will we actually just see the exponential acceleration of adoption within enterprise and it will bluntly be a very smooth hockey stick up into the right? **Sridhar Ramaswamy** [32:54]: I think it is going to be gentler in terms of just growth. On the other hand, I can very confidently tell you AI is creating value today and it'll continue to create enduring value. Many, many things that used to be just crazy hard for you and me to deal with are easier. You know that, I know that. And if some CEO is telling you that they're seeing no value from AI, I'd be like, I'm not sure you know a whole lot. So let's get into the examples, right? The obvious easy ones, okay? I was at Davos, I did 30 meetings. I absolutely used things like dictation and transcribing tools to write notes for myself. I also hand wrote a whole lot of notes. And somebody on my team is like, oh, dude, 25 pages, really? I don't want to read this. How about you give me a summary? I just take it, I plunk all of my notes into cloud, and I go like, I want a one line summary per meeting. Out comes that beautiful concise summary. It's magical. Similarly, we have internal chatbots that have access to structured data and they can handle questions that you have to like click around in dashboards and like you need to provide a lot of context. Again, incredible value. **Harry Stebbings** [34:06]: Davos is an interesting collection of world's biggest CEOs. Yeah. Was there any enduring takeaways for you from the sentiment that you saw at Davos? **Sridhar Ramaswamy** [34:15]: I mean, first of all, I took a very utilitarian view of Davos and less into, you know, the bigger thing. This was my first time and I was terrified by the idea of spending five days away from work, especially with like board and earnings coming up. It was well worth it. Amazing number of meetings, amazing number of key folks from companies. The message that I heard from CEOs was much more that of help us create utility, tell us what is possible. And when I talked to them, both about what we can do with unstructured data, in terms of being able to create a chatbot on a document corpus quickly, our structured data, they got it. But then when I tell them, now you get to mix and match them and create agentic platforms, where you can access a whole lot of related information in one place, people are excited. When I talk to them about here is how you can automate parts of underwriting by bringing together all of the structured and unstructured information that you need to have in order to underwrite like insurance for a building, people are like, oh my God, that is amazing. You're correct, we need to continue to be focused on utility, but I didn't face a lot of like rampant skepticism about who he, because I'll just rip out my phone and show them, here are the five stupid and fun things I did yesterday with AI. **Harry Stebbings** [35:31]: In terms of, like, innovation speeds, it feels like we've never seen incumbents innovate at the speed that they are. I'm friends with Scott Belsky, for example, who obviously former CPO at Adobe just recently. Everyone's moved so much quicker. The whole point of tech, Sridhar, was like incumbents are super slow and shit. They're not slow and shit anymore. Yes. What's happened? Have you ever seen incumbents move this fast? **Sridhar Ramaswamy** [35:53]: I think it is three cycles of disruption. All of us remember our history. We all know no one wants to be the person that is going to be known for the IBM deal with Microsoft. People understand how much of a dramatic shift that was and how companies like Deck, remember Deck, disappeared, We took over SGI's buildings. They were the darlings. The first buildings that Google took over in Mountain View was the SGI Plex with that funky purple. And I used to tell everyone that joined my team for like five years after that, you know, SGI built these buildings. And then I would look at them to see if they got it. We learned from that. But I would actually say that mobile was a big platform shift in which the incumbents did pretty well. Marc went after mobile web for Facebook and then said, forget it, I'm doing an app. Same with Google. They took search, moved it over. I led my team for five terrifying years when we took mobile monetization from being 10% of desktop to being a 100%. I would actually say even in the previous round, all of the tech players got pretty smart. Amazon didn't get disrupted because of mobile. Mobile did produce truly new things like Uber and Lyft, but I would say that generation of companies had already smarted up to the world that platform disruptions were going to be a pretty big deal. And this is why you see these companies do like these crazy investments into the future because they see something and they have the money to be able to do it. This is why Facebook became Meta. And you know what, Marc doesn't care that augmented reality fell flat on its face. He was like, bring it, okay, I'm onto AI now. I think that is companies truly learning from the past and innovating hard. **Harry Stebbings** [37:37]: Sridhar, where does this go? I hope you're my friend. Please advise me. I'm seeing, you know, Marc invest $65,000,000,000 in data centers. You're seeing the $500,000,000,000 announcement of Stargate. I know there's equity in debt, and it's not such a straightforward deal, but we've never seen money thrown at anything like this. This is the kind of arms race of AI. Where does it end? **Sridhar Ramaswamy** [38:00]: With a bubble bursting, as all bubbles do. There's like this super funny conversation and insightful conversation that Ben Thompson from Stratiquity had with Nat Friedman, where they talk about, is this a good bubble, like the telecom bubble in the nineties that eventually laid, you know, fiber for the whole world that Google and Facebook and you and I took advantage of? Or is this the dumber web band stuff that just like burnt money in the early two thousands trying to get you groceries and we had to wait fifteen years for Instacart to then show up. Let's face it, you and I don't know. And if the bulk of those investments are going into things like power and buildings, you can say like, okay, it's created surplus for the world. Something good is going to come out of it. On the other hand, it goes into crazily depreciating hardware that is value disappearing in a poof. I think it's early, but back to your point about what do we do, there's still scope for innovation. OpenAI cannot possibly do every workflow that there is. And what you and I need to do is what are the things that are still ripe for disruption? Where is value being created? I think Harvey is a great company. I don't think it's going to get disrupted by OpenAI. And so I think finding niches like that and investing in them is kind of our formula for success. Money doesn't always buy you stuff. **Harry Stebbings** [39:27]: It absolutely doesn't. Speaking of money doesn't always buy you stuff. The street is saying like, oh, the thing with Snowflake is where's growth? To what extent can you buy growth, and how do you think about an m and a strategy going forward to add the extra 10 points of growth to get the street to where they wanna be? **Sridhar Ramaswamy** [39:43]: First of all, 3,500,000,000 going on 30 sounds pretty cool to me. It's not a bad place to start from. But what we have done, and I said this in our last earnings, is we have significantly expanded the aperture of what Snowflake is taking on. We play it at the goal layer. We said you do analytics with Snowflake. And oh, by the way, we do a little bit of machine learning. We have gone from that to we will help you with data ingestion. We want to be a key part of how you set up data engineering. Absolutely analytics and machine learning. End user access with AI, both in terms of tools that we create, but platforms like Snowflake Intelligence, the aperture just got a whole lot wider. And we have a team that is not only driving things like how do we get even more of the analytics market, which is our sweet spot, but going and disrupting others in each of the other very large segments that there are in the data space? Absolutely, we will continue to look at companies and inorganic kind of unrelated acquisition strategy is not something that I'm excited about. I think it'll be a disruption. Snowflake is a product led innovation company. We are not a PE shop. Not that there's anything wrong with being a PE shop, it's just a different skill. That's not us. And so a lot of our growth has to be driven by product innovation. Will we do smart acquisitions here and there? Snowflake spent some $150,000,000 for Neva. I think it's more than paid for itself. Those are the kinds of things to be doing. **Harry Stebbings** [41:15]: What line of revenue is small or insignificant today for Snowflake that in seven to ten years will be a dominant line of revenue that we should consider? **Sridhar Ramaswamy** [41:25]: Starting with AI, 100%. I think it's going to be a big deal. I think it offers the opportunity for disrupting BI as we know it today, more of a direct to consumer. I actually would say the thing that can turbocharge growth for Snowflake is people building on Snowflake. We have the likes of FactSet, of JPMC, of BlackRock, Fiserv, Siemens. They're all building data applications on top of Snowflake. And we let them do some pretty nifty things when it comes to how they can bring together both their own data and data from their customers in order to create these data applications. I would say that is small today, but I fully expect that that'll be a pretty massive overall revenue opportunity for Snowflake. And the really cool thing about this is we go from being an expense item to actually being part of the top line of these companies, much better partnership dynamics as you can imagine. I wanna be able to say we make money when you make money. **Harry Stebbings** [42:26]: If we expand that to kind of the model landscape, I look at it and I go, I don't know where this is in five to seven years. Do we have a world of many models specialized and verticalized, or do we have a world of fewer models, generalized and very large? I'm just intrigued, especially with the Google experience that you have. It's such a unique perspective. I remember reading, well, like, historically, where people thought search would actually be verticalized at a certain point, and they did not anticipate these huge multi behemoths really owning it all? **Sridhar Ramaswamy** [42:56]: I think this is a really good question. And unfortunately, my answer is going to be predict early and predict often. If we were to deconstruct Google search and why it came to dominate, first and foremost, Google did a bunch of deals to basically become the default search engine with a whole pile of players, Yahoo, AOL, and then soon, people like Firefox, and then all the PC manufacturers. It was a very deliberate strategy to be the center of search. Microsoft was asleep at the wheel for a lot of those early years. That's kind of how Google got started. Organic marketing was a part of it, honestly it was a small part of it. It was the gravitational pull that enabled them to then go knock out every other vertical that there was. It will amuse you to know that live.com, which is a predecessor to Bing, had the better image search. They had the best image search, Google did not. But with this thing called universal search, basically Google said, oh, you're looking for images. We will put them right on the main search page. You don't need to go anywhere. That basically was the vector by which Google conquered pretty much every other vertical that there was whether it is shopping or videos or maps. So that is how by that central sticky property, that is how Google conquered the consumer world. Now, if you look in the world of AI, it isn't obvious to me, especially in the enterprise that there is a single entry point. On the consumer side, I know you disagree. I think ChatGPT is getting to be that entry point. And so if I were a betting person on the consumer side, to the extent that there are variations and models and specializations, I think that'll include to the incumbent and the incumbent 100 is ChatGPT and OpenAI. I think entry points for other models are just fragmented. At some point I used to worry about, oh my God, is there going to be one single enterprise entry point that is going to conquer them all? I still worry about it. I think there is still that kind of opportunity, but on the enterprise side, I absolutely see there being all kinds of specializations because so far in whatever the last fifty years, it's not the case that there's been an equivalent of Google search. **Harry Stebbings** [45:20]: I totally agree, and I also love the kind of historical analysis there on Google's distribution strategy with the partnerships. I didn't know that to such extent. **Sridhar Ramaswamy** [45:29]: Oh, all of us think Google, immaculate conception. One fine day, all of us decide we should use Google. Which was the most needle **Harry Stebbings** [45:36]: moving? Which partnership would you say had the largest impact on Google's distribution ability? **Sridhar Ramaswamy** [45:41]: Yahoo and AOL early on. Those were the entry points. AOL didn't know how to do search. Yahoo didn't think search was important. **Harry Stebbings** [45:48]: Does being first really matter? **Sridhar Ramaswamy** [45:51]: 100%. If I remember correctly, we paid AOL more money than we made. This is like a 100 plus percent rev share. Why? Those were the most valuable users then. The Google founders were amazing. They made a bunch of just credibly smart business decisions. Yes, it was a great product, but people underestimate the power of business. **Harry Stebbings** [46:11]: When you go back to those days and you reflect on them, is there anything now where you sit as CEO of an incredible $3,500,000,000 revenue generating public company and you think back and go, I can take that. I can learn my lesson here. What are those? **Sridhar Ramaswamy** [46:26]: Relentlessness. I still remember every discussion with Larry and Sergey used to be exhausting. They never ended. They just argued with every single topic. But you know, good stuff came out of that. You examined every possible thing and you pushed yourself really hard. I also joke to people that by the time I became head of ads, things like working with the legal team was a whole lot easier because I'd been battered on by Larry and Sergey just pushing the envelope with things like Google Books or YouTube, which was a legal nightmare early on. That is my lifelong takeaway, which is pressing hard, being very first principles. Remember the Dutch auction? What other company has done the Dutch auction for IPOs? They did it. Obviously, Google, but still, I think just the amount of energy that they brought into every discussion and the relentlessness of driving to the truth, to the right business outcome is absolutely something that I carry forward to this day. **Harry Stebbings** [47:27]: Listen, I could talk to you all day. I'd love to move into a quick fire. So I say a short statement, you give me your immediate thoughts. Does that sound okay? Sounds good. How do you feel about founder mode? Eulogized in the valley, you're CEO, you've also been founder of Neva. How do you feel about founder mode? **Sridhar Ramaswamy** [47:42]: I think it's just a shortcut for describing effective people. I think anyone can be that. **Harry Stebbings** [47:48]: You have a 23 year old and a 25 year old. You have great relationship with them. My brother's just had his first baby. I'm an uncle for the first time. What advice would you give my brother who's just had his first baby? **Sridhar Ramaswamy** [48:03]: In my humble opinion, parenting is 90% presence, 10% luck, you're done. Sounds like benches. The books that you worry about, the books that you want to buy, the cool software, I'm like bullshit. The best gift that you can give to your child is you yourself just being there. What do you **Harry Stebbings** [48:20]: believe that most around you disbelieve? **Sridhar Ramaswamy** [48:22]: The possibility of change. What do **Unknown** [48:25]: you mean? **Sridhar Ramaswamy** [48:25]: I think people just assume that too many things cannot be changed, including in themselves. I think we straight jacket ourselves in terms of what we can do and what the people around us can do. **Harry Stebbings** [48:36]: I heard a great statement, which is the heaviest things in life are not iron or gold, but unmade decisions. What unmade decision do you think about most? **Sridhar Ramaswamy** [48:46]: I followed my instincts generally. It was crazy for me to come to the valley because I was a successful researcher in Jersey. It was crazy for me to quit my first company, but I was running a team of like 120 people. I went from that to being a software engineer. I don't have many regrets. I have a wonderful family and a spouse that let me make these crazy decisions. We moved house. I was very against it. It was much closer, many more friends. I just do stuff, man, and I fall flat on my face very often. I pick myself on Wacom. **Unknown** [49:19]: You can **Harry Stebbings** [49:19]: be CEO of any other company for a day. Which would you be CEO of? **Sridhar Ramaswamy** [49:24]: I love my job at Snowflake. **Harry Stebbings** [49:26]: Okay. Knocking your question. Knocking this back. Okay. What's the favorite brand and why then? **Sridhar Ramaswamy** [49:33]: I have to admire the aura that Benioff brings with Salesforce. It's not just brand, it's the brand and the marketing. I think he's a remarkable human being. **Harry Stebbings** [49:41]: Do you think brand and marketing is important for Snowflake today? **Sridhar Ramaswamy** [49:45]: Yes. Absolutely. Too many of our own customers who love Snowflake think of us as like, ah, very good warehouse. I like that. And absolutely, I think we have our work cut out. **Harry Stebbings** [49:55]: What's the hardest thing about being CEO of Snowflake? **Sridhar Ramaswamy** [49:58]: At the end of the day, you're dealing with people. You want to be a good human being, but you also want your team to succeed. Making sure that you're driving while still being a good human being, it's a hard thing. It's not something you should ever take lightly. **Harry Stebbings** [50:14]: Final one, you're interviewed by a lot of people, you're asked questions all day, team members, employees, kids, family, you name it. What question does no one ask you that you're like, they should ask me that? **Sridhar Ramaswamy** [50:28]: You know, one interesting question could have been, what are you most proud of? I don't think anyone asked that. **Unknown** [50:33]: What are you most proud of? Probably most proud of being a good dad. Can I ask you, how do you define being a good dad? **Sridhar Ramaswamy** [50:42]: The thing that my wife and I did was very much that thing around presence and love. We were there when they needed us the most. We set good examples for them. Both of us worked. My wife has never missed a day of work in her thirty year career, like, not one day. So to me, it is like setting a good example, being there, and helping them become thoughtful, independent people. **Harry Stebbings** [51:06]: She's never missed a day of work. Does she want a job? I'll hire her. That sounds fantastic, Sridhar. Please, send send That's it **Unknown** [51:13]: my **Harry Stebbings** [51:14]: great. Oh, the other side of that is like, you have a cold? Really? You can **Sridhar Ramaswamy** [51:19]: you can go to school. It's all fine. **Harry Stebbings** [51:21]: Really? You look fine. Not fever, not a fever. Sridhar, listen. I I so appreciate you doing this. I so appreciate our friendship. Thank you so much for being so open, and I love doing this. Thank you, Harry. This was a fun, fun, fun conversation. **Sridhar Ramaswamy** [51:35]: Thank you. **Harry Stebbings** [51:37]: I mean, that was such a fun show to do with Sridhar. He's been a fantastic friend for a long time now. 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