Bringing AI to the Data Cloud, with Snowflake's CEO Frank Slootman

0:07Frank Slootman is the legendary three-time CEO of Data Domain ServiceNow and Snowflake and one of the most looked up to leaders in technology for his relentless. execution. We're excited to talk to him about what's on the horizon for Snowflake and how he looks at the AI opportunity. Frank, good to see you. Thanks for being here. Absolutely. Good to see you, Sarah. Let's start with just a little bit of personal background. You have had an amazing journey. You grew up in Holland. You're the first person in your family to go to college. What were you like as a kid and in college, and how did you end up in product management and computing in the US?

0:39Yeah, that's kind of a big, wide-ranging question. I sometimes have to, you know, go back and figure out what was the method to the madness because, you know, sometimes your life looks like a random walk, you know. In other words, it's just a series of events that kind of, you know, go from one to the other. But, you know, I was always a relatively focused, disciplined kid. If I were to describe myself in almost any realm, whether it was school or sports or any of those things, it's just the nature of the beast, But, you know, I would say, and, you know, definitely, you know, a bit of a chip on my shoulder, which I generally like in people, by the way, you need to have a reason to get up in the morning and have some to prove to the world or whoever.

1:25Those are all useful things. You know, obviously, I ended up in the U.S. because I think the U.S. is obviously much better. Maybe not obvious, but it's obvious to me that it's a much better canvas for people like me. And obviously, we see that all around us, right? people that come from all over the world here because they have far greater opportunity than they would have where they came from. And it certainly is true for me. I mean, there's no doubt that I would have done where I came from, what I've done here. So I'm very grateful, you know, having had that opportunity. I always tell younger people, you know, it's very important where you decide to be.

2:01Don't just go where your friends are. To the point of choosing the right place, be it geography. Yes. And thank you, America. My parents are also immigrants. You talk about being on the right elevator. And some of the companies you worked at, you know, weren't the hottest companies at the time when you joined. Like, tell us about those choices. I just use the analogy of the elevator because there's this aspects of opportunity and circumstance that you can't change. It is what it is. And you're going to be subject to it for better or for worse. And therefore, you need to choose carefully. You know, some people think that, you know, I can will my way to anything.

2:36That's not true, right? So the choices you make, like we just said, where are you going to be, what industry are you going to be, what company are you going to be, what people are you going to be with, are all very formative. And so you have to make very careful choices because if you combine good choices with great execution, you get the perfect cocktail for opportunities, for future opportunities and for having a successful sequence of experiences. So it matters a whole lot. A lot. And I talked to a lot of people joining entrepreneurial ventures, and they're always trying to figure out where to go.

3:15That is often where their friends go. And sometimes it's where investor friends will direct them. What advice would you have for people choosing that company in terms of the things you can't change? You know, it's a great question. I get asked a couple times a year to speak to graduating classes at really prominent business schools and all that sort of thing. And they always ask me, is there one message that you have for the graduating class? I'm like, well, you know, don't go working for some consulting firm, you know, out of school, right? Try to get a real job in the real economy, building real products, selling real products.

3:47He says, you really need to feel what it's like, you know, to sort of be in the drive train of the economy as opposed to I'm just eating out of somebody else's trough. and I kind of sit on the vessel and glide along and I'm feeling good about myself, but you haven't really touched a real economy yet. And I really wish that for people early on in their careers to sort of feel the heat of competition and also the cold winds of threat of markets that are disappearing because that's the real world. And a lot of people choose jobs that are very removed from the real world. I don't think that's helpful for people's development in their careers.

4:22How do you think about company versus industry versus role? Often when I talk to people as well, I kind of advocate for the choose the right industry and then choose the best company in the industry and the role is secondary. Do you think that holds true or how would you suggest that people actually find their way? Yeah, I totally agree with that. I think the role is not that important. You'll have many roles, okay? And roles come and go. And my first job, I took a role I really didn't want. but being an immigrant in this country, beggars couldn't be choosers, and I figured, look, I'll get in there, and I'll make my way from there.

4:59I was in a corporate planning group of six people attached to the CEO of a large computer company. I was about as far removed from the real world as I could be, and I didn't want that, but that's all I could get into. These were the heydays of affirmative action. We didn't have a lot of picks. So in hindsight, I was right because, you know, once I got in there, you know, you spent two years doing typical MBA stuff, you know, M &A and all the presentations for boards and all this kind of stuff. But then after that, they pretty much gave me, you know, whatever I wanted to do was fine with them. And from there, you know, I made my way.

5:38You've had three just amazing CEO jobs, right? So I believe you took Data Domain from less than$3 million in revenue through an IPO and a$2 billion acquisition by UMC. At ServiceNow, you took it from$75 million in revenue through an IPO and I think$1.4 or$1.5 billion of revenue. And then Snowflake, of course, has just been an amazing run. And it's one of the really seminal companies in the data world. How did you go from step one to step two with all these things? And in particular, you know, when you joined Data Domain, I had an academic co-founder. I didn't have a product that was commercially scalable yet.

6:11But ServiceNow, you really turbocharged. Snowflake was growing, but it was spending a lot of cash. So, A, what are the commonalities between those different experiences? And more generally, what kind of drives you? What do you have to prove? You already had accomplished so much by the time you got to Snowflake. How do you keep going? So, let me first sort of correct the record on day and night. They had no revenue, no customers, nothing. There were 15 people there. And when we first started to, you know, a certain product, it was, it had one terabyte of usable space. Just imagine that. Okay, now it was a while ago.

6:46You know, and it ran 30 megabytes, you know, a second. So it was useless for 99.9 % of applications. So we're like, what are we going to do now? Why'd you take the job? Well, I didn't know that. You know, I'll tell you why I took the job. First of all, you know, I got rejected numerous times for CEO opportunities. And the ones that they were interested in were like second and third string. And I know people really cautioned me at that time, don't hold up, you know, do not go for a second, third string, you know, deal. You need to have really good investors. You know, we were a startup, one out of hundreds at the time.

7:26You know, I'd be walking the halls of NEA and Greylock and people looked at me, who are you? What company is that? Oh, okay. We were a no-name, and we were lectured on other companies that, in hindsight, ended up being no-name. So, I mean, it's almost legendary how Jada Domain just manifested itself. And by the way, I live for that kind of drama. You know, it was great. But we didn't have product-market fit. We just didn't. And, you know, I found a little bit of fit. I remember, you know, meeting with a CIO company that has been acquired since by EMC. and they were testing the products. And the guy said to me, he said, you know, he said, that little product of yours was a real hero here on Friday, and I'm like, tell me more.

8:14Do tell. But he explained that, you know, they had their email database, you know, backed up on our device, and they had a massive corruption email database, as that's happened back then, that's not common anymore. And it was 4 o 'clock on the Friday afternoon, and they're like, oh, my God, we're going to be recovering from tape here all weekend long. We'll be sleeping on cots, blah, blah, blah. And then they remembered, oh, we have a backup on this. And by 7 o 'clock that evening, they were going home. And obviously, you don't need to be a rocket scientist to figure out that there's a use case you can sell a few times more, right?

8:50So we stayed alive, and we did do that$3 million that first year. But I still remember doing the very first contract with like a$5 ,000 service deal with Stanford University. and they bitch and complain the whole way. I'm like, well, this is going to be a great business. You know, one of my favorite books, which I think is really a hidden gem in terms of go-to-market and sales and startups is Tape Sucks. And I think you get into very great tactical advice that's lacking from a lot of other books. Like you get into different channel strategies and whether you should do them and partnerships and other things that I just don't think are addressed very well in a lot of business books.

9:24And you've now written three books and we can come back to the question in terms of what continues to drive you and all the rest. What drives you to actually share knowledge that way and write a book, it looks like, with almost every formative experience that you've had? You know, I get an awful lot of inbound questions. You know, can we have coffee? Can you speak here? Can you do this? Can you do that? And I'm like, I really can't because it'll become a full-time job. So I'm like, look, I'll write a – and by the way, the main book, the tape sucks. It was self-published. It was homebrew. and it's a very dense book even though it doesn't have that many pages um you know i don't spend a lot of time you know waxing poetic or having a lot of platitudes that's sort of the difference between my writing and everybody else's there's no filler everything it's super dense everything that i write is i find uh meaningful and and and worthwhile uh sharing but it's really look these books all have had different reasons okay the the last book that i wrote i didn't want to write okay Denise Pearson our CMO really you know pushed me to write it and she also made it easy for me to write it because I had a lot of help along the way I wrote every word of it okay no in other words it's not a but I did have a growth writer who just went through it just said look you need examples here or nobody will understand this outside your business you know all that kind of commentary and and explain this better and so he helped me just make the book more consumable rather than this very narrow audience that we normally deal with But the net of the reason why I wrote Amped Up was, you know, people said, hey, just like you just said, you've had three very successful experiences, different times, different markets, different technologies, different competitors, blah, blah, blah.

11:03You know, what's the secret sauce? And Americans always think there's a formula that can be extracted. And if I just have my hands on that, I can just do it too, right? It's an immediate gratification type of thing. And the book is really the answer to the question of what do you guys do? What do you think explains the success in these companies? It's my answer. It's not that I'm trying to sell that to people at all. I don't care whether you agree with me or not. I'm just telling you what my best guess, my best take is on the answer to that question, right? People sometimes go like, well, I don't agree with this.

11:36I don't care. I mean, yeah, I did kill customer success at every company I've been in. I think it's the biggest bullshit thing that goes on in Silicon Valley. It doesn't mean that I need you to agree with me. I'm just telling you what it is, right? So one of the core messages in Amp It Up is about the importance of urgency. And you talk a lot about how to create it. I guess maybe a more difficult question is, why do you think a bunch of CEOs and leaders don't push for more urgency or higher standards? Well, I know you guys have been to a California DMV before. You want to see a lack of urgency?

12:09You know, this is what naturally happens to human beings. It's just it's innate. we slow down to a glacial pace unless there are people who are going to drive tempo and pace and intensity and urgency that's what leaders need to do because people naturally slow down they're like well i need to be here anyways and you know and they're sort of their mind is wandering off on their next vacation or what they're going to do on the weekend and it's like you know you you need to set you know high focus high intensity uh high preoccupation you know with with what we're dawn. I mean, people sometimes ask me, what's the message of your book?

12:44I'm like, read the title. Okay. That is the message. Look, there is an X factor. There's an enormous amount of room in the margin that is right under your nose. Okay. And you have the opportunity to take it up in the next meeting, in the next podcast, in the next email, in the next Slack message, you can take it up. You know, you can push the urgency. You can push the standards, right? You can push the alignment, right? You have all these opportunities. Are you taking them? It's an easy message, but it's really hard to have the mental energy to bring that to every single instance of the day, right?

13:23And that's the message of the book. There's a lot of room there. There's a ton of room there, and people don't realize it because, you know, I've seen companies where, you know, you have young CEOs, they just think, I hire a bunch of people, and then I sit back and wait for greatness. they have no idea that they have to relentlessly drive you know every second of the day every interaction and seek the confrontation because you know ceo jobs are insanely confrontational which is not human nature we don't like it we are naturally confrontational we avoid it i mean i had a founder ceo once you know every time somebody had to get fired you know he he had a cfo do it And he stayed home that day because it's just so hard.

14:08Right. And it's like, I don't have the disposition for it. We understand that. But there are people in the enterprise that have to do that stuff. OK, that fully resonates. But another piece that strikes me is people are afraid, right, that they don't have the right people that they'll lose in the talent marketplace. If they push hard enough, their people will leave. Right. What would you how would you respond to that? Well, if they leave, they should leave. OK, I mean, this is a great thing. You know, culture shorts and sifts. You attract the right ones and you start losing the wrong ones. So it's actually quite perfect.

14:39If people are leaving, they're just not your DNA. They're not your blood type. And by the way, you need to create your blood type, you know, around you. Otherwise, you're correct. You have nothing but conflict. I mean, I remember having people after two weeks just said, you know what, I can't take the pace and intensity of this place anymore. It wasn't me personally. It was like everybody was like that. You know, they were all, you know, calling people out and driving these expectations. they weren't used to and they wanted to go home at 4 p.m. and pick up the kids from school. I'm like, well, you need to go back to HP and sleep in your cubicle.

15:12This is not the place for you. So you need to, by the way, culture can be incredibly helpful, you know, to a company. But culture is not a general thing. There's no such thing as general goodness. I mean, a culture needs to really enable your mission, right? And whatever enables your mission effectively is a good culture. There's no universal culture that's good. And, you know, it depends on, you know, the type of leadership you have and type of business you have and, you know, where you are in your journey and all this kind of stuff. But, you know, culture is a very powerful thing because if you don't fill the void, somebody else is going to.

15:46I want to switch over to talking about Snowflake and then what's going on in AI. Can you just give our listeners a sort of Snowflake 101? You know, what is the sort of scale and core innovation and use case of Snowflake today? And we can talk about how the company has been evolving from warehousing to cloud, the data cloud and application platform and AI after that. Yeah, our founders probably would argue immediately with you that they were never a warehousing play. So they sort of want to forgive me. Yeah, you're forgiven. But there's a reason for it because, you know, they were dealing with semi-structured data right from the get-go.

16:27And sort of the workload types were more than just sort of batch analytical, you know, type of stuff, which is mostly associated with data warehouse. And that's also purely structured data. So there was always a broader scope and focus. But our founders were two French guys, longtime, you know, Oracle CTOs, technologists, architects. They were really responsible for making Oracle from the departmental level. You probably can't remember that far back, but Oracle at one point in time was a departmental platform to the enterprise platform that it became. So things like Parallel SQL were all things that came from them.

17:04So they left and they wanted to reimagine database management, for lack of a better word, for cloud computing. In other words, they didn't want to carry technology forward or as little as they could. They want to reimagine. So, you know, building a data base or a data platform, whatever you want to call it, for cloud computing was very different than just sort of taking a Postgres SQL kernel forward and kind of hacking it up for the cloud. I'm being very unflattering here, but there's plenty of people that have done that. So they did some really breakthrough things, you know, most notably that most people know is the separation of storage and compute.

17:48I mean, back in the day, people may not remember this, but, you know, I mean, you bought storage and compute in combination. You couldn't buy one without the other. Whereas in the world of cloud, you can commandeer compute and storage independent of each other. And, of course, it became a consumption model. Not right away, by the way. That was sort of an evolution. And, you know, obviously today is by the machine second or compute second. But once upon a time, it was, you know, by the node and it was by the machine hour and all that. Now it's so incredibly fine-grained and granular that that is completely different.

18:21But the other thing that they did is they took the control plane out of the cluster itself. So the clusters are now all stateless. You know, in other words, they're clueless, which is great because you can run tons of them, you know, concurrently. Right. So there's not there's not one master. The master lives outside of the clusters. So running jobs concurrently is another huge thing, because in the world of data warehousing, just to use that word again, Sarah. I mean, the reality was, you know, you had to beg for a 2.30 a.m. time slot three months from now because, you know, the cluster was consumed very quickly, very easily.

18:52Now it's like there's no limit. So this is what I often tell investors. It's like I'm not creating demand. I'm just enabling it. Okay. It's so pent up. It's insane. Right. And the architecture does that. Right. And then I could also provision workloads either for economy, in other words, to run the cheapest possible, or I could run for performance blistering fast. and you could make these optimizations and choices. So this is beautiful stuff, right? Because we just opened up the demand in that legacy marketplace. And then, of course, we started migrating Teradata databases, I mean, massive Teradata plants.

19:29And by the way, I mean, we're still in the early innings of that because it's not easy to move those platforms at all. But, you know, a ton of Hadoop, of course, which is sort of what we used to call big data, and now old data is big. so that the scriptor doesn't make too much sense anymore. You know, an old Cloudera and on and on and on, tons of Oracle, SQL Server. I mean, so that's what we've been doing. But, you know, when I started, you know, the tagline, if you will, the positioning or core message was this is the data warehouse built for the cloud. That was Snowflake's message. And I'm like, okay, we're not going to stick with that because, you know, you taint yourself with a brush pretty soon.

20:11You can't get it off you, which is pretty much what happened to us. I mean, you just started on it, right? So here we go again. I have an allergic reaction every time I hear data warehousing because to me it's just a type of workload now. It's no longer a market. It's no longer an industry where, you know, cloud data management platforms, you know, are, and certainly we are, you know, we're seeking to become full-spectrum workload capable, meaning from the most batch analytical to the most streaming, online, transactional, massive scale, and extremely low latency from what you're used to in all TPE type of environments.

20:48And the reason is, we don't want the whole premise behind the data cloud is that the work comes to the data. The data does not go to the work. Now, why does that matter? Because historically, the data has always been pumped around to go to the work. Well, you get massive siloing of the data. You don't even have to work at it. You're going to get siloing, you know, whether you try or not, because you have a new app, you get a new silo, you know, because it comes with its own database, right? And the siloing prevents you from really fully exploiting the potential that lies within your data, because there's no walls that exist between them.

21:23So the notion of a data cloud is kind of a really new data strategy element in the mix. And we advocate really hard. I mean, I said it to CEOs of large banks. I said, don't go re-siloing your world in the cloud. You end up with the same set of problems you have right now. And your data science, ML, AI, et cetera, teams are going to be very frustrated trying to overlay and blend that data and fine-tune and train and do all these fancy things we do now with data. So, you know, we're trying to create an unfettered data universe, data orbit, that's much bigger than your enterprise, by the way, because this is really an ecosystem, right?

22:05You have data providers, you know, in the world of, you know, financial services, you know, Faxxed and Bloomberg and S &P and all these things. So, in Hedge Fund, they have hundreds and hundreds, you know, data flows, you know, coming in. So you really need to think of data management as a much broader orbit than just your enterprise. And so in the world of artificial intelligence or general intelligence around data, the ability to mobilize data, you really need to have a data cloud strategy. That's also why we are multi-cloud capable, because we don't think you can have a data cloud in a single public cloud platform.

22:44By definition, you can't, right? So that's really the strategy. And obviously things have taken off a lot, but there have been multiple iterations in the journey of Snowflake. I mean, it started off just moving legacy systems to the cloud and taking advantage of the elasticity and the economics and the provisioning and all these things. But now it's much more broadly workload capable, and that's a journey that goes on and on. The other thing that has changed is no longer a database world. You know, historically, a database was just, you know, a platform that was self-contained and it had standard interfaces like ODBC and JDBC that the application used to access the data.

23:23Now it's like, well, wait a second, you know, we don't want to operate that way anymore because you're breaching the governance perimeter. So the application needs to execute inside the perimeter of the platform, not outside. So we have a programmability platform called Snowpark. Okay. And that's where, you know, all the applications live. We have a native application framework, all these kinds of things. So now you're looking at a very different platform environment, very different layers stacked than historically what we've had in the on-premise stack that we've grown up with, or certainly I grew up with.

23:59So that's kind of as short a story as I can tell you. That's really great background. And obviously, Sniplic has accomplished amazing things and really become central now to the enterprise data world and ecosystem. How do you think about what's shifting in AI? because I think we went from a world where we had almost like this older version of AI models, CNNs and RNNs and things like that, where people were doing old school natural language processing or other things. And then more recently, we've had this big breakthrough wave of generative AI. And it felt like the starting gun for that to some extent was really when ChatGPT came out about six months ago.

24:32And then GPT-4 came out maybe three months ago. And then suddenly everybody started building applications against this. How has that been showing up or has that been showing up yet in terms of the AI use cases that you see in the enterprise or your customer requests? Has anything really shifted yet in terms of the broader enterprise ecosystem that you deal with? Just given that often it takes six months for an enterprise to plan something if it's a very large business. And so I feel like the last few months or last two quarters have just been a lot of big companies kind of planning against what to do.

25:01Yeah, first of all, large language models are about language. Okay, no surprise. but and it's a huge deal because you know i was taught to you know the basics of cobalt when i was in school and you know cobalt stood for common business oriented language well there was nothing common or business oriented about it it was extremely cryptic syntax and all that but compared to assembler and machine code it was amazingly uh you know the syntax was amazingly comprehensible so it's all relative you know in the 80s we had sql which was back then you know also positioned as something that mere mortals could use to query data.