No PriorsNo Priors Ep. 23 | With Snowflake's CEO Frank Slootman
EVERY SPOKEN WORD
110 min read · 21,958 words- 0:00 – 12:42
Frank’s Insights on Career Success as a three-time CEO
- SGSarah Guo
Our guest today needs no introduction. Frank 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.
- FSFrank Slootman
Absolutely. Good to see you, Sarah.
- SGSarah Guo
Let's start with just a little bit of personal background. You, uh, 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, uh, in college, and, uh, how did you end up, um, in, in product management and computing in the US?
- FSFrank Slootman
Yeah, that's kind of a c- you know, big wide-ranging, uh, question. I sometimes have to, you know, go back and, uh, figure out wha- 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, uh, you know, I, I was always a relatively focused, disciplined kid, if, if, if, if I were to describe myself, in almost any, uh, realm, whether it was school or sports or any of those things. It's just the nature of the beast, um, you know, I would say. And, you know, definitely, uh, you know, a bit of a chip on my shoulder, uh, which I generally like in people, by the way. (laughs) You need to have a reason to get up in the morning, and, and, and have something to prove to the world or whoever. Those are all useful things. You know, obviously, I ended up in the US because I think the US is a- is, is obviously a much better... maybe not obvious, but it's obvious to me that it's a much better canvas to, uh, for, for, for people like me. And obviously, we see it all around us, right? People that come from all over the world here because they have, you know, far greater opportunity than they would have where they came from. And, um, you know, it certainly is true for me. I mean, there's no doubt that I would've done in where I came from, uh, what I've done here. So, uh, I'm very grateful, you know, uh, having had that opportunity. I always tell younger people, you know, it's, it's very important where you decide to be. Don't just go where your friends are. (laughs)
- SGSarah Guo
To the point of, of choosing the right place, be it geography, yes, and thank you America, my parents were 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.
- FSFrank Slootman
I, I just use the analogy of the elevator because there's just aspects, um, of opportunity and, and circumstance that you can't change. It is what it is, and you're gonna be subject to it, uh, for better or for worse. And, uh, therefore, you need to choose carefully. You know, some people think that, you know, "I can will my way to anything." That's not true, right? So, uh, your choices you make, uh, like we just said, where are you gonna be, what industry you're gonna be, what company you're gonna be, what people you're gonna be with, um, are all very formative. And, uh, so you, you, you have to make c- uh, you know, very, uh, careful choices, because if you combine good choices, you know, with, with great execution, you know, you, you get the perfect cocktail for, for opportunities, for future opportunities, and, and for having a successful sequence of, of experiences. So it, it matters a whole lot.
- SGSarah Guo
A lot, and I talk to a lot of people joining entrepreneurial ventures, and they're always trying to figure out where to go. Um, that is often where their friends go, and sometimes it's where investor friends will direct them. What advice, uh, would you have for people choosing that company in terms of the things you can't change?
- FSFrank Slootman
You know, th- i- it's, it's a great question. I, I, I, I get asked couple times a year to speak to graduating classes at really prominent business schools and all that sort of thing, and they, they always ask me, "Is there, is there, is there one message that you have for the graduating class?" I'm like, "Well, you know, don't, 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." Because 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 sorta... I, I kinda sit on the vessel and, and, and glide along, and I'm feeling good about myself. But you haven't really touched a real economy yet, and I, I really, uh, wish that for, for people early on in their careers, to sort of feel the heat of competition and, and, and also the, the cold winds of threat, uh, of markets that are, you know, disappearing, because that's the real world. And, and a lot of people choose jobs that are very removed from the real world, and I don't think that's helpful for, for people's development and their careers.
- EGElad Gil
How do you think about company versus industry versus role? You know, uh, y- often when I talk to people as well, I, I kinda 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?
- FSFrank Slootman
Yeah, I, I, I, I totally agree with that. Uh, I think the role is, is, is not that important. You'll have many roles, okay? Um, and, and roles come and go, and, uh, in my first job, I took a role I really didn't want. (laughs) But, you know, being an immigrant in this country, I, beggars couldn't be choosers and I had to... I, I figured, look, I'll get in there and I'll make my way from there. Um, you know, I, I was, uh, I was in a corporate planning group with like 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, I didn't want that, but that, that's all I could, you know, get into. These were the, uh, the, the heydays of affirmative action. We didn't have a lot of picks. So, um... and, and in hindsight I, I was right because, you know, once I got in there, you know, I... you spent two years doing typical MBA stuff, you know, M&A and all this, all the presentations for boards and all this kind of stuff, but then after that, they, they pretty much gave me, uh, uh, you know, uh, whatever I wanted to do was fine with them, and from there, you know, um, I made my way.
- EGElad Gil
Y- you've had three just amazing CEO jobs, right? So, I believe you took Data Domain from, um, less than three million in revenue through an IPO and a $2 billion acquisition by DMC. At ServiceNow you took it from 75 million of revenue through an IPO and, uh, I think one and e- 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, how'd you go from step one to step two with all these things? And in particular, you know, when you joined Data Domain and had a academic co-founder, it didn't have a product that was commercially scalable yet. ServiceNow you really turbocharged. Snowflake was growing but, you know, it was spending a lot of cash. So, um, A, wh- what are the commonalities between those different experiences? And more generally, what kind of drives you? Like, why, what do you have to prove? You already had accomplished so much by the time you got to Snowflake, how do you keep going?
- FSFrank Slootman
Yeah. So, let, let me first sort of correct the record on Data Domain. That was... They had no revenue, no customers, nothing. There were 15 people there and, uh, when we first started to, you know, assert the product, it was... It had one terabyte of usable space. Just imagine that, okay? No, it was a while ago.
- SGSarah Guo
(laughs)
- FSFrank Slootman
Uh, you know, and it ran 30 megabytes, you know, a second. So, it was useless for, for 99.9% of, of, of applications. Um, so like, what are we gonna do now? And, that-
- EGElad Gil
Why'd you take the job?
- FSFrank Slootman
Well, I didn't know that. Um, you know, I, I... Uh, I'll tell you why I took the job. First of all, you know, I, I, I got rejected numerous times for, for CEO opportunities and the ones that, that they were interested in were like second and third string and, uh, I know, uh, people really cautioned me at that time to hold out, 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, a startup, one out of hundreds at the time. You know, I'd be walking the halls of, of NEA and Greylock and people looked at me, "Who are you?"
- SGSarah Guo
(laughs)
- FSFrank Slootman
"What company is that? Oh, oh, okay." We were a no name and we were lectured on, you know, on other companies that in, in hindsight ended up being no names so, I mean, it's, it's almost, it's almost legendary how Data Domain just manifested itself. And, and by the way, I, I live for that kind of drama (laughs) .
- SGSarah Guo
(laughs)
- FSFrank Slootman
You know? It was great. Um, but we, we didn't have product market fit, we just didn't. And, um, you know, I, I found a little bit of fit. I remember, you know, meeting with a CIO company that, that, that, that has been acquired since by, by EMC. Uh, and I was, they were testing the products and, um, 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, I'm like, "Tell me more. Do tell." (laughs) Um, but he, he, he explained that, you know, they had their email database, you know, backed up on, um, on our device and, uh, they had a massive corruption in email databases as, as happened back then but that's not common anymore. And it was four o'clock on a Friday afternoon and they're like, "Oh my God, we're gonna be recovering from tape here all weekend long. We'll be sleeping on cots," blah, blah, blah. And, uh, then they remembered, "Oh, we have a, we have a backup on disc." (laughs) And by seven o'clock that evening they were going home and, and obviously you don't need to be a rocket scientist to figure out that is a use case you can sell a few times more, right? So, we stayed alive and we did do that $3 million that first year. Um, but I still remember doing the very first contract with like a $5,000, uh, service deal with Stanford University and they bitched and complained the whole way. I'm like-
- SGSarah Guo
(laughs)
- FSFrank Slootman
... "Well, this is gonna be great business." (laughs)
- SGSarah Guo
(laughs)
- EGElad Gil
Yeah. You know, one of my, 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, um, tactical advice it's lacking from a lot, lot, 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. And you've now written three books, and we can come back to the question in terms of, you know, 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?
- FSFrank Slootman
You know, um, I, I get a, 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's just, uh, it'll become a full-time job." Um, so I'm like, "Look, I'll, I'll write a..." And by the way, the Data Domain book, uh, Tape Sucks, you know, I 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, 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, and everybody else's. There's no filler. Everything... It's super dense. Everything that I write is, uh, I find, uh, meaningful and, and, and worthwhile, uh, sharing. But it's really... Look, ev- th- these books all have had different reasons, okay? The, the, the last book that I wrote, I didn't want to write it, okay? Uh, Denise Pearson, our, 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, uh, along the way. I wrote every word of it, okay? No one... In other words, it's not a... But I did have a ghost writer who just went through and just said, "Look, you need examples here" or "Nobody will understand this outside of your business." You know, all, all that kind of commentary and, and explained this better and so he, he helped me just make the book more consumable rather than this very narrow audience that we normally deal with. But the, the net of the, the reason why I wrote Amp It Up! was, you know, people said, "Hey," just like you just said, "You've had three very successful experiences, different times, different markets, different technology, different competitor," blah, blah, blah. You know, "What's the secret sauce?" And Amer- Americans always think there's a formula that can be extracted and, uh, if I just have my hands on that, I can just do it too, right? It's, it's that immediate gratification, uh, type of thing and the book's 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, it's not that, you know, 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? Um, people sometimes go like, "Well, I don't agree with this." I don't care. I mean, we have... We... 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. That doesn't mean that I need you to agree with me, I'm just telling you what it is, right?
- SGSarah Guo
So, one of the core messages in Amp It Up! is about, um, the importance of urgency. Um, 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?
- FSFrank Slootman
Well, fe- uh, I know you guys have been to a California DMV before. You wanna see a lack of urgency? You know, um, th- this is what naturally happens to human beings. It's, it's just... It's innate. We slow down to a glacial pace unless there are people who are gonna 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, 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 doing. I mean,
- 12:42 – 25:01
The Message of his Book Amp It Up
- FSFrank Slootman
the, the people sometimes ask me, "What's the message of, of your book?" I'm like, "Read the title, okay?"
- SGSarah Guo
(laughs)
- NANarrator
(laughs)
- FSFrank Slootman
Uh, (laughs) because that is the message. Look, there is a, 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, uh, to bring that to every single instance of the day, right? And that, that's the, 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, I've, I've seen companies where, you know, you have c- c- young CEOs. They just think, "I hire a bunch of people, and then I sit back and wait for greatness." (laughs) They just, 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-
- SGSarah Guo
Mm-hmm.
- FSFrank Slootman
... CEO jobs are in- ins- insanely confrontational, which is not human nature. We don't like it.
- SGSarah Guo
Mm-hmm.
- FSFrank Slootman
We aren't 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, he had, had his CFO do it, and he stayed home that day (laughs) because it's just so hard, right? 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, okay?
- SGSarah Guo
That fully resonates. But another piece that strikes me is, uh, people are afraid, right, that they don't have the right people, that, um, they'll lose in the, they'll lose in the talent marketplace. If they push hard enough, their people will leave, right? What would you, what would... How would you respond to that?
- FSFrank Slootman
Well, if they leave, they should leave, okay? I mean, uh, this is the great thing, you know, culture sorts and sifts. You attract the right ones, and you start losing the wrong ones. So it's actually quite perfect. If people are leaving, they're just not your DNA. You know, they're not your, your blood type. And, uh, 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, I remember having people that 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-
- SGSarah Guo
Mm-hmm.
- FSFrank Slootman
... everybody was like that, you know? They were all, you know, calling people out and, and driving these expectations they weren't used to, and they wanted to go home at 4:00, 4:00 PM and pick up the kids from school. And I'm like, "Well, you need to go back to HP and sleep in your cubicle." (laughs) You know? "This is not the place for you." Um, so you n- you need to... Uh, but like culture can be incredibly helpful, you know, to a company. Uh, but culture is not a, a general thing. There's no such thing as general goodness. I mean, a culture needs to really enable your mission, right? And whatever, whatever enables your mission effectively is, is a good culture. Is... There's no universal culture that's good. You know, that 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, is a very powerful thing because if you don't, if you don't fill the void, somebody else is going to, you know?
- SGSarah Guo
I want to switch over to talking, um, about Snowflake and, and then what's going on in AI. Um, can you just m- 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? Um, and we, we can talk about, uh, how the, how the, um, company has been evolving from warehousing to cloud, uh, the data cloud and application platform and AI after that.
- FSFrank Slootman
Yeah. Our, our, our founders, uh, probably would argue immediately with you that they were never a warehousing play. So, they sort of want to-
- SGSarah Guo
Forgive me.
- FSFrank Slootman
Yeah. You're forgiven. Um, but... And there's a reason for it because, you know, they were dealing with semi-structured data right from the get-go and sort of the workload types were, were more than just sort of batch, uh, analytical, you know, type of stuff, which is mostly associated with, with data warehouse, and that's also purely structured data. Um, so there was, there was always a broader, uh, scope and focus. But our founders were two French guys, long time, you know, Oracle, uh, CTOs, technologists, uh, architects. They were really responsible for taking 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, you know, were all things that came, you know, from them. So they, they left, and, you know, they wanted to reimagine database management, you know, for lack of a better word, for cloud computing. In, in other words, they didn't want to carry technology forward, uh, or as little as they could. They wanted to reimagine. So, you know, building a data, uh, base or a data platform, whatever you want to call it, for cloud computing was very different than just sort of taking a PostgreSQL kernel forward and kind of hacking it up (laughs) for the cloud. I'm, I'm being very unflattering here, but there's plenty of people that have, have done that. Um, so they did, did some really, uh, breakthrough things, you know, most notably that most people know as the separation of storage and compute. I mean, back in the day, people maybe not remember this, but, you know... I mean, you, you, you bought storage and computing combination. You couldn't buy (laughs) one without the other. Whereas in the world of cloud, you can commandeer compute and, and, 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, an, an evolution. And, you know, obviously today is about a machine second or compute second. Um, but once upon a time, it was, you know, by the node and it was by the, by the machine hour and all that. Now it's so incredibly fine-grained and granular-... um, that, that is completely different. But 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 (laughs) , which is great because you can run tons of 'em, 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, the, the reality was, you know, you have to beg for 2:30 AM time slot three months from now because, you know, cons- the cluster was consumed very quickly, very easily. Now it's like, there's no limit. So this is, uh, this is what I often tell an investor, it's like, "I'm not creating demand. I'm just enabling it," (laughs) , okay? It's so pent up, it's r- it's insane, all right? And the architecture does that, right? And then I could also provision workloads either for economy, in other words, they run the cheapest possible, or I could run 'em for performance, blistering fast. And you could make these optimizations and choices. So this is, this is beautiful stuff, right, because we, we just, we just opened up, uh, the demand, uh, in that, you know, legacy marketplace. And then, of course, we started migrating, uh, you know, Teradata, uh, databases. I mean, massive Teradata plants. And by the way, I mean, that's, we're still in the early innings of that because it's not easy to, to move those, uh, platforms at all. Um, but, you know, a ton of Hadoop, of course, which is sort of the, you know, what we used to call big data. Now all data is big, so that, that descriptor doesn't make, you know, too much sense anymore. Um, you know, and all the Cloudera and on, and on, and on, tons of Oracle, SQL Server. I mean, so that's, that's what we've been doing. But, you know, when I started, you know, the, the, the, the tagline, if you will, the positioning or core message was, this is the da- this is the data warehouse built for the cloud. That was Snowflake's message. And I'm like, "Okay, well, I'm gonna stick with that." (laughs) 'Cause, you know, you, you, you, you taint yourself with that brush, pretty soon you can't get it off you, which is pretty much what happened to us. I mean, it's, you just started on it, like, 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... And, and, you know, cloud data management platforms, you know, are, and certainly we are, you know, we're, we're seeking to become full-spectrum workload capable, meaning from the most batch analytical to the most streaming, online, transactional, you know, massive, you know, uh, scale, and, and, and, and extremely low latency from, from what you're used to in, in OLTP type of, uh, environments. And the reason is, we don't want... The, 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, you know? Because historically, the data has always been pumped around to go to the work. Well, you get massive siloing of the data. You, you don't even need to ha- e- even have to work at it. You're gonna get siloing, you know, whether you try or not because you have a new app, you got 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, that lies within your data because there's now walls that, that exist between them. Um, so the notion of a data cloud is, is kind of a really new data strategy element in the mix, and, and, and we advocate really hard. I mean, that's... I've said it to CEOs of large banks. I says, "Don't go re-siloing your world in the cloud. You end up with the same set of problems, you know, you have right now in your data science, ML, AI, et cetera. Teams are gonna be, you know, very frustrated, uh, you know, trying to overlay and blend that data, and fine-tune, and train, and do all these fancy things we do now, um, you know, with data." So, you know, we're trying to create an unfettered, uh, data universe, data orbit, that's much bigger than your enterprise, by the way, because this is really an ecosystem, right? It, it... You, you have data providers, you know, in, in the world of, you know, financial services. You have FactSet, and Bloomberg, and, and, and S&P, and all these things. Um, so... And, and, and 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, as, as a much broader orbit, uh, than, than just your, your, uh, your enterprise. And so, in the world of, of, um, artificial intelligence or general intelligence, uh, 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 know, we can have a data cloud in a single public, on a single public cloud platform. Uh, by definition, you can't, right? So that's really the strategy, and, uh, um, obviously things, uh, have taken off a lot, but there have been multiple iterations in the, in the journey, you know, of Snowflake. I mean, started out, off, started off just moving, uh, legacy, uh, you know, systems to the cloud and taking advantage of the elasticity, and the economics, and the, the provisioning, all these things. Uh, 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, it's 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 you, that the application used to access the data. Now it's like, "Well, wait a second." You know, we (laughs) , we don't wanna operate that way anymore because you're breaching the, the governance perimeter. So the application needs to execute inside the perimeter of the platform, not outside. Um, so we have a programmability platform called Snowpark, okay? And, and that's where, you know, all the applications live. We have a native application framework, all these kinds of things. So now you, you're looking at a very different platform environment, very different layer stack than historically what we've had, um, in the on-premise, uh, stack that we've grown up with, or certainly I grew up with. That's kind of as short as- a story as I can tell you. (laughs)
- EGElad Gil
That's, that's really great background, and, um, obviously Snowflake has accomplished amazing things and really become central now to the, 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, um, 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, and 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, or has anything really shifted yet in terms of, you know, the broader enterprise ecosystem that, 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 have just... Or last two quarters have just been a lot of big companies kind of planning against what to do.
- 25:01 – 36:29
Future of Natural Language and Data
- FSFrank Slootman
Yeah. You know, first of all, large language models are about language, okay? (laughs) No surprise. Um, but... And, and it's a huge deal, um, because, you know, I was taught, uh, you know, the basics of COBOL when I was in school, and, you know, COBOL stood for Common Business-Oriented Language. Well, there was nothing common or business-oriented about it.
- EGElad Gil
(laughs)
- FSFrank Slootman
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. So this is all about what, wha- what, h- how and what is your relationship with data, right? And over the years that has, you know, evolved, but it's been immensely frustrating, you know, for people to get, you know, access to data in the form that they want. And there's a lot of ad hoc, and there's a lot of standardized reporting, and dashboarding, all this kind of stuff, but it's been difficult. So, you know, going to natural language is like, it's like the last mile here. Um, and that is, is an enormous thing. I mean, the effect on demand will be just enormous because every mortal, uh, if, if you're semi-literate, maybe not even literate, you can just talk, you know? (laughs) You can, you can get value from data. Wow. You know, so it is an incredibly, uh, you know, big deal. But, you know, the generative aspect in terms of content generation, that's very cool when you're trying to plan a trip to Yellowstone, but when you're in enterprise, you're dealing with structured proprietary data, and, you know, they're not planning trips to Yellowstone. (laughs) They're gonna, you know, they're gonna ask really hard questions. Like in insurance, for example, they may say, um, you know, "We had disproportionate, you know, bodily injury claims in Florida, and the surrounding states didn't have it. You know, A, what explains that? B, are we gonna have it again next quarter? And C, what do we do about it? Do we stop underwriting, do we change our pricing? Blah, blah, blah, blah." Um, believe me, th- you're not gonna get the answer to that question (laughs) out of a large language model. So, um, you, you got to sort of separate the issues of, you know, text to SQL and all, all that, you know, which I think are incredibly valuable from going to structured proprietary data, because that's a, that's a very different realm. So, you know, I, the way I'm trying to think about it right now is, yeah, we have language models, but we're gonna see all kinds of other models. We're going to see business models, okay? Because the question I just asked, you need to understand business models. I mean, one of the big things that... Just to stick with insurance for a second. One of the biggest things in insurance, in a specific type of insurance, like auto insurance, you... Auto insurance is GEICO and Progressive and Liberty Mutual and all these people. You know, telemetry data is, is number one through 10 for them, okay? Telemetry data is the device you get in your car, and it, it knows when you're speeding and-
- EGElad Gil
Mm.
- FSFrank Slootman
... uh, all this kind of stuff, um... And by the way, that, that's how they now price risk, and they're able, they're capable of lowering their prices, yet increasing their profits because of their extremely sophisticated and refined use of that data. That data is extremely predictive, you know, in terms of, you know, what, what the claims are going to be. Uh, and it's the difference between winners and losers and people who make money and people who don't make money. So that's, that level of, of... And by the way, that's not even AI. That's, that's just, you know, machine learning, uh, really data driven, uh, and, and that's already in, in broad use in, in, in other insurance companies. That's, that is sort of, you know, where this is all going, and I need to be able to ask questions that analysts might take weeks and months, you know, to... Or bring in McKinsey or Bain or whoever, you know, to kind of study, you know, problems, right?The systems will be able to start giving you insight, uh, into those kinds of questions. That's really where we live, you know, proprietary, structured enterprise data. That's a totally different realm, you know, and, uh, you know... And by the way, you couple that with language models and, you know, having natural language capabilities. Yeah, that's pretty powerful. Sorry, it reminds me of Iron Man and Marvel movies, you know, we need retrolist systems. (laughs)
- EGElad Gil
(laughs)
- FSFrank Slootman
It's kind of... That's a nice model. Uh, but I imagine in medical we have diagnostic models, you know, and we have all these different, you know, levels of intelligence that we can build, uh, that as long as they have the, the data, I mean, they're gonna be insanely lightning fast, uh, providing insight. You know, I mean, we, we acquired this company called Neeva, uh, you know, very recently. I'm very excited about, uh, bringing, uh, the expertise into, into the company because, you know, they're search experts, and I'm, I'm a search junkie. I mean (laughs) 25 years ago... I mean, I wish I had had search, you know, earlier on my life because it's such a huge thing, you know? I, I just can't help myself, I'm always... Um, and, and search is so addicting because it lets you sort of explore everything that's known and ever been written or published or opinioneered about, and, and sort of process all that information. But the problem with search is it has no context, right? It just matches on strengths, and, uh, you know, if, if you search on snowflake, you might get the company, you might get the weather, uh, you might get the, the, the social phenomenon, uh, because it doesn't know, it just knows the word. And it ha- and it's, it's incredibly... And so enrichment and context is really the name of the game in the world of data, right? We, we always like to say you... One attribute can, can make a data attribute go from, uh, being mundane to being high-octane, because of the context that it create all of a sudden becomes wildly insightful and, and impactful and predictive and all these kinds of things.So, you know, in order for, for, for search, you know, to, to get that context and become stateful, uh, is, is, th- those are going to be enormous step forward. And, you know, chat and search, you know, it all becomes one, one natural language conversation after a while. Um, so you combine that, you know, with having this, these new levels of intelligence specific to industries or just subject matters, um, you know, I, I think it's, that's really where there's a world of opportunity waiting to unfold still. And I'm, I'm certain that it will, you know.
- SGSarah Guo
Yes. Uh, you know, Inivo is a, a, a, a dear former portfolio company. Do you imagine that the, um, Snowflake, like, interface, um, for users, uh, changes a great deal over the next, you know, five, 10 years in, in, in terms of, like, supporting more natural language or a broader user set?
- FSFrank Slootman
Yeah. Both of those things. Um, you know, I, I think the, the... there, there still will be a future for, for BI companies, business intelligence, sort of Tableaus, Lookers, uh, Opworld. And, you know, dashboarding is, is done for a number of reasons. Sometimes it's just, you know, uh, basically providing data in a consumable format. But it's also done because it, it, it's a way to basically tell people, "This is how I want you to look at the data. This is how I want you to understand." So there, there is sort of a, a guiding element, uh, to dashboarding. Not all analysis is ad hoc based.
- SGSarah Guo
Mm-hmm.
- FSFrank Slootman
Now a lot of it is. And, uh, you know, for ad hoc, you know, nothing is going to be better than, uh, than natural language. Um, I, I at least, uh, I'm already using it, you know, we, we push Salesforce data into what we call Snowhouse, that's our internal Snowflake data. That's where we push everything into. And it's just incredibly easy to use al- already commonly available services and, and have, you know, a conversational relationship with that data. You know, who are my two top reps in, uh, in this country or that market, or this industry? You know, it spits it out in a fraction of a second, and, and with a beautiful graph, uh, attached to it and all of that. And (laughs) so, um, it's very addicting because it just, uh, it's just like search, right? You just keep going and going and going, and it becomes like a, a whole journey. Um, so yeah, I... definitely democratize access. Uh, anybody semi-literate will be able to get, you know, way more value than they ever imagined from the data. Um, and it will change, you know, how products get used. I mean, BI will not be the same. I think I, I see that as severely affected by, by this evolution, you know.
- SGSarah Guo
You made another acquisition of a company called Streamlit that I, I think we're also both familiar with. Can you talk about, um, the rationale for that?
- FSFrank Slootman
Streamlit is, is a company that does visualization animation, um, you know, for, for Python applications, but specifically in the world of machine learning. The problem with machine learning is, um, if, if you're not a programmer, it's pretty damn hard to consume, you know, what, what it is and, and how it works. Um, but Streamlit is almost reflexively reached for by Python programmers to basically make a machine learning model consumable by a general business, uh, user, right? You can manipulate the variables and it just redraws everything. Visualization, animation, uh, and, and that's really the, the reason that we acquired Streamlit, is A, you know, that's certainly... we have to have visualization and animation. And by the way, this also touches the world of BI because a lot of people use Streamlit, you know, for the same reason that they would use BI type of products. But this is just much more, um, you know, specific to all kinds of reporting and use cases and, uh, and, and, and dashboarding. Um, so what we wanted to do with Streamlit is to bring it inside Snowflake. We call it Stream- Streamlit in Snowflake. And the reason is, you need to have that hardcore trusted sanctioned, uh, governance perimeter, um, because otherwise people, people will not allow the business to use these kind of applications. Governance is a really big deal because the data needs to be sanctioned and, and trusted, and the business should not be able to get in trouble with the data. And, uh, that's really what we try to do at Snowflake. We are a hardcore enterprise-grade, uh, platform and it's really hard. I mean, you can bring Python to your data in two weeks time, but the problem is, you know, people are downloading libraries every couple of weeks to their heart's content, and people have no idea what kind of risks they are exposed to in terms of exfiltration and all that. We spent two years, you know, making, making Python non-porous, um, and it was an enormous effort to do that. But, you know, you go to large, uh, financial institutions, they won't let Python anywhere near our core data, which is not even a conversation. And we're like, "Well, we're gonna do it in a way that, you know, the people that use Python," there are many, obviously, um, but they can do it in a way that they don't violate, uh, and, and create exposures, um, to the enterprise. So that's really the, the role that we play. We talk about governance a lot. Uh, we talk about data quality a lot, and we get into this conversation, I don't know how many times a day, because in a, in a world of AI, if you don't have highly organized, optimized, sanctioned, and trusted data, what, what do, what do you want, you know, your models to do? Just kind of train on, on, on a data lake? I, I call it a landfill, you know. I mean, you have no idea what the hell is in there. You know, everybody dumps their stuff in there. You're going to go train on that? It's just absurdity. So, you're having highly organized, optimized, sanctioned data is really, it's a prerequisite for, for all... and people publish what they call data products. I'm sure you've heard that term, uh, before. A data product is essentially, you know, I've taken data, you know, out of a lake, and I've created into a trusted, optimized, understood, uh, object that I can now give to the business and stand behind. That's really the role of the Chief Data Officer to, to make the data, you know, trusted, organized and optimized, and then also that the business can't get in trouble, you know, with it either because the data is no good or, or because they're breaching all kinds of security and compliance, uh, you know, aspects, uh, of, of, of using data. So that's... Streamlit is really important to us. Uh, the, the great thing about it is it's an open source project. So, you know, peop- so many people out there are, are reaching for it when they want to publish something and, uh, you know, we're like, okay, we're going to bring that inside the enterprise perimeter and make it high trust, you know.
- 36:29 – 45:13
Data Management and Industry Transformation Future
- SGSarah Guo
I go back to sort of the, um...... journey you described from, uh, not just a data warehouse, but only data warehouse as a first workload, to, you know, broadly, you know, more online anali- analytics, other workloads, applications that sit inside Snowflake with, um, you know, unified data. Wh- what are the, what are the biggest challenges you guys face in making that vision come true? Is it convincing people to, like, move to, you know, customers to an entirely new architecture? Is it building the ecosystem? Is it just supporting the workloads? Because it's a, it's a very big rewrite of sort of enterprise architecture overall.
- FSFrank Slootman
Yeah, but it's, um, you know, we are rewriting anyways (laughs) because of our, our, our migration to cloud is, like, the most disruptive thing ever. Um, and yeah, look, you know, w- when I was at ServiceNow, w- we basically had an on-premise architecture that we hosted in the cloud. And by the way, I'm, I'm, I'm not being, you know, unduly critical here. I mean, 'cause it was very useful that we were, you know, a single-tenant platform. It had all kinds of advantages, and we were able to, uh, to manage it really well through massive standardization and, and, and things like that. I'll give you an example. Um, you know, all, all, all the federal business that we had, um, at ServiceNow was all on-premise Oracle because, you know, you could not get in there with a cloud-hosted solution. Just couldn't. By the way, you still can't. I mean, uh, the certifications in, uh, on, on federal are, are so insanely demanding. Um, you know, federal is, is, is a very small part of our, our business because we spent... we're, we're, we're in the process for years and years and years, uh, to meet, to meet those standards. It's very, very hard, right? Um, but we are a pure cloud implementation. We can't run on-premise. I get asked that by people, you know, and like, uh, I mean, I- I can't even conceive of it, you know, the way Snowflake works, right? Because it commandeers, you know, resources. It's not a, it's not a machine-centric, uh, platform, you know? Um, so they... it's, it's, um, it is a big change. There's, there's no doubt. And, um, they just... as I said earlier, you know, um, you know, we, we fight the siloing of data because we're that kind of a company. From a data strategy standpoint, we really tell people, "You need a different data strategy for the cloud. Do not continue with what you've been doing because you've created a massively proliferated bunker silo world, and it will not serve you in the world of AI and machine learning and any, any level of data science. If you wanna drive intelligence from data, you're gonna be in a world of hurt if you keep siloing the data." And, and we tell that to application developers, to ISVs, and say, "Look, don't have your own data container, okay?" Because instinctively, application developers, "Oh, I wanna have my own, my own data layer hanging underneath it." And I'm like, "You know what? Um, it, it's... you're gonna hate it because, A, it adds no value to what you do because you're not a data management expert."
- EGElad Gil
(laughs)
- FSFrank Slootman
It, it's just a utility function, uh, you know, for you. But then, you know, you're in another silo, and the customer's now frustrated because they're gonna start pushing that data into Snowflake, and now we have pipelines and ETL processes and all this kind of stuff, and latency issues, governance issues, all this kind of stuff. So, we, we just announced that... this relationship with Blue Yonder, for example, says, "Hey, we're gonna fully re-platform, you know, on Snowflake," because in the world of supply chain management, that's really important because we need to have visibility, you know, across all the entities that make up a supply chain, but you only, you can only do that when you have a single data universe, and when you have all these containers, it's impossible. That's why supply chain management has never been platformed, 'cause the data problem was unsolvable, literally, you know? Um, so this... and, and then the, the other thing is the supply chain management. I mean, they, they run these extremely demanding, uh, analytical processes, right? And they run many, many, many times, you know, uh, uh, you know, per minute, per hour, and they are very, very commanding of resources, right? So again, this is where, you know, our style of computing is, is very, very desirable, right? Because I, I can run the processes. I can run them as fast as I need to. I can run as many as, as, as I want concurrently. So, all these new architectural things are lending themselves, really, to use cases that have been there for generation, but, you know, supply chain management isn't email spreadsheet business. I mean, it's still living in, in, in the world of Microsoft 30 years ago. That's insane, right? Because it's, it's one of those use cases that should have been extremely optimized, but it isn't, right? So yeah, you're gonna be doing re-platforming, re-architecting, and, and, uh, and re-imagining. That's what we did. Snowflake is a reimagination of data management for, for, uh, for cloud computing. But it... you know, as, as we get through our journey, it's looking more and more different than what it, what it used to look like.
- EGElad Gil
You mentioned some very large-scale evolutions in terms of just the data world there. Uh, what are some of the other future directions that you're most excited about, or the big thrusts that you see coming in terms of data?
- FSFrank Slootman
Data is going to redefine whole industries, okay? And that, that, that's what I find the most interesting. And, and the reason I say that is, um, first of all, you know, nine out of 10 conversations I have with customers are not technology and architecture and all that, and migrations. It's about industry use cases. It's about call centers. It's about, you know, making medicine predictive, for example, because everybody knows, you know, healthcare is, is economically, you know, not viable, uh, at the scale that we need to deliver it. And so data can make us, you know, predictive and prescriptive, right? We can... if we have enough data, you know, we can tell who is at risk for what disease, when, and what they need to do. All data-driven. This is not... well, we... (laughs) this is not somebody's opinion. The data just... data doesn't have opinions, okay? (laughs) It just... that's what it is. And it gives you the accuracy, uh, to go with it. So, the more depth and breadth of data that you have, the more, that certain that stuff becomes. But this is, this is how, uh, healthcare will become, uh, much more effective, obviously, because you don't... you're no longer reacting to disease and, and symptoms, but you're getting ahead of it. And every f- every healthcare institution, you know, that we talk to, and they're a customer of ours, this is where they want to go, this is where they need to go. They don't want to treat disease, they want to prevent it.... and they wanna anticipate it. So, it will change, you know, healthcare as an industry but, you know, I just mentioned, you know, auto insurance is a similar type of example. In the world of pharma, you know, it takes on average 12 years to, um, you know, to, to, to bring a drug to, uh, to market. Well, then you've got five years left before your patent runs out. But what if I could, could, could compress that by one, two or three years? Now you've changed the economics of the entire industry, right? So, you know, data is, is far more, um, important to how an, the, the, the economics and how the industry functions than, and people still realize, you know.
- EGElad Gil
How, how do your em- investments in R&D reflect this? Or what are the big areas of thrust that you have right now from an R&D standpoint?
- FSFrank Slootman
Well, the, the, the hardest part, you know, for us is, you know, I have to (laughs) massively enable... we have to massively enable this platform to be incredibly, broadly and, and capable, not just broadly but also in depth because if it doesn't do what people need it to do or it doesn't do it well, they're going to say like, "Well, forget it, we'll just pump the data over here." And now we're back to, you know, fragmenting and, and, and siloing the data. So if there, if, if we have the data, we have to enable the workloads, okay? We have to. And that's really hard. That's really hard. I mean, you, you mentioned some of the, some of the workload types but we do things like global search, okay?
- EGElad Gil
Yeah.
- FSFrank Slootman
Because in the world of cybersecurity, you know, that's incredibly important because a lot of cybersecurity companies that, you know, they are partners of ours, they are running on the data cloud. They don't... they... because they couldn't sell to their customers yet another database container 'cause we didn't want it. They said, "Look, we'll bring the data here and then we can combine it with all these other data sources," you know, vulnerability and, and... and then, you know, our analysts can, can search one day in the universe instead of 15 of them and try in their head to figure out what does it all mean and do something with it.
- EGElad Gil
Yeah, I'm definitely seeing a lot of people right now building in terms of, um, Snowflake apps so that they can just, uh, maintain the data locally within a Sno- Snowflake instance for a customer, but then provide enriched functionality on top of that or access to that data in ways that are really performant and combined with what the, you know, uh, with what the company's trying to do more broadly. So I think that's been a really great innovation for the industry. Um, I, I guess one last question is just around the macro shift. So obviously, we've, we've gone from a zero interest rate environment where everybody was just buying software, um, like crazy to a world where people are cutting SaaS budgets increasingly, they're rethinking spend. Um, does the macro environment change your point of v- point of view on consumption or credit-based pricing or, you know, how you think about, um, the, the pricing and economic model in the, in this new regime?
- FSFrank Slootman
Yeah, not really. Um, you know, I... we have different, uh, stakeholder does have different opinions on this. Investors, of course, love it when you have customers over a barrel and you can keep a gun to their head and they're gonna pay you no matter what. I don't
- 45:13 – 50:09
Managing Resources in Changing Economic Environment
- FSFrank Slootman
particularly like that. You know, when I was at ServiceNow, you know, I, I always felt that it was not an equitable relationship that we had with our customers, um, 'cause oftentimes, you know, they, they would sign up with us for many millions of dollars and it took them nine months to even get in production. They were paying for all their users all this time. I'm like, "How, how is that equitable?" Um, so one of the things that I really liked about Snowflake and cloud computing and consumption models and the elasticity is that we pay for what you use. It's a utility model. And, and, um, you know, is, is that painful? Sometimes? Yes. I mean, I, I, I talked to the CIO of a bank last week and he said, you know, he says, "My bank's growing 3%. Snowflake's growing 22%." You know? And he said, "That can't go on forever." You know, the CFO gets in there and he goes... he starts going bullshit on everybody and saying like, "Hey people," um, you know, they basically say, "This is the size of your bread box. Live with it. You're not going to get a new contract." But it's... and then people need to go back to the, to the drawing board and go, okay, it, it's a very fine-grained thing because you can go into your Snowflake workload and say, "Okay, I'm going to downgrade the provision on this. I'm going to run this less frequently. I'm going to change the retention period on data." You can do all these things to, to lower your, your, your consumption of storage and, and compute. Does that hurt us sometimes? Yes. But it's, it's a value to the customer because, you know, if, if you're in a SaaS subscription model, they got to wait for the next ƒ1 before they can start cutting off a limb here. Whereas with us, it... you can do it in near real-time. Investors don't like it. I understand because they, they love it on the way up. They just hate it on the way down. (laughs)
- EGElad Gil
Yeah, absolutely. I guess related to that, a lot of the people who tune into No Priors um, are people who are running their own companies right now and they're at different stages. You know, we have everything from early stage startup CEOs to executives at larger companies, um, researchers, engineers, etc. And one of the big questions of their mind right now is how to manage differently through this, you know, economic downturn or this shift in spend or this shift in the macro environment. You obviously are known as a CEO who is very good at making tough choices and, you know, prioritizing in both good times and bad times. How should people think through managing differently in this, in, in this changing economic environment? What are the first things people should do?
- FSFrank Slootman
You know, I mean, I see all these layoffs, you know, with Amazon and Meta and Google and all this kind of stuff and, and, um, we, we don't do layoffs because we don't wait until there is a, you know, huge headwind. Um, we're always pruning the tree, so to speak, right? So we don't have to do it as some massive event that is super unsettling. Um, you know, management of resources is something that should be happening on a, on a daily basis. Not just performance but also, you know, bringing supply and demand in sync with each other, alignment, um, that should be happening constantly. But the, the culture has, has sort of evolved over the years where it's just, it's just unfathomable, if that's a word, where you just... you... they can't conceive of being so confrontational that we're gonna take somebody out of a job, so we'll just look the other way until we get a crisis and then we start r- ripping out, you know, tens of thousands of people. I just don't think that's, that's, uh, fair a- as, as well as effective, right? I mean, so you're... this is the reason my world doesn't change all that much because I was already doing it. So, uh, these are just more, um, sort of management practices and, and, and ways of thinking about, you know, how you run things, um, you know, rather than, "Oh gosh, we have economics headwind now. We need to change everything we're doing." No, you don't. You just need to run things. You know, like you always... by the way, people are not used to living in downturns. You know, when you've been around longer, it's like, hey, they come around. Okay, it's part of life. And, and by the way, let's, let's, let's, you know, let's double down, triple down, put our game face on, put our boots on, you know, we're in the fight now. This is actually going to be a lot... I will say this, it's going to be a lot of fun.
- EGElad Gil
(laughs)
- FSFrank Slootman
This is where the fight really happens, right? So in other words, you can get up for it. You know, you, you just amp things up. That's what you're doing. People are growing up and like, oh, they, they only know, you know, that the trees grow into the heavens. Trees don't grow into the heavens, okay? They don't.So they need to- everybody needs to grow up a little bit, you know, and- and just get a leash on reality and say, "Look. This is- this is part of life." You know? Do I have to start rethinking everything because economically things are now, you know, different? Yeah. To some degree, yes. I mean, we're- we're scrutinizing productivity much harder in sales organizations. You know, we might be a little bit quicker on the trigger, all that kind of stuff. For startups, obviously, you know, raising money is a whole different ball game and you guys are in that world, uh, so they- they definitely need to think harder. I mean, when I was at DataMain we- we- we would r- basically run the company from one fundraising milestone to another. That's how it was back then. That- that hasn't been the way it's been. I mean (laughs) , uh, you know, in- in recent years people have not never had to raise money or- or run businesses that way to prepare themselves for a fundraising milestone. They've never done it before. Well you should, you know? 'Cause that's how you stay alive. I, you know, I mean-
- EGElad Gil
Yeah.
- FSFrank Slootman
... fundraising is oxygen for a company, you know?
- EGElad Gil
Yeah. Basically, I think gravity turned back on and everybody's like-
- FSFrank Slootman
Exactly.
- EGElad Gil
... realizing it.
- FSFrank Slootman
Yeah.
- 50:09 – 51:21
Amping Up Energy and Intensity Amid Economic Headwinds
- FSFrank Slootman
- SGSarah Guo
Frank, this is a great conversation. Is there anything that we missed that you think would be useful or interesting to talk about?
- FSFrank Slootman
Um, well we- we've already talked about amping things up and, uh, that's always the, you know, um, you know when we- we have conversation like this and a lot of people are listening to it. I just- I just wa- I'm- I'm trying to get people to say, "You know, my next meeting, my next message, my next encounter, my next situation, I'm going to amp it up." Uh, because it's just a choice that you make. And, um, you know, don't be afraid, you know, that people will react poorly to it. They won't. The good people will actually love it. And especially if you're in a leadership role, and who isn't, you know, this is- this is really what people want. They want to inject energy, and focus, and intensity, and quality so that the whole place starts to feel, you know, exciting, you know? And- and it's not like, "Oh, it's 4:00 (laughs) or 5:00," or whatever. No, right? It's- it's much easier to live in an energized environment than one that's devoid of energy, you know? So...
- SGSarah Guo
I love it. That's a very, um, it's a very courageous message. Uh, thanks for doing this, Frank.
- FSFrank Slootman
You bet.
- EGElad Gil
Thanks a lot.
Episode duration: 51:22
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