AI and the Future of Work: Artificial Intelligence in the Workplace, Business, Ethics, HR, and IT for AI Enthusiasts, Leaders and Academics
00:05:07 · Jeremy Burton
[00:05:07] S0: Yeah. Thanks for the the, the intro. I I appreciate it. No. Look. I mean, as the accent would suggest, I am not a native of these parts, although I've been here thirty years. So I say tomato and aluminum and all the good words y'all Americans will understand. But, no, I I actually came out to The US in in '95, long time ago, twenty... Thirty years to work for a guy called Marc Benioff. Marc was only a couple years older than me at the time. We were both a lot younger and far more handsome back then. But Mark was working on on a new product, and I came out to to learn about it, and I ended up... I told my wife I was staying two weeks, and I ended up staying six weeks, and did the the launch demo with with Mark on on stage at the Moscone Center and with Larry Ellison in attendance, and I moved out six weeks later. So, yeah, I've I've been here a while. Always done enterprise software. Most recently, a startup. I... My entire career had done big company things, and I really badly wanted to do something from scratch. So when I joined Observe, it was, you know, sort of a handful of founding engineers. And it was as much to prove something to myself as anything, which is I'd I'd worked at a lot of big and successful companies, but, you know, really, that that bigness and successfulness was not really down to me. I helped, for sure. So then the question is as well, you know, can can you get in at ground zero and make a difference and get something going and off the ground? And I think those are the folks who probably deserve most of the credit for getting these huge corporations to what they are today. So, yeah, little bit more meat on the bone.
00:07:03 · Dan Turchin
[00:07:03] S1: Incredible journey. Great story about Benioff in... Back in '95. Yeah. You made a fateful decision when you were starting Observe to hitch Observe to Snowflake? And when I think about the observability space, whether it's Datadog or Dynatrace or others, you know, I I think about applications first, not about data platforms. What insight did you have that led you to team up with Snowflake very very early on?
00:07:31 · Jeremy Burton
[00:07:31] S0: Yeah. There's a couple of factors. You know, when I I left Dell, I mean, e... EMC had acquired the company I worked at. Sorry. Dell had acquired the company EMC that I worked at. I really wanted to go do something that was, like like, in the in the core of of of data. And I'd been on the board of Snowflake at that point for probably three years, and I was like, okay. I thought the database world was over. I thought it was gonna be reinvented by Hadoop. We all probably can still remember big data and Hadoop. And then when I came across Snowflake, I was like, ah, this is really, a rearchitecture and a reinvention of of the database. And I felt, you know, probably after seeing it grow for a couple of years that it it was gonna do great and that there would be companies that would be sort of snowflake shops. And, you know, 20 earlier when I was at Oracle, that that... It... It's like history repeating itself. Right? I saw that firsthand. Anyone who built an application on top of Oracle, a good one, actually did quite well. Because certain companies were like, yeah, we're an Oracle shop. Do you wanna put more data in Oracle? Great. Bring it on. And and so I I was I was looking to do something which was, like, looking for a company that was building on top of Snowflake. And I I I talked to three or four of them, Southern Hill Ventures, that were one of the very early investors in Snowflake. They they had funded a number of companies that were building on top of Snowflake. And the the observed pitch resonated with me, not just because they were building on on Snowflake, but if you if you look at the the problem of observability, and it it... It's still somewhat the same today as it was seven years ago. You know, if you wanna see if there's a problem with your system, if something's broken, you would look at a metric, and you would have a time series database and a tool that would sit on top of it. And then... But if you wanted to dig in and investigate, oh, well, then you don't... That's not metrics. That's logs. And by the way, that's not in a time series database. That's in this bespoke system over here we call Splunk. And then if you wanted to go dig into, you know, like, latency performance, oh, no. That's that's actually not logs. You know? That... You you gotta look at spans and and and traces, and that...
00:10:00 · Jeremy Burton
That's in a system over here, and it... It's it's like a New Relic or an AppDynamics. And so the sort of big brain thought was quite simple. It was like, why don't we put that data in one database, and then when we see a spike in a chart, we can see the logs for the spike, and we can see the spans for it. And so the founders, the thing that resonated with me was observability is really a data problem. I know people are saying that they've got lots of tools, it's confusing, and it's expensive, but they have lots of tools, and it's expensive because they have fragmented data. And so Snowflake was really one of the first databases to come along and elegantly deal with the diversity of data, unstructured, semi structured, structured data, as well as the scale. And it was really like a new database architecture that would enable them to scale. We had a couple of early Snowflake engineers on the Observe team as well, so that helped the decision along quite nicely. Philip Unter Brunner, who did the query engine, and Vadim Antadol, who did a lot of the unstructured data support in Snowflake. It was quite a controversial decision. We lost a chunk of the engineering team over it, because there were plenty of folks in that early team that wanted to build their own database, which was not a stupid thought, because, you know, the... I mean, Splunk built their own database. Honeycomb built built their own database. But we felt like, hey. If we didn't need to build our own database, we could spend more of our engineering time adding value on top of that database, and ultimately, that's that's what people are charging for. So, yeah, we we lost a bunch of the team. We didn't know at the time we made that decision whether we could actually build an an interactive observability experience on top of what was inherently back then a a data warehouse, which, you know, typically is batch mode type processing. But we convinced ourselves after six months it was possible and and never looked back.
00:12:07 · Dan Turchin, Jeremy Burton
[00:12:07] S1: It was prescient because you foreshadowed an AI era when there's so many more applications, so much more software, and most importantly for your business, so much more telemetry data, and it's so... Observability is infinitely harder. [00:12:24] S0: Yeah. I mean, you know, back when we started, a terabyte a day, five terabytes, so that was a lot. I would tell you we have midsized companies, let's say a thousand to 2,000 employees, that have got 30 to 50 terabytes a day at this point, and and large enterprises that are 500 to a petabyte of of data a day. So the the data volumes are quite astronomical. And just to put that in perspective, when I started at at at EMC fifteen years ago, we had one customer in the whole world that had a petabyte of data. Since the beginning of time to to to 2010, they they collected a petabyte of data. We have some customers that will will collect that every two days. [00:13:09] S1: Unbelievable. You have had a catbird seat through your board role and now obviously through Observe on really exciting epic journey at Snowflake. I had the pleasure of working under Frank Slootman when he was at ServiceNow. You presumably did when he was EMC. He famously left ServiceNow to lead Snowflake. Now Sreedhar is the CEO there. And by the way, on this podcast, we recently had Arnon Kishuri, who's the chief people officer at Snowflake. Could you give us a little bit of an an insider's tour of the culture at Snowflake? And I know it's contribute... It's it's it's a big factor in why Snowflake has been so wildly successful.
00:13:49 · Jeremy Burton
[00:13:49] S0: Yeah. I mean, look, I go back to sort of the two founders, Benoit and and Thierry. I I knew I knew both from Oracle. I knew Thierry better. I I actually played soccer with with Thierry. He he was a far better engineer than he was soccer player, which is which is which is great. Right? Because... So so they they... There's a... Like, the engineering culture, I'd say, in the company is incredibly strong. It's a very sort of warm accepting, almost collegiate type place. You know, the the product has been wildly successful. I think, you know, when Frank came in, you know, his power alley is scaling from a few 100,000,000 to sort of low billions. And I think probably then the very early engineering centric culture sort of broaden to include the sales team, you know, when you... You've gotta start to land, like, some of the biggest and and and largest accounts in the world, then, you know, you've you've gotta build up more muscle on the go to market side of the house. And then, look, I think Sreedhar now coming in. It's actually been... I I... Obviously, I knew Sreedhar from from from from being on the board. And I think the big challenge of not just Snowflake, but any company the size of Snowflake is there's a new world out there. There's a new reality around AI. You know, Snowflake and and any other company, you know, created before the last couple of years is not an AI native company. And so how do you get a company that's 10,000 people to to to think that way? And I think Sreedhar just deserves massive, massive credit. Every bit as much credit as maybe Frank would... Deserves for scaling the the go to market side of the business for for really getting the company on the same page around AI and what it means to be an AI native company, and it's painful. You know? There's no easy way to do it. I mean, and, you know, observe. I mean, I ran a company of a couple 100 people. It's it's quite easy to get a relatively new company onto a new trend because you don't have many people, and, you know, by nature, have been in a start up. I think you are much more attuned to the to the latest trends as they come along. So, yeah, I think, you know, Sreedhar is is different to Frank, is different to Bob Muglia, who was the original CEO. But I I do believe in sort of a a leader for a time, and Frank was certainly the right guy to bring in after...