411: Jeremy Burton, GM of Observability at Snowflake: The Data Layer Was Never a Commodity. It’s the Whole Game

00:00:01 · Jeremy BurtonPlay from here

[00:00:01] S0: A few queries run on your enterprise data will give you vital context that you can supply to the LLM so that you can burn less tokens over here. And so, feel like, in the enterprise at least, if you wanna get the return on your AI investment, you've gotta do some work on your data foundation. Otherwise, you either are not gonna get the context and actually not get the right answer, or you're gonna blow a lot of money getting to the right answer. So it's gonna be one of those two things. Yo. It's the future. Don't hit the snooze. AIs here giving humans the boost. Team humans rolling. Brains in the game with Dan Turchin. Y'all remember the name. People reign in the mix. No stopping the flow. Better work, better life. Yeah. We're ready to go.

00:00:50 · Dan TurchinPlay from here

[00:00:50] S1: Good morning, good afternoon, or good evening depending on where you're listening. Welcome back to AI in the future of work episode 411. I'm your host, Dan Turchen, CEO of PeopleRain, the AI platform for IT and HR employee service. As always, if you've enjoyed this great conversation or any other, you owe it to humanity to pay it forward. Share a link to this one or any other that you liked with just one friend, and they will know that you care about making humans better with great technology. If you leave a comment, I just may share in an upcoming episode. Like this one. Thank you to Tony from Austin, Texas. Hook them horns, whose favorite episode is number one fifty nine from back in 2021 with a Shu Garg, general partner at Foundation Capital about finding and investing in the future of AI. That was a fun one. Shu's been in the news quite a bit. It's been talking a lot about context awareness for AI. Go look that one up. We learn from AI thought leaders weekly, and, of course, the added bonus, you get one AI fun fact each week. Here it is for today. Anthropic cofounder Chris Ola was invited to speak at the Vatican in response to Pope Leo the fourteenth's encyclical Magnifica Humanitas as part of Anthropic's initiative to widen the AI conversation in his remarks. Ola summarized Anthropic's perspectives this way. AI may displace human labor on a massive scale, making the support of displaced workers a moral imperative. Because AI development is concentrated in a few wealthy nations, we need a mechanism to ensure its economic gains are shared globally. As AI systems become embedded in everyday life, society faces pressing questions about what it means for individuals, families, and communities to truly flourish. The internal structures of frontier AI models are increasingly mysterious and unsettling. Researchers are discovering internal states that functionally mirror human neurological results and emotions. It's a pretty dense read as is the encyclical. Of course, I'll share a link to that in the show notes. My commentary on this one, the pope's encyclical echoes themes shared by pope Leo the thirteenth in 1891. Following the first industrial revolution, Pope Leo the thirteenth condemned both unrestrained capitalism and revolutionary socialism. Similarly, Pope Leo the fourteenth rightfully says AI is not morally neutral.

00:03:19 · Dan TurchinPlay from here

Both embraced the need to not reject modernity while also not letting technology violate human dignity. Just as Pope Leo the thirteenth didn't slow the pace of innovation, Pope Leo the fourteenth's encyclical will only cause us to ask more thoughtful questions, which in itself is an important outcome. I applaud the pope for using his platform and influence to share a message that humans can and must coexist with machines. Intelligence will never be outsourced to bots. Only humans have true agency because we dictate what AI can and can't do. It's pretty dense fun fact for this week. But, go and read up on that, and, we'll continue to unpack some of these topics in future weeks. Now shifting to this week's amazing conversation. Jeremy Burton's the GM for observability at Snowflake post acquisition of his company Observe where he was the CEO. Prior to Observe, he was EVP of marketing and corporate development at Dell where he also served as president of products for EMC. Jeremy joined EMC from Serena Software, where he was CEO. Prior to that, he held leadership roles at Symantec, Veritas, and Oracle. He's also a long serving member of the board of directors at Snowflake and a member of the McLaren racing advisory board. He received his bachelor's in engineering from the University of Surrey, Southwest of London, which, of course, served as the training base for the London twenty twenty... Twenty twelve Olympic and Paralympic games. One thing that Jeremy has not done is appeared on this podcast that's about to change. Jeremy, welcome to AI in the future of work. Let's get started by having you share a bit more about that background and how you got into the space.

00:05:07 · Jeremy BurtonPlay from here

[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 TurchinPlay from here

[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 BurtonPlay from here

[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...