00:59:37 路 John Coogan, Sridhar Ramaswamy
[00:59:37] S1: Can imagine you're doing well. The the company is doing fantastically. I am interested to hear no. I mean, obviously, there's been an emotional roller coaster, but I'm more interested in the data that you're seeing that shows acceleration, so much promise, so much opportunity in this particular business. [00:59:57] S8: Yeah. Data is the foundation for insights. I worked in a data company. I worked in the search ads team at Google, where great data was the flywheel that made it into a great business. That's what we aspire to do with each and every one of our customers. AI has done a couple of things. It's made the act of bringing data into Snowflake doing just a whole lot easier. Pipelines that used to take weeks to set up or migrations that used to take years now have dropped to days and months, which is pretty remarkable. But people also realize how much more power they can get by having great conversational access to their data. And now with things like Snowflake co work, how we can actually solve pretty meaningful business problems in an interactive way, it's that it's that loop that is compounding for us that drives a lot of our growth.
00:59:57 路 Sridhar Ramaswamy, John Coogan
[00:59:57] S8: Yeah. Data is the foundation for insights. I worked in a data company. I worked in the search ads team at Google, where great data was the flywheel that made it into a great business. That's what we aspire to do with each and every one of our customers. AI has done a couple of things. It's made the act of bringing data into Snowflake doing just a whole lot easier. Pipelines that used to take weeks to set up or migrations that used to take years now have dropped to days and months, which is pretty remarkable. But people also realize how much more power they can get by having great conversational access to their data. And now with things like Snowflake co work, how we can actually solve pretty meaningful business problems in an interactive way, it's that it's that loop that is compounding for us that drives a lot of our growth. [01:00:49] S1: Is has there been any movement for Snowflake? Whenever I hear the story of a a a data lake, a properly managed data warehouse as an entrepreneur, even in a small business, I think that sounds amazing. That sounds like the dream. Then I see the companies that, you know, actually have the resources to onboard be, you know, immensely large, and obviously, that's fantastic for your business. Yep. But I'm interested in in what the future looks like. Is there a world where a 10 person start up with AI agents and and these pipelines that can be built much faster can actually set up their and then not have to go through a cumbersome migration in the future.
01:01:34 路 Sridhar Ramaswamy
[01:01:34] S8: Yeah. We are seeing that happen in front of our eyes with Snowflake's own data team. Yeah. You know, they, like with every other company, used years long. You ask them for a feature, they'd be like, Here, take a ticket. Come back, you know, in a few quarters. What they've been able to do with Agentic AI is grind through those kinds of backlogs very quickly. Absolutely. Data and agents are going to make it much easier to set up these things and have them evolve as they go along. I'll give you examples from the public. We rewrote our, both our support teams and our SRE team's software. These are the folks that take care of different kinds of problems that we get into an, and the net result of that by agents investigating the problem. And if you see enough instances of a problem that you have not seen, you go figure it out, go write a tool for it, it's now in a self healing loop. I increasingly imagine that more and more operations get into that kind of a mindset where there are very competent agents, sets of recipes you can call them skills, there'll be some other name tomorrow that take care of problems, but it's it is a self learning loop. That's what AI makes possible.
01:02:45 路 John Coogan
[01:02:45] S1: Got it. Where are we in the path to, like, fully automated migrations, fully automated new integrations? It feels like every new model release were like, this is the one. This is the one. The nontechnical CEO is gonna be doing the job now. He's just gonna say, hey. We we have two systems. Go fix it. Go integrate it. Get it into Snowflake. It's gonna happen. And then reality sets in and there's not just token costs and cost of that to to delegating to AI, but also just the real world of of other decisions that need to be made that might be outside of the context. So what are the the the remaining challenges that come up when you're building a new integration or or working on a migration?
01:03:34 路 Sridhar Ramaswamy, John Coogan
[01:03:34] S8: Yeah. I think the timelines are definitely shrinking Mhmm. When it comes to legacy migrating off of legacy platforms, the on prem ones. Yeah. We used to think of them, the biggest ones, as running into, say, like, three odd years. And these strike terror into every company's heart because it's three years of, like, really anxious development work and waiting for results and hoping things don't go wrong. To give you very, concrete numbers, we now feel a lot more confident that we can tackle really tough migrations and have them finish in a couple quarters. That's a big deal. It's going from 12 down to one or two. And the migration team, which work on top of agentic harnesses that we create, are confident that the technical parts of these problems will be solved by the end of the year. But there is the change management. There is all of the other applications that are running on the old system that you have to validate on the new system and ensure that there is business continuity. That kind of change management is still going to be nontrivial. But the technical parts, the act of, doing the migration or writing new software, these are the things that AI is absolutely driving down. [01:04:43] S1: What is the biggest [01:04:45] S8: By the way, I actually go check out every feature my, team puts out using our coding agents. Mhmm. That's already a thing. And, honestly, it's not that hard if you have a modestly technical background.
01:04:45 路 Sridhar Ramaswamy, John Coogan
[01:04:45] S8: By the way, I actually go check out every feature my, team puts out using our coding agents. Mhmm. That's already a thing. And, honestly, it's not that hard if you have a modestly technical background. [01:04:55] S1: Yeah. Yeah. No. That makes sense. What is the biggest lesson that you or the company have taken forward from Frank Slootman's era? [01:05:07] S8: Frank was always about amazing go to market execution. Yeah. And we remember that. Okay. And, in fact, our sales teams [01:05:14] S1: Yeah.