Nathan Labenz: belief

Transcript context

…Thank you, Nathan. Thanks for having me. I'm excited for this conversation. There's going to be a lot to learn. I think people, we have a very diverse audience. The number one profile is AI engineer. And within that profile, people work at a lot of different kinds of organizations, from solo entrepreneurs and consultants to startups to enterprises. So some people will certainly know Snowflake and will work at organizations that are customers of Snowflake. Others probably have heard of it and don't really know too much of the backstory. So maybe for starters, just kind of give us the real quick Snowflake 101, and then I'd love to go into how AGI pilled is Snowflake today. Sure. So Snowflake is a data platform. We call ourselves an AI data cloud. So what that means is our customers bring a lot of their data onto Snowflake so that they can secure it, govern it, and analyze large amounts of data for various insights, dashboards, and the like. And from an AI perspective, because there's a lot of gravity to data, our customers do not want to replicate data in multiple places. Instead, they want to bring AI to run next to data. So that's a very high-level overview. And the AGI pilled is an interesting phrase. For us, we're quite practical. We serve large enterprises, and the goal is to get to high-quality AI agents that create positive ROI for customers quickly. And that can happen today, and it is happening today. Super excited about where things are.…

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