The Exchanges

Q Coming into this role as CEO, you've been here almost over two years now. What has been the biggest surprise for you leading through one of the most volatile environments?

A I'm very pleasantly surprised by how quickly, ah, a pretty large team in dozens of countries has adapted to a very new environment of operating. Two years ago, AI wasn't nice to have, but no one thought that it would affect their day-to-day life. And yet, what we expect, for example, from, I expect our sales team to be able to show off Snowflake Intelligence, ideally on their phone, every single day. That was not something that I thought would happen all that quickly. Similarly, solution engineers went from people that clicked things on screen And maybe wrote a SQL query or two, to actually being really good and proficient with coding agents in order to deploy actual problem, you know, solutions to problems for our customers. Similarly, our engineers have gone from, we are a database company, we make 24 month plans. Database companies love making long plans, to, I guess we'll figure out what we do next week, and act week on week. I think That's been a very pleasant surprise for what I said, what I said started as a database company. Companies don't change that quickly, but I think the company has transformed itself very, very quickly. It doesn't come easy. It is, it is hard, but I think that's been very positive.

AI assessment note: “I'm very pleasantly surprised by how quickly, ah, a pretty large team in dozens”

Q I'm really curious, like, because we're in such a competitive environment, you, you alluded to this a bit, like culturally, it's totally different in, even from like the beginning of last year. So how do you keep the teams motivated and kind of, uh, able to weather the storm with you as it, as it changes so much?

A You have to embrace change. And, um, you also have to find people. There are a class of people that thrive under change. You have to make sure that they are in positions of being able to have an impact. When we wanted to roll our coding agents, for example, to our solutions team, we identified 35, forty-odd people that were naturally inclined to want to go learn, to want to go tinker. You hold them as exemplars to the rest of the team and, ah, help spread the message, help spread change through. Winning over iconic people with extra effort makes a huge difference. I joke to people that I could scream from the rooftops to all my engineers about how they really need to use coding agents. It's not going to have that much impact. They're going to go like, what does he know about software engineering? On the other hand, Benoit, our iconic founder, fell in love with coding agents. And Benoit is a truly religious figure. When he believes in something, trust me, you're going to hear about it. And every engineer that he met heard about the impact that these coding agents had on Benvo's own day-to-day work. That had a huge impact. So you also need to be strategic about who do you have representing change. And the more you can have naturally influential people represent change, the easier it's going to go.

AI assessment note: “You hold them as exemplars to the rest of the team and, ah, help spread”

Q I guess to take a step back a little bit further, where are we exactly in the AI super cycle?

A It's a, it's a great question, and my humble answer is, I don't think anyone really knows. It is early, and it is useful to draw from history about similar kinds of large changes. And if you look back, even things like industrialization, which one tends to think of as like some discrete thing that just happened within a few years in, I don't know, 1800, something like that, actually is a phenomenon that started closer to the 16th century and just kept going for a very, very, very long time. I think AI represents the beginnings of us being able To run truly thinking algorithms, to industrialize thought in a very, very big way, and I think it's very much the beginning. And I think there are lots and lots of applications for things like this. Everything, as I said, from being able to pretty much Create, for example, what's called a classifier or a sentiment detector. You have a piece of text. Is this text angry or happy? Um, being able to do problems like that without really needing to know any programming. Two, Let me think about a complex analysis that I am going to do when I'm given a new piece of information. We get revenue information every single day. We often want to know, why did revenue go up? Did it go down? Is there something else? These are all things that a human with expertise in the area needed to be able to do. Now we can begin to write down some of these things in…

AI assessment note: “It is early, and it is useful to draw from history”

Q What did you learn from your acquisition and how are you making this onboarding process? Founders ship faster on deal. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit deel.com slash sorcery. That's deel.com slash s-o-u-r-c-e-r-y.

A Our acquisition went pretty smoothly. It's a little bit different from Observe in that we were more tech, like, tech and talent rather than a running product. Observe is a running product. It's a business. Um, to me, the most important thing to remember if you are an acquired company is that you have to become one with your new home. You need to align yourself, um, with what your new home, in this case, snowflake wants. On the other hand, As the CEO of Snowflake, I have to recognize that what this startup, what Observe has created is magic. It's really hard to create products that are working well. People often underestimate it because, you know, we see so many successful companies, but to me, a working product is pure magic. Frank, my predecessor, used to say a working product or working startup is like a life force. You just can't create it. It's very, very special, and so we're going to try everything that we can do to keep that team together. Jeremy is going to report to me directly, and we're going to empower him to scale that business as rapidly as he can, benefiting from things like close access to Snowflake engineers, the scale of the platform. They no longer have to pay Snowflake for using Snowflake. I think things like that are going to be beneficial. They're trying to strike the right elements between Give them, give them that support, but also give them that indepen…

AI assessment note: “Jeremy is going to report to me directly, and we're going to empower him”

Q And one of your competitors recently raised, I think it was their Series Q might have been, I don't know, very late round. Rumors of IPOs coming around. How do you view your strategic positioning against someone fast moving like that?

A There's no question that we have to move fast. And, uh, We have had pretty good quarters, but bluntly, we should be thinking about, we should be asking ourselves why we are not growing a whole lot faster, because the opportunity is there. The hyperscalers, who are massive compared to us, often are showing us how. And so I think that is very much that competitive spirit in me, in Christian, our head of product, in Vivek, who runs engineering, or Mike, who runs sales. Ah, absolutely. I think we need to, ah, to do more faster. That's that sense of urgency and opportunity that I, um, that I do feel. On the other hand, there's, you know, in, with private companies, there is, like, selective metrics, um, not everything is subject to scrutiny the same way that a public company has scrutiny, but I feel very good about where Snowflake is as a company. When it comes to supporting enterprises, We were talking to the, you know, to the head of a really important financial services company right again in that room this morning, and he was saying being enterprise grade in everything that we do. Where, um, we provide for disaster recovery. We provide for excellent governance. We provide a whole slew of things that are needed to be truly enterprise ready. That's our heritage. We are very good at doing that. Do we need to combine that and be faster moving and seize the opportunity? 100%.

AI assessment note: “with private companies, there is, like, selective metrics... That's our heritage.”

Q And so given that those were mostly Nvidia, Meta, big, big name stocks, Alphabet, um, some people are pointing to the application layer, some of the categories that you just mentioned. Are there any categories within that that you think are underrated?

A I think there's, there's still an open question about things like the modes that application, traditional application providers have. I think the jury's out. I think they have absolutely a lot of value, but there is also going to be a lot of disruption for many applications as we know it. What happened in the first decade of the cloud computing revolution Is that things like enterprise SaaS software had a Cambrian explosion. There's just an application for every single niche that you can think of. And there is an amount of fatigue in the enterprise, um, men trying to manage several hundred applications, their own licensing models, and things like that. I think, um, even in the world of data, there was a very large explosion of different kinds of tools for every stage of the data life cycle. So at Snowflake, for example, absolutely, We want to be there for our customers at every stage of the data life cycle so that they don't have to stitch together lots of complicated, um, individual applications in order to get some job done. I think what AI does to the application space is very much something that is open. I think there's lots of opportunity and lots of disruption.

AI assessment note: “I think there's, there's still an open question about things like the modes”