01:05:14 路 John Coogan, Sridhar Ramaswamy
[01:05:14] S1: Yeah. [01:05:15] S8: Are incredibly well versed now in our products and in AI as a whole because we created products that could work for them. Mhmm. And having an effective go to market motion is the real strength of Snowflake. Again, to make this super concrete, the number of, use cases these are new basically within customers, that our account executives won, went up by some 75%, year on year. That's the power of sort of using AI to get work done faster. And, that is a tradition that will that that will continue. What we have added on focus that comes from a product first person like me. AI in sort of a generic way or about worry about things like what, you know, what can it do. But I think sometimes what we forget is if you have a well built system that uses, like, the latest it's actually an incredible delight. All kinds of information that you would want. I was at a conference recently. Every piece of information that I wanted to know about a customer that I was having a conversation with, I would look up even live if I didn't know that. I would do it in front of them and show them the power of Snowflake's AI. A big part of our success over the past couple of years has been internalizing this. AI is a different way to think about product and product delivery, and the companies that are going to succeed are the ones that truly internalize that. That there is a big chasm between how we did it with web pages and clicking on things to these agentic flows that can truly solve problems.
01:06:51 路 John Coogan, Sridhar Ramaswamy
[01:06:51] S1: Then how is the sales the role of the sales rep changing, the sales associate changing? Are you looking for any different skills or are you doubling down on what worked in the pre AgenTik AI era? [01:07:10] S8: First of all, a lot more familiarity with Snowflake is a must. [01:07:15] S1: Sure. [01:07:15] S8: Because these folks now have access to products that show off what Snowflake is about. Yeah. I expect every sales rep to have co work on their phone and be able to show off the actual impact of having a product like that with pretty access to information to each and every one of our customers. When it comes to our solution engineers, these are the technical presales people. Used to be that we'd have six demos total for all of Snowflake, and maybe they would do a little bit of customization and say, hey, here's what Snowflake can do. Now pretty much all of them are capable of creating a custom demo tailor made for a specific customer in a vertical, in a way that makes sense to them, that will really illustrate the power of Snowflake. It's that kind of empathy that they can use the technology that we create to drive. I would say it's changed in a really, really big way because a lot more possible, but the bar is also a lot higher in terms of what you're expected to bring to the table. [01:08:14] S1: Can you walk me through the partnership with Amazon Web Services? I I I'm sure you compete in some categories, but how did this come together? What does it mean for the future of your business?
01:08:14 路 John Coogan, Sridhar Ramaswamy
[01:08:14] S1: Can you walk me through the partnership with Amazon Web Services? I I I'm sure you compete in some categories, but how did this come together? What does it mean for the future of your business? [01:08:29] S8: Yeah. We work with the hyperscalers. AWS is the biggest partner. Yeah. And, you know, we work with them on a number of different levels. We work on product integration. [01:08:40] S1: Sure. [01:08:41] S8: You know, buy a lot of capacity from them, a lot of GPUs that our inference team runs runs models on. But where we really shine is in joint go to market. AWS is an incredibly customer first company. And if a customer says, hey. I want AWS plus Snowflake, they lean into it. They bring us. And we really focus on how do we solve problems jointly, for customers. And there's a deep, deep relationship both at the account level going all the way up to the CEO level that ensures that problems that come up in practice get solved very quickly, it's it's the kind of partnership that one only dreams of. It's incredibly effective in practice.
01:08:41 路 Sridhar Ramaswamy, Jordi Hays, S5
[01:08:41] S8: You know, buy a lot of capacity from them, a lot of GPUs that our inference team runs runs models on. But where we really shine is in joint go to market. AWS is an incredibly customer first company. And if a customer says, hey. I want AWS plus Snowflake, they lean into it. They bring us. And we really focus on how do we solve problems jointly, for customers. And there's a deep, deep relationship both at the account level going all the way up to the CEO level that ensures that problems that come up in practice get solved very quickly, it's it's the kind of partnership that one only dreams of. It's incredibly effective in practice. [01:09:24] S0: What's been your what's been your strategy for trying to predict AI progress? Because we have people on the show every single day, somebody from a lab, somebody that's an investor, customers of the labs, things like that. Everyone has a different opinion. You have to weight them differently based on their incentives. But you're running a massive company that's leveraging these tools, but at the same time, you wanna understand what the capability will be one year out, two years out, and it feels harder than ever to actually be able to predict that. [01:09:59] S8: I think this is a is a really good question and one that to deal with. I don't think the software industry as a whole has internalized that this precious commodity that we all loved creating by hand, which [01:10:15] S5: is
01:10:15 路 Sridhar Ramaswamy
[01:10:15] S8: software, the cost of creating new software is going to keep going down. I tell people that the best analogy that I can give for them is to go back to, let's say, the 2 thousands when the cost of creating and distributing new content truly dropped precipitously. And you have to work through what is the implication of something like this. For example, I think simply getting deployed into an enterprise and being part of a workflow there is no longer guarantee that things will going to things are going to keep continuing. Because switching is also easier, I I would say that's the first thing. Every every company that's in the world of creating software as a big part of their business needs to think through what is the durable value that they are creating. I think it's a really hard question to internalize, and so we spend a lot of time just thinking about it. The second one, and this is this gets to the heart of your question, and I honestly just have a which is that this is a bad time to be making two and three year plans. Any time things are getting better or worse by 30% every month, all the human ability to predict these things, which are exponential in nature, is, is, you know, it just doesn't it doesn't really work. I joke to people that at this, point in time, we should treat coding agents the same way we treat traffic. Any person is always going to go get, look at Google Maps first before they go somewhere because it's an all seeing agents are sort of becoming like that when it comes to when it comes to software. And the more you have that open mentality that more things might be possible with a new model release than was possible before, the more you'll be pleasantly surprised and you'll be ready to take advantage of it. And so I stress that childlike quality in figuring out what is possible. Obviously, you know, there are nuances to how do you put in work in such a way that even if the model got better, you'll still be able to take advantage of what you have done before. There are practical problems like that. But the biggest thing that I ask for is that open mindedness to what is possible today because a lot different from what was possible, say, a month ago.
01:12:35 路 John Coogan, Sridhar Ramaswamy
[01:12:35] S1: Are you positioning Snowflake as a company that's in the token path or in the token stream? I don't know if you've heard this phrase that's sort of new coinage for a position in the AI value chain. And it feels like you're firmly in token stream, in the token path. But I'm wondering about what you think about that category. Is that narrowing you? Is that valuable to communicate to customers and investors? What do you think of the phrase like in the token path? [01:13:13] S8: It's a useful way to think about how value is going to get created. Mhmm. Remember, back in the web era, we talked about, you know, number of visits, number of unique visitors. [01:13:24] S1: Mhmm.