...That would be very similar to Datadog use in others. That would be monitoring the delivery of that application to its clients in the same ways, metrics, traces, and logs. So that is an activity metric based on a, a set of customers getting a lot of activity and growing, and it's a pretty broad set of customers, where Datadog is monitoring their production environments, just like we monitor all the other applications. So it's much more similar to what we do across the board. Does that make sense? Yeah. Yeah. No, yep. Yeah. I do know that you've stated publicly that these companies, you know, you kind of- Mm-hmm sift through the data and say Mm-hmm Okay, this is clearly an AI native company. Uh-huh. Tool company. We're gonna name them- Right. Exactly. Does it become more difficult or, I guess, visible to you? Mm-hmm -in the future as more companies have AI applications in production to truly see within the business model where the inference is coming from? Is that- Definitely. There's no question that this is a placeholder, and we haven't promised to give this forever. Basically, the money will be the biggest part of the money, and I can go to some other places we're investing, will be when we're monitoring LLMs within client applications. And it's tough to tell because we're not running those applications, we're monitoring it. So, you know, we will do our best over time to understand the effect of the injection of LLMs into the application, but we may not even know for sure. We're essentially trying, you know, trying to, you know, see. But I think that's where you have not just a set of tool providers, but you have our customer base, our 26,000-28,000 customers, using the functionality in the platform to monitor LLMs within applications. And that really hasn't happened yet because most of these mission-critical applications have not been put in production environments yet with the LLMs. It's more sort of testing. So I think we've been pretty clear to say, at that point, when you have inferencing and production, we may see that manifest itself mainly in our workloads, but it hasn't happened in a material way yet. Yeah. Yeah, no, that makes sense. Yeah. I do wanna press you on this a little bit. Yeah. It does seem like there's one, a positive. Mm-hmm. You're able to call out some sort of percentage- Yeah -for generative AI. But also somewhat of a predicament because it becomes less visible in the future. Mm-hmm. And so, you know, because you have this data point out there, I mean, it does feel like- Yeah ...the investor community is becoming accustomed to getting it. Mm-hmm. It does feel like it may be- Right -removed at some point or just talked about less frequently. Mm-hmm. How do you anticipate in the future, either quantitatively or qualitatively? Yeah -describing your, I guess, participation- Right in generative AI? Yeah, we hope to, you know, follow the... Everything we do is, don't forget, monitoring observability of what our clients do. So we hope that we get more data about what our clients are doing, and either qualitatively or qualitatively can express that. That may manifest itself in, in more, you know, hosts, more GPU hosts, more... It could also. We have a product in public beta, which is LLM Observability, and that, you know, is meant to basically have a module which allows our clients to look at the functionality and of, of the LLM models within an application. We may get signals from that that we can express. Right now, it's in beta, right? It's public beta. So that would be like we have with other product lines, if you go back to our most recent script, when we talked about the amount of ARR that we got from newer products, and we gave a number of examples. We talked about cloud cost, we talked about database, we talked about a number of the other products. It may be that as this develops further, we're able to have metrics like that in terms of modules of our platform that we can deliver. And, you know, particularly when, you know, we have those in GA for our customers. So when I think back to Datadog last year- Mm-hmm. Yeah ... one of the more exciting announcements that we thought was your integration with NVIDIA- Mm-hmm down to, I think it was the, the chipset, right? Mm-hmm. You kind of go straight in there. Yeah. Is that something... I mean, that definitely feels like it's a, you know, AI indication. Would that be, you know, I'm not saying give a metric today- Yeah ... but would you be able to have that type of visibility? Yeah with that type? Yeah. The metric we gave was, you know, over 2,000 customers are using our, those types of integrations. So we gave, if you look back to the script, we've been. It's a difficult thing because we are, and I think we maybe are doing it, you know, more than other companies. We're trying to give flavor without, you know, having that specific, "This is the use of this module." And that integration was, that comment on integration, both last time and this time, was really about what you just said, which is clients using our integrations, our deep integrations, and it's an activity monitor. So we gotta figure out exactly what metrics we're gonna use, but that's another type of metric that we've chosen to put out there to give evidence of traction. Okay. Okay. I'm gonna ask you one- Yeah One more question here, not, not on AI, a different question. And then, and then I wanted to open it up to the audience. Okay -to see if there's any questions out there. Yeah. We do have someone with a microphone. You know, please raise your hand, and we'll get the microphone over to you for the webcast. And okay, so next question before I open it up. Yeah. ... big deal activity. Mm-hmm. Right? Every quarter, you guys talk about- Mm-hmm. some pretty big deals. Yeah. 6-figure deals, 7-figure deals- Yeah. Eight-figure deals. I mean, how have these deals come to be? Mm-hmm. I know you guys are land and expand. Yeah. But is the shape of the deal? Mm-hmm -flow changing? Mm-hmm. I mean, are customers coming in bigger? Mm-hmm. Are they expanding larger? Is there a certain type of customer, you know, whether it's enterprise, mid-market, or certain vertical- Mm. Yeah that you're seeing better demand out there to drive the big deal out? Yeah. I would say it's still land and expand. It would be finding use cases and finding workloads. Landing, we land in the vast majority of cases, they're landing with not just infrastructure, but two of the pillars. That's the majority. So most of those deals have been expansion deals, where we are either covering certain of the pillars or certain business units. I would say they tend to reflect, as we've talked about over time, more consolidation as our products have gotten stronger, and not only the platform, but the individual products have gotten to parity or beyond. We've had a flow over a number of years of consolidation onto the platform, so we give some examples of that. So that may be something that's developed as we develop the products. We also have, sometimes, it's not the vast majority, we will land bigger because they're doing a rip and replace, and they're adopting us at the same time they're consolidating, and so you see some of those come in, but that's not the vast majority. So I would say the motion hasn't changed in that we do tend to land bottoms up. We do tend to develop use cases and then expand either in more pieces of the platform or more business units over time. It really, whether you call it an enterprise or a mid-market or an SMB, the clue is, what are they doing in the development of their digital businesses? And, you know, what decisions they're making to consolidate. And so we have examples in that of very large traditional enterprises, and cloud natives. I would say we've been clear over time that, traditional enterprises in some very traditional industries, automotive, manufacturing, you know, things like that, have been behind on their journey. When you see a lot of those examples, and we give the industry, you see that those are examples of those traditional industries catching up, and those are larger companies, so they tend to evolve to larger deals faster than, you know, smaller companies. Got it. Thank you. Yeah. Any questions from the audience? Please raise your hand, and we'll walk the microphone over to you. Questions? Oh, we got one question in the back. Thanks. So two questions. Yeah. One, first, from an AI perspective, do you get any feedback as to whether or not activity is picking up in terms of the tools that your, you know, your customers are using? Or is it sort of stabilized at this point with people just doing proof of concepts? And then the second is, you know, there's a very large theme over the last couple of weeks that the software market has matured significantly. It's now slow growth. Mm-hmm. If you're seeing signs of improvement, are you seeing signs from your traditional installed base that's actually coming back, or are you seeing potentially market share gains so that it's not necessarily a sign that the overall market's coming back, but that- Mm-hmm You're doing better? Yeah. So the first one, I think we said that we believe a lot of the initial work is being done in training, internal application, sandbox, and, you know, gave some examples of use of integrations, which means that there's activity. But it's too soon to comment on activity in this quarter versus that quarter. It's still, you know, fairly early on. In terms of what's driving the business, the business has basically been driven through a combination of expansion of use of the platform and additional pillars or modules. And the pillars or modules have been, for quite some time, market share gains. We know that because if you look and follow the public research or you look at the kind of ARR expansion that we've been getting every quarter, it's been larger than our competitors. That's been correlated to both the popularity of the platform, but also, as I mentioned, the investment we've been making in different pieces of it. So I think that those have been driving the business for quite some time. We've also had. I would say the thing that changed is we had maybe overexpansion in the bubble, and then optimization, which weighed. We said we think we're back more to normal. The new business has been relatively stable for this whole cycle, meaning there's enough new projects and logos that it's been relatively stable in terms of what we've been getting. You could argue that it hasn't gotten to an expanded level because whereas it's been out there, we haven't had, you know, the cessation of the weight of the, you know, Fed and the economics. We don't know, but it's been relatively stable. ... Maybe one more question from the audience, if there is one? David. Yeah. Wanted to kind of ask you a question related to that- Mm-hmm. on buying patterns from, Mm-hmm. From your customers out there, and it could be both for new or experienced. Yeah. You know, I know a lot of your customers- Yeah when I speak with them, they always tell me, "The contract's a year- Yeah But we're, we know we're gonna run out at some point. Right. There seems to be some sort of runway to run. Mm-hmm. Some sort of pattern there. Yeah. Whether it's 6 months, 9 months- Yeah whatever it may be. Have you, have you noticed that runoff time change over the years? Meaning, was it a much shorter time- Mm-hmm Call it, I don't know, 2018 to 2020? Yeah. Now it's longer runway today? I mean, how would you- Yeah -categorize that? Definitely. So, we tend to sell, sort of, on capacity planning that tends to be conservative. A lot of these are new applications, and because it's cloud and bursty... And we run our own company the same way, you generally don't buy for the peak. You buy, you know, under, and then you're willing, in capacity planning, to do some on demand, and that really hasn't changed. And you're right, most customers... And we don't force it. Like, we try to land at what the client wants. We're confident in expansion, so we don't force them or even incentivize them to overbuy. So we still have that motion of them staying short. When the net retention is lower, which it has been than at the peak, you would have the time on the y-axis to the ramping to the use of the capacity be slower, and that's purely a factor of, you know, the net retention and the growth. The net retention being the growth of the customer in using the platform this year compared to the previous period. So yes, it takes longer, but the overall motion of staying short and getting to a new commit hasn't changed. Okay. And I guess the follow-up there would be- Yeah -thinking about pricing trends in the market- Mm-hmm -versus the competition. Are you seeing roughly the same pricing trends out there? Mm-hmm. When I look at observability- Yeah Specifically, there's, you know, there's been some movement. Yeah. There's been some consolidation out there. Yeah. What are you seeing specifically that you could comment on to the pricing trend? Yeah. I think our pricing has been very stable. Sort of the optimization has been more a unit or consumption optimization, so our pricing is pretty stable. As our customers have grown, we've always priced based on discounts on volume and somewhat on term. And I think you're right, you said it. If a client... And for the most part, we have very high gross retentions, so the vast majority of our clients do feel this way, know that they're gonna be using Datadog long term. We have, as we talked about in Q4 and Q1, an extension of duration, a trend towards more three-year contracts, where they do get a little more of a price break, so. But it hasn't changed the overall weighted price, because we have the next generation of customers coming in, you know, smaller, and paying the higher unit price, because they're not either ramped yet in terms of overall units or duration. Okay. Okay. You are the CFO. Yeah. I'm gonna ask you two CFO-y questions. Okay. One on cash flow- Yep -and the other on stock-based compensation. Okay. So- Yeah ... one thing that's, you know, might be coming up more- Mm-hmm and more for you from an investor debate perspective. Yeah is cash taxes. Mm-hmm. You guys are profitable. Right. So how do we think about cash taxes this year, next year, or into the future? Yeah. So we said that this year we're not gonna be a significant cash taxpayer. We still have either enough stock-based comp or RSUs or NOLs. We gave out, you know, an effective tax rate, and, you know, what that can allow you to do is, we've had cash flow higher than, you know, than operating margins, and part of that is due to the fact that we don't pay cash taxes. So if you think about, just to use round numbers, the low twenties, 20, 21, and you think of the operating margins, you can see that, you know, I'll just use round number, 25 and 20, you know, that's basically 500 basis points, right? So you would have essentially, if you are gonna be a cash taxpayer, your ratio, all other things being equal, they may not be equal, we may have a different working flow, you're gonna have some, you know, somewhere between 300-500 basis points. We do pay some taxes. So we all... We said all along that we don't—we don't assume we're gonna pay, but it's likely that the cash flow margin and the OpEx margin, all other things being equal, start to compress a little more once you become a cash taxpayer. Yep. In terms of... Your second question was? Yeah, so stock, stock-based compensation. Stock-based comp, yeah. When I look at the model- Yeah ... sometimes I'm like, "Ooh, that's, that's a lot of stock-based comp. Mm-hmm. So, how do you think about stock-based compensation? Because I understand you guys- Definitely, yeah ... are R&D focused. Yeah. There is a component of that to drive- Yeah product differentiation. Yeah. How should we be thinking about stock comp? Yeah, I think we essentially never went crazy. So if you look at the amount of stock-based comp, we never went off the rails. We've always been more like 2%-3% dilution in stock comp, and that's really what we think about. We understand that, you know, over time, that, you know, we need to sort of bring that down, but the most important thing is to stick within that dilution, as well as to hire and retain the right people for growth. Awesome. How we think about it. Thank you. We're all out of time. Thanks a lot. Thank you much. Thank you, everybody. Thanks. Thanks a lot. Thanks for having us. Thanks. Thank you.