Datadog at Goldman Sachs Conference: AI Strategies and Growth Insights

On Tuesday, 09 September 2025, Datadog Inc. (NASDAQ:DDOG) presented its strategic vision at the Goldman Sachs Communicopia + Technology Conference 2025. The company outlined its ambitious plans to enhance its platform with AI capabilities and expand its enterprise sales team. While Datadog sees significant growth opportunities, it also acknowledges the challenges posed by the evolving AI market.

Key Takeaways

• Datadog is integrating AI tools to enhance its platform and improve efficiency.
• The company is expanding its enterprise sales team to capture more of the cloud modernization market.
• Success in the AI native market is driven by Datadog’s ability to meet modern software needs.
• Datadog is focusing on long-term customer relationships to manage market volatility.
• New product developments include AI observability and database monitoring.

Financial Results

• SMB Sector: Stabilization observed, with a notable increase when AI-related growth is included. A rise in net retention suggests a balance between growth and cost optimization.
• Enterprise Sector: Steady growth continues, with a focus on priority projects, including AI-related initiatives.
• AI Native Sector: Significant growth due to reliance on Datadog’s platform for mission-critical operations.

Operational Updates

• AI Strategy:

- Integrating AI tools with 4,500 customers sending data from AI tools.

- Monitoring GPUs, CPUs, and LLMs to enhance service management.

- AI-enabling the platform to quickly diagnose problems.

• Go-to-Market Strategy:

- Expanding the enterprise sales team and geographic presence in India, Brazil, and the Middle East.

- Investing in sales and marketing to exploit significant market opportunities.

Future Outlook

• AI Opportunity: Datadog aims to follow workload trends and leverage its platform’s capabilities to serve modern software companies effectively.
• Lessons from Cloud Native: Focusing on long-term customer relationships and aligning SKUs with use cases to increase stickiness.
• AI Bubble Management: Utilizing a consumption-based model to monitor and optimize customer usage.

Q&A Highlights

• AI Native Customer Success: Customers choose Datadog for its cost efficiency and effectiveness in reducing time to remediation.
• AI Impact on Software: AI is transforming enterprise software interfaces, with successful transitions leading to greater success.

Readers are encouraged to refer to the full transcript for a comprehensive understanding of Datadog’s strategic insights and growth plans.

Full transcript - Goldman Sachs Communicopia + Technology Conference 2025:

David Obstler, CFO, Datadog: I understand what you’re saying. Yeah, I understand what you’re saying. Yeah, thanks.

Unidentified speaker: What a delight to host two companies from the great New York City.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: Headquartered in New York City, and my favorite outside of San Francisco ever. I think I spent most of my time outside of San Francisco in New York. I love New York and welcome David Obstler, the CFO of Datadog, which is based in New York.

MongoDB had Mongo based in New York City and Datadog.

David Obstler, CFO, Datadog: It’s very appropriate that we’re back to back. Dave is on our board.

Unidentified speaker: No way.

David Obstler, CFO, Datadog: A long time, Director of Datadog, and we learn a lot from each other. It’s a very appropriate pairing.

Unidentified speaker: Kindred spirits. Kindred spirits. Two great companies back to back. Welcome back to the Goldman Sachs conference here.

David Obstler, CFO, Datadog: Thank you. It’s great to be here again.

Unidentified speaker: Fourth year in a row we’re doing this fireside chat.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: I think we’ve done this at multiple ballrooms, whatnot.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: A delight to have you back. I keep asking you the same question. What is the vision for Datadog five years out? If we are to come back, Communicopia, I think it’ll be 2031. What does your company, Datadog, look like? Just as Dave was asked the same question about MongoDB, what does Datadog look like five years from now?

David Obstler, CFO, Datadog: Yeah, I think we want to look at our customer, which is sort of the production engineer, the reliability engineer, the DevOps. We want to be the platform they turn on in the morning and never turn off or perhaps never turn off. When you think about how the world’s moving, we’ll talk about it towards more and more complexity of applications, more and more migration. There are many more sort of use cases or breadth of use case that we can satisfy with that customer base. We’ve already, I think, had a strategy well articulated in our platform in metrics, traces, logs, observability, but anything that touches the function of that application when it comes to, and we’ll talk about a database, network, LLMs, service management, we want to own. We want to spread out our use cases to things like security or DevSecOps and sort of coding tools.

That’s the vision. That’s what Olivier, our Founder and CEO, and his partner, Alexis, have been doing relentlessly since the founding of the company and want to continue doing.

Unidentified speaker: How do you operationalize the vision? What are the things you’re doing to put this in action and help actualize the vision of the company?

David Obstler, CFO, Datadog: Yeah, that’s right. That’s where I come in. There are many, many types of product enhancements and go-to-market enhancements. I think we’re in a very good position given the size of our customer base and platform and the fact that we get real-time feedback from customers. We, as many of you know, are a consumption-based model with underlying subscriptions or credits. We actually can see what our clients are doing. The philosophy has been to look at what they’re doing in their day-to-day operations and have a list of things where we can enhance value or develop the platform and then get that feedback from customers. We’ve been, and I know it’s one of your questions, announcing various milestones, $50 million, $100 million, $750 million of parts of the platform that are going to be adopted.

What we do day to day is think about how important a use case is and can that be evolving from that $50 million to $750 million and beyond. That’s how we do it. It’s mainly from the customers.

Unidentified speaker: The compounding S curve. You have got a product.

There are disclosures for logs.

A whopping number a few years ago.

David Obstler, CFO, Datadog: Yeah. Yeah.

Unidentified speaker: I want to go back to the vision question a little bit.

You threw in LLMs, networking, et cetera. In the cloud world, it was easy to understand how that network topology and the infrastructure layer got to be much more complicated.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: was much more massive scale and how Datadog kind of rode that wave.

David Obstler, CFO, Datadog: Right.

Unidentified speaker: As you think about AI and what’s ahead, what is the relevance of Datadog’s core technology in an AI world?

David Obstler, CFO, Datadog: Yeah, and sort of stepping back, what we saw in history is as the world got containerized, Kubernetes, serverless, as it became impossible to monitor these applications using legacy observability platforms, that enhanced Datadog. We see that happening again when it comes to GPUs, LLMs. In terms of AI, there are a number of things we’re doing. I’ll start with our platform itself, our product. One is our goal through our integrations is to monitor wherever the workloads and data goes. It’s Datadog. We’re essentially developing integrations into the AI tools. We have 4,500 of our customers now sending us data from AI tools. We want to be able to monitor, and we can, GPUs and CPUs, and we want to refine that GPU. We also want to be able to monitor the LLMs in the application, and we announced our LLM monitoring product.

What we want to do is monitor all the content. That’s one part of it. We want to AI-enable our platform. We believe that to continue to be the leading observability platform, we have to inject AI into our platform, and we’ve been calling it blank bits. An example of that is our service management, where we’ve always had machine learning, we’ve always had Watchdog, we’ve always had analysis of correlations and what might be happening. We’re using our LLMs and outside LLMs and training them to get quicker in the diagnosis of problems and therefore be able to become more reliable and speed up the work of our clients. That’s a good example of a platform feature. We have the customer base, which we’ll talk about.

We’ve always been a company, because of the innovation, the R&D, that has been the choice of platform for what we used to call cloud natives, but now we’ve created a new segment called AI natives. They’re essentially cloud natives. If you look at some of the disclosure we’ve made, and we could talk about this further, we’ve been gaining quite a bit of traction in that market. That seems to be where a lot of investment is going. We want to monetize that in our customer base. It’s an accelerant, as you just heard from Mongo, as you’ve heard from a lot of companies. Lastly, what about internal to Datadog? What are we doing?

We’re trying to dog food our own uses, and we’re trying to use AI, whether it be coding tools or the service management, more proactively in order to accelerate our product development, as well as eventually we maybe become more efficient in the spending.

Unidentified speaker: Got it. Got it.

David Obstler, CFO, Datadog: Yeah, it was a long answer, but it’s a big topic.

Unidentified speaker: It’s a good one. That’s pretty technical for somebody with a finance background. I think I’ve mentioned this a couple of times before. Are you sure you’re the CFO or you’re the Chief Product Officer?

David Obstler, CFO, Datadog: I’m not. I look at all the great work being done by our engineers and product, and try to understand it.

Unidentified speaker: Thank you. You’ve done really well observing that.

Now, to dig into consumption trends.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: We talked about SMB improving at the margin, enterprise established coming out of Q2 results.

Can you just give us an update on the broader spending trends across these cohorts, enterprise versus SMB?

David Obstler, CFO, Datadog: Yeah. I think in SMB, when the bubble burst, as you all know, we had funding pullback. We had a change from growth at all costs to the combination of growth and efficiency. That hit the SMB. Now for us, because you have to have a cloud deployment, we’re not talking about what some of you might think of as SMB. It’s not your corner dry cleaners. Essentially, many of these companies have significant revenues and 500 to 1,000 employees. They had to change what they were doing and funding got constrained. We went through an adjustment there. What we saw in the last two or three quarters is stabilization. This is excluding the AI. If you add the AI in, you would see, because most of them are SMBs, as we define it, less than 1,000 employees, you’d see a material increase.

In the non-AI, what we’ve seen is things return a little more back to normal. In the last quarter, we saw a pickup of our net retention there, meaning what they’re doing is getting back to, maybe they’ve calibrated, they’ve optimized, and they’re getting back to the appropriate balance between growth and cost. We’ve seen that. In enterprise, this is where we have a very, very long opportunity, meaning if you look at the percentage of workloads that are in the cloud and then modernized, not lift and shift, but modernized, you see we got a long way to go. That might be in the 20% or 30%. There are many enterprises that are right at the beginning of this. What we’ve seen is a return to, I would say, the priority projects. Some of them are AI related.

We’ve seen steady growth and consolidation, meaning we’ve seen similar growth rates as we’ve had in previous quarters. We still have a careful environment, a balanced environment. What we’re trying to do there is expand our enterprise sales team. I think we got a little behind in that. Maybe we risk managed a little too much. There are a lot of geographies we can talk about. We’re trying through the combination of product innovation and go-to-market to accelerate that. We’re in a good place. We’re not in an ebullient place.

Unidentified speaker: Got it.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: That’s good to know. You’ve seen good growth from, actually tremendous growth from AI native to your point, which is not included in the SMB consumption.

Over the last 12 months or so, how do you think about the potential for sustained growth for Datadog in this cohort? Why is Datadog so well positioned for this AI cohort?

David Obstler, CFO, Datadog: Yeah, it’s a great question. We follow the workloads and we follow where revenues are being gotten. You can see a lot of these companies are publicly announcing their progress. They’re giving you revenues. They’re giving you funding rounds. We have a business here that has hundreds of customers, indicative of the demand environment. We have eight of the 10 largest companies by valuation in the cohort. We have, we said, over a dozen $1 million customers and maybe even more importantly, long term, over 80 $100,000 customers. The signs are there, like other companies are discussing that we’re attaching ourselves. Now, why? Datadog, when you, when these are, we can call them AI native, but what are they? They’re modern software companies whose whole business was invented in the last five years or so.

They have a modernized tech stack and their whole business is delivering through APIs and others to their clients. That makes the delivery of the product mission critical. Because Datadog has invested most of its dollars in servicing the modern side of this, the cloud side, the reliability side, the breadth side, and the speed side, it’s a perfect solution. We’ve always been the leader in the choice, I’d say, in cloud natives. If you want to call these cloud AI natives, it’s an extension of that.

Unidentified speaker: Mm-hmm.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: As you look at that cohort ahead, this question came to me midstream.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: What are the lessons learned from servicing the cloud native cohorts during the big cycle that we had?

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: How do you apply those learnings to monitoring the AI native cohorts?

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: What are some of the telltale signs you’re looking for as a CFO to make sure that you run a balanced business, not over-index too much?

David Obstler, CFO, Datadog: Definitely. No question. We learned a lot of lessons. We have pretty good transparency because we have the meter on it, its consumption. We can see the level of usage and the type of usage. I think what we learned in the cloud native.

Unidentified speaker: At one level, you could say there is an AI bubble happening in venture, like you had a cloud bubble happening in 2021.

David Obstler, CFO, Datadog: Yeah.

I think yes.

Unidentified speaker: We should be smarter now in this cycle.

David Obstler, CFO, Datadog: Definitely. I think you can see it’s a much smaller part of our customer base. Essentially, the impact of whatever may happen, for better or worse, positive or negative, is going to be smaller. You see a workload growth. What probably will happen will be, there’ll be some winners and losers. You’re going to have some consolidation. You’re going to have some companies that are really mission critical and their workloads are going to continue to grow. You’re going to see more AI activity in all applications. What we learned was we’re here for the long-time relationship with customers, meaning our application for the good part is frictionless. That doesn’t mean we can let there be no friction. Sometimes we have to be the friction. We see what’s coming in. We are proactive in helping the client use it. They may be sending us too many logs.

They may be sending us the wrong logs. What we’ve always done and learned, in the cloud native, it’s really important to have long-term relationships. We’re focusing on the length of contract. We’re focusing on initiating the increase of commitment where they can get a better price and what it means in the trade-off of commitment and size. We’re focusing on our own platform. I think we talked last night that when you think about logs, it’s not just logs. It’s what are you doing with the logs, which is why we’ve created flex logs, frozen logs, a number of different things to try to match up the use cases with the SKU. That doesn’t mean we’re cutting price. That means the intensity of the cloud use of that application is less than real time.

Therefore, what we’re going to try to do is instead of pricing, and we’ve already done it, sort of unilaterally, we’re going to try to match up on a gross margin basis the costs and the SKU price. That is creating, I would say, more stickiness. It’s also creating a broader market use cases and logs that are beyond real-time observability. Those are some of the things I think we learned in the bursting of the bubble that we’re applying in this generation. There may be more volatility, but we’re going to try to, in my seat as a CFO, try to manage that volatility in a more proactive way.

Unidentified speaker: Yeah, I know people try to sort of get at, oh, why did this large AI native customer not grow the business?

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: There are all kinds of conspiracies.

I want to flip that the other way and say.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: The biggest AI native customer, Datadog, what are you doing right for them? What can we learn from that success? Why could that not be a template for other AI natives that may be on the fence? You know, should we do it on our own?

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: Look at this big case study, the shining example.

David Obstler, CFO, Datadog: Yeah, I think that’s a very important lesson when you look at how the.

Unidentified speaker: The glass half full versus.

David Obstler, CFO, Datadog: The glass half full. Think about it. It’s a very good thing that all of these companies are choosing Datadog. They’re choosing Datadog because for their use case, it’s the best product. Their DevOps teams love it. If you try to take away their Datadog, they protest. It makes their job easier. The time and cost to remediation is dramatically reduced. We’ve been able to prove over the years and with this cohort that economically, it makes more sense to use the platform than to build it yourself. You have huge investments you have to do yourself. That’s why with so many of these cloud natives, we’ve been able to grow the business and why our gross retentions are so high. The vast, vast majority of customers choose to stay with Datadog and grow their use.

I think we have a whole team, business value team, that does nothing other than relentlessly prove this to customers. You can look at it both on the cost side, but you can also look at it on the revenue side. Having, and a lot of these, as you build companies, you have certain accidents or things happen. If that happens, you lose a lot of revenue. We’ve been able to prove that it’s a good decision, net-net, to use the Datadog platform.

Unidentified speaker: This is like value engineering, engineers that go in and say.

David Obstler, CFO, Datadog: Yep.

Unidentified speaker: Okay. This is what.

David Obstler, CFO, Datadog: There’s value, there’s prioritization, there’s cost, all of those things. The vast majority of our customers have chosen that way. I don’t know if we can get into the large customer if you’d like to and talk about that. I don’t know if that’s where you want to turn next. The largest, the most customers are not building a Datadog internally. We can’t tell what happens. We certainly don’t retain every customer. We have a very long track record of keeping upper 90% of customers. We think it makes sense for them to use the platform.

Unidentified speaker: David, did you know that I can vibe code my way into a Datadog competitor? I mean, I did not know that.

David Obstler, CFO, Datadog: Wow.

Unidentified speaker: I can’t, the problem is it doesn’t scale that well.

I mean, it does not integrate.

It does not have governance.

It does not have security.

It does not have authentication.

David Obstler, CFO, Datadog: Definitely.

Unidentified speaker: It is not a foldable.

David Obstler, CFO, Datadog: I think you just heard that. When I walked in, Dave was talking about that.

Unidentified speaker: Yeah.

David Obstler, CFO, Datadog: When you think about the difference between a consumer going into a model or chat and all the things that happen in the enterprise where these are your mission-critical applications, you have to balance uptime, putting new functionality in, security, privacy, speed, the platform being used by everybody. It’s not at all trivial, which is what’s made Datadog what it is.

Unidentified speaker: I want to get into some of the growth businesses.

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: It’s been amazing since you started disclosing.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: Logs, APM, those businesses have grown pretty massively.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: They’re approaching $1 billion in revenue.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: Can you talk about what’s going on in the APM market and logs?

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: I want to get into security just a little bit.

David Obstler, CFO, Datadog: Yeah, definitely. You have the observability where we repeat this a lot. We call it all these products, but our clients call it problem solving in the platform. What they are speaking loud and clear is they don’t want to go to different point solutions given, you know, the real-time nature of it. I think, as you just mentioned, we’ve done a really good job of creating a platform that covers metrics, traces, and logs well. We’ve been able to extend it into a number of the things that affect the application, network, database. Now, we’ve announced that these products are growing very fast. Synthetics and RUM, what does this mean? You’re taking it from the back of the infrastructure all the way out to the device, product analytics, things like that. In the platform itself, service management, we’ve been able to create additional SKUs that have become significant.

On top of that, you have some growth vectors that are tangential, somewhat related, and security is one of them. We have a lot of the data. We have a pretty good real estate of customers. We didn’t come from security. What we’ve been doing is investing in the three areas of security, which would be cloud SIEM, cloud security, which is posture management and vulnerability, and application security. I would say, in the DevSecOps world where they abut very closely, we can attach, and that happens a lot in cloud nativity. What we’re doing is moving to the next level, which is essentially, how can we use our infrastructure and our, for instance, logs and create a cloud SIEM product that is able to address the nature of compliance and other use cases besides observability, where we’ve been very successful. We’re starting to see success there.

I think we announced that security had gotten over $100 million, which is, you know, an achievement. We have some game plans in product, in marketing, in creating channel relationships, and expertise in sales teams to try to push that. I think we have a great opportunity in cloud SIEM, given where we already are in logs and some of the other things that have been happening with some of our competitors. Also, we have the AI, which we mentioned, the LLM and the GPU, and then service management. I want to address this as a kind of a combo of an observability platform, but extending it, because we generally have been a company that analyzes data, produces clues of where things might be wrong. We haven’t been a workflow company.

What we’re doing, I think we think AI accelerates our opportunity to reinvigorate, reinvest in this, and essentially go from what’s wrong to who’s going to fix it, and way out there may be auto-remediation. These are some of the areas we’re most excited about in sort of growing on top of the observability.

Unidentified speaker: That prompts the obvious question, service management.

David Obstler, CFO, Datadog: Uh-huh.

Unidentified speaker: Is that who you’re trying to, I’m not suggesting that you go up against them.

Have you uncovered a niche in the market that they’re not addressing so well that your product is naturally suited to address because of the adjacency, right?

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: What do you see in the ITSM market?

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: We had Marc Benioff from Salesforce also talk about we’re getting into the ITSM market, right?

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: What is Datadog?

David Obstler, CFO, Datadog: Yeah. You have to then go below that and figure out who is it. IT or, you know, when you call your corporate IT group, that’s not our customer base. What we’re doing is the whole thing’s platform is basically, we have a real-time use case that emphasizes speed. What we’re trying to do, I think you might have looked at Opsgenie and things like PagerDuty.

Unidentified speaker: Mm-hmm.

David Obstler, CFO, Datadog: We’re trying to do it for DevOps and security reliability engineers. I think there are, in this case, you have to look at who the end market is. I think ServiceNow obviously has done a fantastic job in a number of markets, but we’re not trying to boil the ocean. We’re trying to have this be tightly aligned with our platform to create more value to our customer base. I think in the end, if we’re successful, we’ll sit alone. Those customers will have ServiceNow for what they do, and they’ll have Datadog for what we do.

Unidentified speaker: Got it. Got it. Got it.

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: I want to talk about some of the newer products.

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: We did touch upon this a little bit.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: AI observability, LLM monitoring.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: Database monitoring. What do you see in the opportunity set, and what is your investment philosophy to nurture growth in these nascent markets?

David Obstler, CFO, Datadog: Yeah, definitely. When it comes to looking at sort of prioritization, since we put everything on a common platform and about 50% of our investment in R&D is platform, that is a huge birthright, meaning we’re more efficient than others in putting out new products because that’s sharing in a very large investment in platform. Some of the things that we’ve been able to do is, as in database, for instance, as the database, you just heard, you just heard from Dave and Mongo, as the database world and the data world has innovated, there’s more and more connectivity into the applications and more variety. In that case, it’s been really, you cover another database, your revenues increase.

Unidentified speaker: Mm-hmm.

David Obstler, CFO, Datadog: Because we need to see, our customers need to see everything that affects. I think database has been a really good opportunity for us. Take RAM.

Unidentified speaker: Particularly this MongoDB database, right? I mean, what’s that MongoDB thing?

David Obstler, CFO, Datadog: I don’t know what that is, but people are using it. I just heard that, you know, it can’t compare, that Postgres, I don’t know. I don’t know the database world. I know about monitoring it, but, you know, when you think about how this is evolving and this is the same thing as our other integrations, we need to be comprehensive. As it gets more complex, as customers have more choices, that’s when you need Datadog.

Unidentified speaker: I think at dinner last night, you made this point.

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: I just thought of it.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: 50% of the research and development dollars are for the platform.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: Everything is an extension of the platform. It’s so underappreciated because you can think of building an APM company and then another product that then you got to extend the breadth of the platform.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: When I first met Ali, it just blew my mind how he got the idea for this company in San Diego decades ago.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: I mean, the view back then when you founded the company, had this idea, was a wide spanning view.

David Obstler, CFO, Datadog: Right.

Unidentified speaker: I think the pieces are falling in place under that view.

David Obstler, CFO, Datadog: Yeah, it turned out that infrastructure was the ideal place.

Unidentified speaker: Yeah.

David Obstler, CFO, Datadog: To start because everybody needed ubiquity, you got a large canvas. Then, when you think of what others maybe didn’t do first, Ali thought of the underlying architecture and the sort of coding of data. If you sit in meetings with him, with our product meetings, you see that he is obsessed with UIs and customer activity. A lot of companies have a great product, but it’s so complex to use, and you can’t see how to use it. Every time Ali sees that it’s not very intuitive and native, that somebody can’t pick it up, he challenges. I think he also created a very, very customer-friendly UI with workflows in the platform that could attach really quickly. Those are some of the things when you get the platform that made Datadog.

Unidentified speaker: I don’t know if it was for me, when I first saw Datadog, it was 2011 or 2012, AWS re:Invent.

David Obstler, CFO, Datadog: Uh-huh.

Unidentified speaker: I went to a demo booth. I don’t know if it was Datadog.

David Obstler, CFO, Datadog: Uh-huh.

Unidentified speaker: I had a massive monitor with flashing signals all over the place.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: What is this?

It’s so animated, so expressive, and so full of details.

It’s Datadog.

David Obstler, CFO, Datadog: Datadog.

Unidentified speaker: That was my first product, Datadog.

David Obstler, CFO, Datadog: Yeah, that’s right.

Unidentified speaker: Almost 12 years ago. Subsequently, my other wake-up moment was 2023 Dash in San Francisco.

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: We’d love to have Dash in San Francisco.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: You launched a refreshed version of the logs product.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: It just blew my mind.

David Obstler, CFO, Datadog: Definitely.

Unidentified speaker: The live demo, the LLM monitoring is just, of course, Selena and my team went to the Dash conference in New York City.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: She said, "Dash, look at all the stuff that I picked up. I spoke to all these partners and these customers.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: Just a company that’s got a lot of buzz.

David Obstler, CFO, Datadog: I think when you think about it, you want to look just methodically at what’s going to affect the application. Of course, LLMs will be in applications. You can’t cover everything else and not cover the LLM.

The goal is to be comprehensive in a single unified platform.

Unidentified speaker: Yeah. Dave, what’s happening? By the way, at the five-minute mark, if anybody has questions, just raise your hand. We’ll get to you. Doing a pulse check. Okay. What’s happening on the GTM side? I know that.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: Last year, when you gave guidance for Calendar 2025, we had built in some expense buffer to wrap up the go-to-market engine.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: What is happening there? What is, I know you said you were a little bit behind in hiring, but how much of this is actually proactive? Should we read this as a sign that you’re actually, I always, I’m an old-school software guy.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: When companies ramp up hiring and sales, that is a bullish sign.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: When companies ramp up CapEx, that is a bullish sign.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: In software, what am I to make of your signal that you intend to step up your sales and marketing?

David Obstler, CFO, Datadog: Definitely, I think your old-timeness is right on. We have a reading of significant uncovered white space and believe that there’s a correlation between ramped quota capacity and top line. I think we, on the back end of COVID, got a little conservative. Some of it is we couldn’t travel. We couldn’t develop the international markets as well. We saw a lot of white space we weren’t covering. We have a lot of proof points. This might surprise you, but we had no one on the ground in India.

Unidentified speaker: Mm-hmm.

David Obstler, CFO, Datadog: Brazil when, you know, COVID ended. We were covering them centrally. I think what we learned is in looking at the white space and looking at the competitive environment, there were huge opportunities in a large number. I would say the Middle East would be an example that we just had nobody. We came to understand that we need the combo of centralized sort of SMB and commercial sales and marketing and feet on the ground. We’ve been developing those markets, and it’s paying off. We’re seeing great growth. I think, yes, you’re right. It is a bullish signal that we think we can get really good return from increased investment in sales and marketing.

Unidentified speaker: Is there any trends in the time to productivity?

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: Changes in how quickly people get productive?

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: Because Datadog is now institutionalized today.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: Versus two, three years ago, a rep joining the company today ought to be, it’s got to be easy.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: Not easy, but less complicated.

David Obstler, CFO, Datadog: Yeah, we definitely are focusing on enablement, but it still takes an enterprise, it still takes a year for a rep to get ramped. That is because they have to get educated, but then they have to make their champions, go and make their champions in companies. After that, since we are still somewhat land and expand, we have to get our landing spots and then grow them.

I think, you know, potentially we have a longer ramp, but a ramp that you can monitor along the way. I still think you should think about a year to ramp reps.

Unidentified speaker: Just to finish up here, any last question? It’s your last chance. Okay. Maybe, you know what, I’ll do it slightly differently. Do you have a question for me?

David Obstler, CFO, Datadog: Yeah. What do you think of the opportunity or risk factor of AI on, in one case, application or SaaS software, and in the other case, infrastructure software?

Unidentified speaker: Yeah. Infrastructure obviously more insulated because at the end of the day, it’s about compute, networking, storage, and bottlenecks.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: These are things that are homogeneous across tech cycles.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: As far as SaaS is concerned, I liken it to the web browser. In the late 1990s, the web browser became the front end for most things. Enterprise software lagged pretty badly.

David Obstler, CFO, Datadog: Uh-huh.

Unidentified speaker: Mark Benioff, who’s going to be speaking later today, had this idea that we need to put our web browser front end to the boring, drab world of enterprise software. That not only just became the UI for software, but it replaced the front end application layer, right?

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: One thing led to another.

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: The back end logic of how business does business does not change.

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: I think what we saw was a catalysis of the enterprise software industry, the web browser front end. Everybody said, Amazon, Netscape, all these companies are going to destroy enterprise software.

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: No, actually they catalyzed.

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: It was the birth of companies that changed up the user interaction model, the application code of the front end, and we had a 20 to 25-year run right now as a result.

When I look at AI, maybe I’m being completely wrongheaded about this.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: AI is the new UI.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: It is going to change the front end of the enterprise software industry, the application industry.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: I see a graceful world where you interact with the software through AI, whatever your prompt engine is, whether it’s a foundation model, X, Y, Z, du jour. People, I think, are always ultimately very curious.

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: When you enter a prompt, you get an answer back, and you want to find out more.

You want to dig in. I want to go to the source.

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: That transition from UI.

David Obstler, CFO, Datadog: Which is AI.

Unidentified speaker: Into the back end of software, the back end of software will also change.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: To accommodate the graceful transition from AI into the software, companies that make the transition graceful and are able to accommodate that business model aspect to them, I think one of the panelists on the VC panel yesterday said it best.

David Obstler, CFO, Datadog: Mm-hmm.

Unidentified speaker: I think Byron, he said some of the SaaS companies are trading at 5x multiple today, will go to 3x, and some will go to 10x.

David Obstler, CFO, Datadog: Yep. Yeah.

Unidentified speaker: That is what keeps me super excited.

There is going to be some massive transformation.

David Obstler, CFO, Datadog: Yeah.

Unidentified speaker: It’s not going to be the same, but there’s a lot of money to be made. I want to thank you once again for your partnership.

David Obstler, CFO, Datadog: Thank you.

Unidentified speaker: You’ve been tremendous. I really love these discussions.

David Obstler, CFO, Datadog: Yeah.

Thank you very much. Thanks for having us.

Unidentified speaker: Absolutely.

David Obstler, CFO, Datadog: Thank you.

Bye.

Unidentified speaker: Thanks.

David Obstler, CFO, Datadog: Thanks, everybody. Have you had?

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