EP 108: Olivier Pomel (CEO, Datadog) Shares Every Lesson From Scaling to $40B

33:47Yeah, I think it requires constant discipline and constant attention because it's very easy for a company to veer one side or the other. You know, to caricature, if you go sales driven, you'll do whatever you need to close the next deal. That's what's going to drive the roadmap. That's what's going to drive the economics and everything. whereas if you veer engineering driven you start with a solution you build this beautiful tower and then you know maybe you let the customers in but only if it doesn't detract from the the beautiful journey we're on and the destination we set what about it and i think for what we do in particular we can't have either of those we need to start with a customer we need to start with instead of starting with a solution instead of starting with the money we need to start with a problem like what's their problem what what do they have in their environment in their life that is horrible and how can we make it better how do we show value there that's the uh the core of what we need to focus everything on and it's uh it goes beyond what can we do for them today also which is well what can we do that's actually going to be great two or three or five years from now which means for that to be great five years from now we we need to be a great company five years from now, which means we need to have the economics, we need to reinvest, we need to build.

35:12So really everything has to be seen through the prism of, if we project ourselves five years from now with that customer, who is everything amazing for everyone? The manifestation of this within the company, I've heard there's some examples like engineering rotating through on support, maybe for a week, a year or something. I'm not sure if that's still the case. But are there things you've done from a cultural standpoint to enable this within the organization? Yeah, so we did actually for a long time, we had engineering rotate into support. We don't do it anymore because it was too many people running for the system.

35:51It was a bit too complex to run a scale. But the idea behind it was really to close that feedback loop. Like we were big fans of feedback loops. But to close the feedback loop between, hey, I had a great idea and I implemented a new product. and then seeing what it actually works in practice. And it turns out, like always, some genius ideas are actually amazing and some others actually not that great. And you only realize that after the fact. Everything, by the way, everything, I keep telling everyone who listened to that, but everything you find that is horrible in the world around you started as a genius idea.

36:28The intent was not to make everybody miserable. Your grow-to-market initially was bottoms up. I know you don't like the term product-led, but that seems to be one of the terms that's in vogue today. How did you make the decision to go about selling that way with, I guess, the alpha, the beta, and then from there? Initially, look, we had no sales team. And we were selling also to cloud companies. And cloud companies in 2010 were smaller, newer tech companies. So bottom-up motion was just completely natural. That was the only thing that would make sense for that. And that's what we started with.

37:06It turns out, as we scaled, and as the other parts of the market came to the cloud, like, you know, later on, enterprises, big enterprises started moving to the cloud, things like that. When that happened, bottom-ups was still mostly the way we went to market. And we've tried, you know, various ways of top-down also. the earlier thing we tried in TopDown for example was when we started raising money from big VC investors everybody was eager to make a lot of intros and get us in front of their best and brightest companies it never really worked great and the reason for that and the reason we still sell bottom up even in the enterprise is that we're the kind of product that inherently has to be the team's idea People need to want it.

37:56They need to fill a specific relationship to the product. The moment it's something that your boss's boss's boss passes down, it's suspect. So that's why all type of products with all type of users, they're much better bottom-up. And so then that sales motion, in the early days, it sounds like you all held off on hiring traditional VP of sales or salespeople for a while. Is that fair? Yes, yes. We wanted to figure out what the right way was to go to market. We didn't want to rebuild an enterprise Salesforce from the very beginning in the same exact way every other company had built them. Some of that might have been, we were just a bit naive and clueless.

38:45But if you fast forward to where we are today, it actually yielded better economics and a much tighter sales process in general. I would say, I don't know if I would recommend it to everyone to do exactly the same way. I think now you probably have a pretty good idea of how every single piece of software, whether that's for developers, cloud consumption, not consumption, everything can be sold. But at the time, at least it made a lot of sense and it paid dividends for us to do so. One of the things that in going bottom-up versus going more enterprise-oriented or outbound sales-oriented is you don't have the same number of dials that you can pull necessarily.

39:26Like most of our enterprise businesses, you hire more reps and that's the way you grow the business. What were the dials in the early days that you all thought about to actually generate more leads and make sure that you're able to scale? Well, so here's the thing. I mean, those dials still apply. So that's why I don't like product-like growth because it actually takes both product. and sales. The sales team still is going to get you in front of customers and there's still a coverage model and there's still a math of how many reps do you have and what part of the world do they cover and productive are there and all of that stuff.

40:03But the main difference is that you don't just talk to the CIO, the CTO, you actually talk to the people in the trenches who do the work. And they're the ones adopting and they're the ones growing the product and all of that stuff. earlier on very early um we were like many super early companies were inbound driven so we would produce marketing um in the form of events or blog posts and things like that and then we'd get people signing up on the product and then adopt it and they'd go i think that model for us and pretty much for everyone at some point plateaus like you reach a point where your natural reach with the content and the events and everything else is limited.

40:48And then you need to go further to actually find customers wherever they are. It's actually a pretty traumatic transformation to go from inbound to outbound. Most companies struggle with that because it's a different culture, different sales culture. There's different metrics, different everything that relate to that. So I remember it was a hard time when we did that. But again, to scale past a certain point, I think there's no other choice. About how big were you when you started layering on the outbound? I think we did that. Maybe we were 100 million revenue, something like that. So pretty late on a relative basis.

41:27In generating the content, a lot of technical companies will try to do rotations for engineers, produce one blog post a month or whatever. And inevitably it falls down the stack rank and then they're not happy with the product and that they're actually putting out there. And so you guys had a different, maybe tried that and then ultimately hired people specifically dedicated to producing content? Yes, we did. And the problem was it's actually hard to operationalize having engineers produce content. And what we found also is that it's not, it can be very, very unproductive use of people's time because people might be excited about writing.

42:12but they might not actually enjoy writing all that much. So you'll see people spending their day in front of the editor typing almost nothing and just because it's painful to stop writing. So we decided not to do that. We stopped doing that. So today we have a team of writers that are at the intersection of tech and journalism typically. We look for people with both experiences and they're the ones, they actually can't be marketers, they can't be non-technical, otherwise the content just doesn't come out right. And they're going to spend time also with internal teams. They're going to spend time interviewing people internally, they're going to spend time validating everything they put in there, they're going to spend time researching with the data and they're going to produce content there.

42:59We still have engineers on a conditional basis publish, but it's more of a nice to have if people are motivated, if they have something they want to say, if it's not too painful to them. But we don't rely on the team to do that too much otherwise. In building a go-to-market motion as a technical founder, was there something that was particularly counterintuitive to you that you learned along the way? I don't think there is anything that was so counterintuitive. I think, look, the way I see it, these are all systems. And your systems have feedback loops and they're instrumented in some ways. I think the thing that's the hardest to come to grips with as you build the sales systems is that while they are extremely well instrumented, everything that happens is captured in a CRM, all the interactions, you can produce numbers in just about anything.

43:57The numbers are pretty lumpy and pretty hard to interpret over short periods of time. so even though you can measure to uh with many decimals actually the productivity of your team and the conversion rates and all that that you actually need to let things play out for quite a while before you get an idea of what's working what's not working yeah the architecture point uh that your sales organization has an architecture similar to your engineering yes uh team or is building an architecture or is architected in some way it's a there's a lot of parallels between the to and making sure the systems don't have break points or single points of failure or anything yes and look it's very important to build the feedback loops everywhere uh so how do we know that what we're doing is working how do we know we're spending our time in the right place um if we did something horrible how will we know about it like it's uh it's hard and when you know i think you know one thing um we've done for example very early on is we had these uh very short-term contracts with customers and we still do that today you know we can buy our product month to month even if you buy on our if you're in a multi-year contract with dead dog uh you can use any of our product for you know a month if you want and then turn out of it uh and use another one instead um i think what it gives us is this very very very quick uh feedback on whether the product is good enough and valuable enough and that helps us improve very quickly it helps us get bad news uh in an in a way that's uh impossible to ignore because you know as you grow as a company uh you train yourself to ignore bad news um and and you have this opportunity right now to fix it the the flip side is or the um uh the alternative is you uh you sign everybody on a three-year contract um and if they stop using the product in month two you don't have to face the hard truth you know for another three years um and by then it's too late to actually fix your product you haven't you know put that into the uh into the feedback loop i've heard you describe yourself as a little bit of a control freak in the early days how did you learn to empower uh the the teams as you scaled you touched on it a little bit earlier but it maybe didn't come naturally yeah well i mean look i think it many founders can relate like typically when you start a company you might be a bit of a control freak happens i've seen it a number of times um i think for me it was a very new um and and good experience to learn to give space to people around me so i i knew how to do that already with my co-founder we had we knew each other we had worked together for a very long time that was not an issue but adding more people to the mix I think was more difficult um very early on like we had hired a um the head of product uh and I was butting heads with him all the time because you know he he was a control freak I was a control freak we're going on each other all the time and it I think it almost blew up in the first three months at which point we decided to hit reset um and that's actually how I learned to uh to give room and that's something i've kept doing after that as i've added i've added more people to my senior management team so people that report directly to me i find that i should be able to think as the people on my team as peers they're not people i manage if i have to manage them or their career it's probably not the right fit i should let them do their thing and we should talk about okay what's best for business what do we do next etc Maybe we can disagree on some things, but they are doing their job.

47:40Their peers, I trust them and have the space. I shouldn't be making decisions for them. I encourage everyone who's building a management team to try and think that way. I think it's liberating and I think it also helps you set the bar at the right level when you hire. Is that early product leader still with the company today? Yes, so he's retiring at the end of the year. This is Amit, is it? This is Amit, yes. Oh, wow. yeah so so so i mean for people that don't know amit was a quasi co-founder in the early days i've heard uh and he he a lot of stuff rolls through him it's not just chief product officer yeah he did he did a lot of the customer stuff for a lot of time too which for us is very related uh again the product is all about what the customer thinks of it and the problem we solve so we thought actually the two were very very related um and uh yes and so that that was a very productive relationship for the company and and that almost blew up completely blew up uh in a firework uh in about two months in wow that's that's amazing um you you still do things though to stay close to the customers despite uh or close to the business despite the empowerment i've heard there's some tactical things you'll do going through maybe still support tickets or reading employee reviews uh can you speak to the ways at which you stay close while still empowering people Yes, I think it's two things.

49:01One is data should flow up to management from everywhere. There shouldn't be any filtering. Of course, you'll have this filter views anyway. People will build retrospectives and reports and things like that. But you should be able to get data from every single layer of the organization. I see it as important to sample data from just every single part of the org because that's, at least to me, that's my contact with reality. Like, what does the fabric reality look like? When you read customer support issues, when you read transcripts of sales interactions, when you read, you know, what engineers are complaining about on the engineering team, what does it look like?

49:43What do they talk about? And does that actually agree with the numbers and the reports and the other things I see? Like, is it part of the same reality? I see that also as part of training the model. Like, you know, your machine, you keep seeing those things. What you see actually completely informs your perception of the world. So you can't just look at nicely polished, simplified, a little bit, you know, rose-tinted versions of the world that you might always see as an executive. So that's that. So data all the way up. On the way down, though, it's very important to go through the management team.

50:20So you can't just go and go find somebody on the sales team and tell them, no, no, you do this, you do that. You actually have to go through the management for that. Otherwise, when you don't do that, you completely, you notify, I mean, basically you disempower your management team. People know that they shouldn't listen to their managers. Instead, they should listen, they should wait for whoever, for the top to come and tell them something. But I think it's very important to have this asymmetry. You can get data from anywhere, but you can't act on anybody at any time. The other thing I found is that when you sample a lot of the data this way, everybody in the company starts caring about the details.

51:01So instead of looking up and trying to think, okay, so what do I need to show my boss? They start looking down and think, okay, so what's actually happening here? I better understand that. You know, the first time I, or people see an email from, you know, me or C-level or VP level about a very, very minute issue with a customer and asking a question about it. The first question people ask themselves is why, why is he or she looking at that? And then the second thing that comes after that is, okay, maybe I should probably know more about it than all these people up the chain. So let me look into that.

51:36And it creates this culture where people care a lot about what's actually happening. more so than what they're trying to pass up to the hierarchy. Is it right that you all only ever burned$25 million roughly? Yeah, definitely. And now you're approaching$3 billion run rate or something? It was still$2.5 billion, but yeah. $2.5 billion, so approaching. I can say that, maybe you can't. Outside of simply strong product market fit in the early days, what enabled that culture of cash conservation and efficiency in a way that maybe isn't obvious? Yeah, I mean, look, it's the culture of discipline in general.

52:20So first, the easiest way to spend a lot of money as a company is to have too many things in your sales process because it's tempting to, you know, you spend more on marketing, you spend more on sales. You can, there's always more things you can do, more people you can involve in your sales process. And so our approach there has been to be, to always understand before we add something to the sales process, what's actually load bearing and what's not in the sales process. So maybe we're going to try one thing. We'll try it small in a small fashion first, or we'll try it and then we'll remove it.

52:56Then we'll see, you know, this is actually make a difference. um the problem if you don't do that is you keep adding things you know typically in zero interest uh worlds uh the pressure is just to grow faster so of course you're going to spend more and you're going to you know weigh all the different things um and the problem you get at the end of that is that you have no idea what part of it you can remove or not and you're scared because look you the pressure is still to grow after that so you have to save money and you have to grow but you don't question who can remove, so it's a bad situation.

53:29So on our end, we're always very disciplined about deciding what to add, what not to add, and keeping those economics fairly straightforward. We've also been very disciplined about not doing bad deals. So when we look at commutative situations or customer situations, just because somebody else wants to do something that we think is stupid doesn't mean we shouldn't be doing it. and again if you look back at what I said earlier about solving problems for customers not just for today but for the long run this is the right thing if we want to be the best company and the best solution for our customers and make a big difference for them five years from now we need to keep investing in our product for those five years there's a cold hard math to that and I can come back to that and that means we shouldn't actually be doing bad deals that's part of it So that phrase, load-bearing, to make sure I understand the point, so you would keep the sales organizations more nimble and figure out what were the mission-critical functionalities within that and not layering with sales engineers or solution architects or whatever it is around the process because then it muddles what is actually mission-critical?

54:48Well, the sales engineers, of course, you're going to have sales engineers. Sure, of course. You're going to have all of those things, right? but then you can you can say uh hey uh we need for these products we need specialists that are going to sell them because they need to understand the product better so then you need to scale another organization on top of it and you have these more people that show up you know in the customer meetings maybe you're going to say hey um we we do a better job with customers when we can do an assessment of the business value which also do by the way but then the question is how much you scale that?

55:24Do you also end up having one more person that comes to the meetings with the customer every single time because they're here to assess the business value? So there's all these different things you can do and they all make sense individually. But if you're not disciplined about understanding what actually makes a difference when for which customer in which situation, you end up scaling all of those organizations at the same time. And you end up in situations such as, before I studied Datadog in my previous company, we tried to buy a service from i think it was sun at the time uh it was a server they we were just happy to order it online but you had to contact sales we contacted sales and then 10 people showed up uh i just wanted to buy and knew exactly what i wanted to buy and you know 10 people showed up uh and you had all these different functions and they produce a memo a lot you know where we're going as a company and all those things.

56:18None of that was required. All of that was, I'm sure, incredibly expensive for them. And is it just a byproduct of an organization that has grown without understanding what actually was needed or what made sense from a customer perspective? So we try to be very, very disciplined with all that. So pricing, in the early days of Datadog, you wanted to make it really easy for customers to get going, but there's this balance of what type of business you want to be, the premium product or maybe the cheaper solution out there. How did you think about where to fit on the pricing curve? Yeah, so there's two things.

56:56I mean, one is what kind of cycle do you want to have with your customers? Do you want a cycle where you charge for your product? every year your customers tell you why that's a lot of money and I need you to deliver value for that so here there's other things I want you to do for me and by the way the part of your product is not valuable enough so you need to fix it that's a good interaction because it means it pushes you up it pushes you to do more it pushes you to solve more problems it pushes you to be better that's the interaction we chose the alternative is to be a price disruptor which is you just select the customers on that and then the conversation with the customer is why it's cheap.

57:43If you remove this and this and this, it could be even cheaper. And that one pushes you down. I think in the short term it might work. Maybe some business models, things that are more consumer-y, I think it works when you can get mass adoption that way, for example. I think for what we do, it doesn't work in the long term. Because there's a there's a fairly cold map in terms of what it takes to build a company that could be successful in the wrong run. There's a like you need to be able to first of all you need to be able to sell your product. You know so say if you do something that's 10 times cheaper can you still actually pay a sales team to sell it?

58:30Or is it so cheap because the cost of sales is fairly fixed. Like you know you still talk to people you spend time et cetera et cetera. You market them, you have to find them. So how much of your revenue is going to go to sales as a result of that. And then as a consequence of it, how much do you still have to invest in product? And then where can you be, you know, two, three, five, 10 years down the road based on that investment you're going to make? So we chose the cycle of, hey, we're going to be pressed for value by customers and we're going to be on the hunt for delivering more value and doing more for them over time, as opposed to, you know, hiding at the bottom of a bill.

59:06somewhere hoping to be forgotten and having and shaving from it you know perpetually competition i mean this is an old adage i don't know if you agree with it but competition will typically come from some orthogonal area and it's it usually starts as a low cost option or a lower cost option and then it builds more full featured set over time how do you one do you agree with that but And two, how do you make sure that you don't get disrupted from adjacency with some lower price option? I mean, look, so first of all, we're always careful about what customers actually use, right? So the way to look at competition is not to read computer websites, because that will drive you crazy, I guarantee you that.

59:51Especially in a field like ours, you know, where there's a steady stream of new companies. And when we started that, there was also too many incumbents already. but the way to understand competition is through the eyes of the customers so what do they say what do they see what do they like what do they not like what do they think is viable what do they think is not viable so that's completely the prism to use to look at competition then when you look at disruption so you have to look at what's good disruption what's bad disruption so bad disruption is are they disruptive from a price perspective because they have a poor business model or they raise half a billion in zero interest and they're using that to subsidize their customers?

1:00:36Are they building a business where they can't actually invest and they're not going to be around in a few years? That's bad disruption. Typically, this one is a little bit painful because there's people out there offering deals. But you know, and we've seen that many times over, you know these are not going to be around for the long run and those deals have a short lifespan. The good disruption, like new technology, new modalities, new topologies for data, things like that, that we actually try to bring upon ourselves. Whenever we see something in the market or we can think of something, we try to read ourselves.

1:01:14An example of that is we released a new product at our conference last year, it's called FlexLogs, that makes log data basically in order to manage cheaper and we aim to do more and more of that over time for our customers. base uh i've i've i've heard uh datadogs culture uh described as low ego slash drama um how do you uh how do you action-wise that or or make sure that that remains the case yeah i think it's a so that's the stance of the company that's the stance for uh the management team my co-founder myself um i would say the the biggest thing we look for in p and people and the biggest threat of the company that leads into that is that uh we need to be you need to have a growth mindset we need to be humble whether that's in front of the customers or internally you know it means when we go meet with a customer we we're here to to learn about their problem we're not we're not here to teach them what to do things that we want to be taught um it doesn't come naturally mostly like you've been building something for a long time you have a lot of opinions about what works and or doesn't that you actually need to be but when you meet with a customer you need to be here to listen.

1:02:32So that's humility. The same thing works internally. When say you're a star engineer, you've been hired because you're super smart and you're super good at your job that's a given. You build something but somebody else on your team who's been here maybe a little longer or is also very good or just basically someone who's maybe a manager or the actor, whoever. He's telling you, no, no, actually, you know what? It's not. It's great, but we shouldn't be doing it that way. Let's try it again this other way. We want people who, when they are being told that, well, maybe they will explain, discuss, et cetera.

1:03:11And then they say, you know what? I'll do it. I'll try it again. As opposed to, oh, you know, this is bullshit. I know what I'm doing, you know, et cetera, et cetera, et cetera. And I've seen many, many smart people, very smart people, falling in the trap of being too aware of being very smart and reaching a plateau because of that because you know they're not open enough to the uh to you know trying again learning um not having necessarily that work mindset so when you're forced um to be humble when it was a customer and we're forced to be humble uh internally i think it it lends itself to a culture where you You don't take yourself too seriously.

1:03:50And relating to the low drama and low ego side of things. And I think it's a great... For future profiling an organization, I think it's great. Are those characteristics that you think you can assess in an interview and it's kind of innate to people? Or is it something that people can learn when they come in the doors? I think it's hard to assess in interviews. You get some signals from it. I think in interviews you understand you know how smart people are how well they understand their job that's good. When you look at their experience you get some sense of how they've progressed and how they've grown but the two things you are going to learn to see only when they're on the job is are they actually productive?

1:04:35You know some people are very smart, very good but not very productive and do they actually have the growth mindset? I would say early in career, growth mindset can be trained pretty well. So we do a lot of campus recruiting. And if you have the right organization, if you have the right managers, the right mechanisms and culture inside the company, I think you can really train that growth mindset. And as a result, we've been very successful with seeing people who joined the company as interns and who now run huge parts of the organization, just because they've always on the hunt for the next stage and they want to grow and you know they're happily uh are going to take the next problem make it disappear and then grow one level are there quantitative ways that you think about measuring the culture or how do you go about making sure that there's not drift from these principles that you you espouse it's hard uh i don't think we have any hard data on that um and you know one thing that's specific to us is that we've never written in doubt so we've never we don't have to have principles or seven values or any of that stuff.

1:05:45We've considered doing it a number of times. Maybe we'll do it in the future as we need to hire and onboard thousands of people every year. But so far we haven't done it. What we do instead is we do the traditional employee surveys. But one thing that we still do to this day is I will personally read every single comment in the employee service that we did twice a year. And they're a great way of just getting a sense, again, of the fabric of reality. Like, what are people thinking? What do they complain about? How do they speak about the organization? How do they, what's happening in there? And is there, do we see some change over time?

1:06:28Are there some things, you know, when you slice it by theme or geography or things like that, are there some things that we should be paying attention because, hey, it looks like in this part of the world, maybe people behave a little bit differently or think a little bit differently. I've heard you describe culture, and this is a good reminder, as who you hire, who you fire, and who you promote. Can you speak to that a little bit of how you think about it? Well, I mean, who we promote is people who have a real growth mindset, humble in front of the problem, low ego, low drama, but also who are doers and fixers.

1:07:02So you want people who are productive, are going to get things done and are good at fixing issues. Like the best people in organizations, you send them problems and order comes up. And in general, you can get a sense of who these are because it's like fluid dynamics. So work finds amazing people and avoids the others. So when you see the people lining up to get to work with certain people on the team, you know they just make problems disappear. I know seeking bad news is an important thing. We touched on it earlier, but how do you make sure that you're a, that you maintain a culture that seeks bad news?

1:07:44Well, I mean, again, you focus on the details. So anything that's aggregated is suspect, right? Because when you aggregate, you lose the color, or maybe you tone down some things. Maybe somebody doesn't want to look bad. And, you know, it's completely human, but they don't want to look bad. And they don't include something that reflects poorly on them, other teams, things like that. So that's why it's important to go back to the source, go back to the data and see what's actually happening in there. So that's number one. We discussed that already. The second one is having feedback looks that are actually painful to the organization.

1:08:16So they make it hard to ignore. So when you attach revenue to a new product, which is something we do, you get that very hard feedback when the product is not ready, when it's not good enough, when there's a product producing enough value for the customer, you get these revenues going down, churning, things like that. It's hard. It's impossible to ignore that. And as a result, you know, you sort of have to face reality and go for the bad news. Are there other things that force the bad news process that you guys have found? I mean, revenue is a great one. Are there other things you guys have done?

1:08:59I mean look every single step on the way we try always to figure out what's broken I don't have to look for it so I'm the CEO so usually when something arrives in front of me it's bad news but we try to make sure that every single layer of the ignition people understand when naturally people will always try to make things look better so say when you're a product manager when you go and get feedback from a customer if they tell you two compliments and one bad thing just signal two compliments uh the one thing they want to tell you is the bad thing and so that's the only thing you should pay attention to so again we try to apply that to pretty much every single part of the there are some exceptions of course i mean you don't want to be to be just negative about everything like you know and depending on the function and the culture that people can complain more or less um but you know in general whenever it comes to the business and customers it's very very important to focus on the bad news.

1:09:57The good news, you're going to, don't worry, you'll get them, you'll see customers ramp up, you'll see them use more, you'll see, that's going to be fine. The bad news, you really need some special attention. What have you learned about hiring executives that you would tell your younger self or someone that's early in their company journey? Well, so first of all, it's important, as I think we touched on that already, but hiring true partners is important. I think it gets you so much further when you can lean on an executive team and have people just run the show. And, you know, I keep joking that my goal is to grow the team so that, you know, I can be at the bar downstairs all day and nobody will notice.

1:10:41But at the end of the day, these are the people who need to run the company. So it's important to overinvest in having the right team around the table. So what I've heard that, I mean, I think this is intuitive, but the most talented people typically are looking for jobs. How have you gone about attracting those people? Now, I'm sure it's easier than it was once upon a time. But how do you think about getting people to want to join in the early days? In the early days, I think it depends on the functions. I think when you're small, you can attract engineers fairly easily, I would say. because engineers, I mean, and I'm an engineer, so I can completely relate, love the ability to shape everything from scratch, leave their mark, you know, have a lot of a say in the architecture.

1:11:29I would say on the go-to market side in sales, it's harder because the folks who are very good at it will likely go where, you know, the chance of them making a lot of money is higher. And that's typically not with an early stage startup with a lot of different, you know, hypothetical and things like that. So I think as you grow, you should expect to keep hiring and keep building as you keep attracting better and better people for your sales organizations. The two are a little bit different in that way. Look, at the end of the day, as you scale the organization, the thing that matters is to give people impact, both on the sales side and on the engineering side, is to give people impact.

1:12:13make sure that they can build things, they see the results, they understand how it impacts the business, and they understand how it impacts their own career. I think that's completely similar, even though the motivation structures between engineers and sales might differ a little bit otherwise. I heard you say that you sucked at fundraising in the early days. Do you think you actually got demonstrably better at it over time? did the business just get so much more obvious and the numbers just so much more inevitable that people gravitated to it? Well, we'll never know whether I got better at it or the business itself.

1:12:50It certainly got easier. Yes, it definitely got easier. But also, like everything else, it's a question of understanding who you're talking to and who the other side of that relationship works. What are investors looking for? what uh what world do they live in what what's the what data are they looking at like who do understand the various categories like some of the things um some of the words that were used i was using initially actually didn't work at all like i was i was very naive about what what the category were setting into it was very naive about the uh the state of the art you know what the other companies out there were doing um i think you have to understand all that and understand through which prism the investors are looking at you to make that case.

1:13:37And that's something I've had to learn with VC investors. And now something as a company, also we've had to learn with public investors that we're a public company. We need to understand what they're looking at, how they understand the company, why they would invest in Datadog versus the other many, many stocks they can invest in. And what their frame of reference is to understand where we're the same and where we're different. It sounds like those two things are fairly distinct and each individual investor might be distinct in their approach and how they're viewing things from an industry standpoint or whatever it is.

1:14:12Was there one or two insights other than just putting yourself in that investor's shoes or trying to understand the language that they were using that you would tell yourself 10 years ago? Well, I think that one's definitely important. The other one is to build relationships. and that's true that was true with the uh vc investors before us true with public investors now um investors like build trust over time um so the biggest advice i give for example when i invest in a in in new companies and people have are going through a hot deed or hot series a or something like that and this they say hey i've got what i need i don't need to talk to anybody else anymore because I've got two term sheets already and also I won't spend more time.

1:14:59What I usually tell them is, no, actually talk to a few more people now. You probably will not take money from anybody else right now. That's fine. But the people you talk to right now are going to start doing the work. They'll ramp up on your company. They'll get to know you and then they won't stop doing that work. And then by the time you need to raise a letter the next round, they'll have built conviction about your company and they'll be the ones who actually will make your next run happen. So it is worth it to build these relationships over time. Now that we're a public company, we do the same.

1:15:31The biggest misconception about an IPO is that it's an exit. It's actually not. It's a starting line, not a finish line. After that, you're on the treadmill, actually, and you need to deliver every quarter. When you go on a roadshow and you talk to all those public investors, what you're not doing is getting them to invest in the IPO. What you're doing is starting this relationship. so that maybe they will invest a bit now, maybe not. Usually they will, but they might sell right away. But really what you want is you want them to do all the work and track your company and build this confidence in what the management team is doing, what the company is doing, so that over time they will build and build and build a position and there'll be long-term investors in your company.

1:16:10I realize it's a deeply personal decision, but along the way, every successful company seemingly has people beating down their door trying to acquire the business, not speaking about any specific things, but along the way, as those situations potentially presented themselves, how did you think about the different constituencies, the decision to keep going versus not? Just at a high level, what would you recommend for founders? First of all, it's a personal decision usually. I think there's usually reasons to sell and not sell. And everybody is in a different personal situation. For us, the first time we got those

1:16:58opportunities, first of all, it was an occasion for us to understand that we had come along pretty far from the company nobody thought was going to be successful, nobody wanted to invest in. So it was good, in a way, to take stock of that. so that was positive second it was very important for me and my co-founder that we actually agreed on what needed to happen next so we spent quite a bit of time talking to each other about hey what do you think of these just to make sure that we don't end up in a situation where you know one is really deciding for the other and the other one resents you know and then you end up with a you know poor situation a few years down the road so we were very careful about doing that and the last thing is we tried to have a um a framework for deciding you know does it make sense to sell or not um and came down to two things for us uh one is when you don't sell um it means you think you have another 10x like can i can i grow that another 10x maybe probably okay but let's try that the same thing is understanding that when you pass on one of those opportunities it's at least a five-year commitment and the question there is okay so i believe it's a great business i believe i can scale it uh and in addition to that do i actually want to do that day to day like do i want to do that for at least another five years i think those are the two ways i mean again maybe these numbers are completely wrong i don't know but these are the two ways that we we try to have to frame things and and help you know decide because otherwise it's just nerve-wracking to try and decide um artificial intelligence we touched on it a little bit machine learning uh if there's a lot being said today about how it's going to change software development uh if you were an engineer 22 23 24 uh looking at this and you you hear different um considerations about if it's come for certain jobs or not like how would you work with the tooling around ai and try to future proof where you're headed in your career Yeah, I mean, first thing I would say is right now, if you're going to graduate in the next year or two, you really shouldn't skimp on, you know, matrix multiplications, because apparently, if you can multiply matrices, you can raise$100 million, you know, so that's good.

1:19:22But more seriously, I think, look, it's super important for everyone to lean to the tooling there. I think software development in general, land is said very, very well to being amplified, augmented, accelerated by AI. We're seeing that today, and I think we'll see a lot more of it in the future. So it's important to lean into the tooling and learn all of that. The way I think about it, by the way, is that it's yet another step in the curve that we've been riding of a continuous improvement of developer productivity. If you go back 40 or 50 years, you had people programming in machine language and punch cards.

1:20:08And then you had machine language and keyboards and screen. then you had a more advanced language on keyboard and screen then you had but you still had when you wanted to code you still had to go by a book at the library and then you know what there is in the book and that's it then you had the internet so you could learn about anything anytime then you had all of the libraries in the open source then you had SAS and cloud with the APIs you can use to do simple things so now when you look at the AI augmented development, I think that's another step on that curve. And I think every single step of the way, like these major steps, we improve productivity anywhere from 50 % to 10x.

1:20:50And I think we'll see something similar with AI. Are there particular things that you're paying attention to outside of the core benefits to Datadog within artificial intelligence? Well, I think to us, the opportunity we have at Datadog, by the way, is that it's a, on one hand, it drives a lot of cloud migration and consumption. AI does. Yes. And, you know, move to storing your data and using more of your data. Like all of that is like, I would say, plays into some of the existing ways that we've seen. But also, you know, if you follow the curve of productivity I just mentioned, a lot of the value actually is moving from writing the code to understanding it, to adapting it to the real world, to securing it, to understanding what happens when other people make changes to it.

1:21:42So actually it pulls more into our part of the world. So it creates, I would say, a very big opportunity for us to go after. It also so happens that the AI written code or AI in general makes the code less predictable. It used to be everything was very mathematically predictable. Now you end up with probabilistic executions and things like that. So I think there's going to be a lot of new areas to cover there. So on that point on where you all fit into it, just to make sure I understand. So the dev side of the house is increasingly going to spend just less time on the low levels of code writing.

1:22:26and it's going to become more dev and ops together in that way and actually understanding and executing. And so then a system that can understand what's being written and the different bugs and all that is going to be even more important. Yes, exactly. Right now, it still takes a lot of time to draft the code. You have to figure out what to type. You go on Stack Overflow. You spend more time. Then you fight with the compiler, all that stuff. I think a lot of that is going away. I think not to get from, okay, maybe I should do this to have a first version of it that I can plop in my code, I think can go pretty fast.

1:23:03But then the question is, does it actually do what I want? Or wait, somebody changed some other module. How does that impact what I do? I see those errors in production. What do they mean? Or, you know, it looks like there might be a secondary vulnerability here. How do I address that? So all of those things still have a lot more to do with the behavior of the code and the world around it than the code itself. And I think that's where a lot of the value is going to be moving forward. So I guess to wrap, New York. So you've been here now 25 years. You resisted moving out to the Bay Area. Was that actually asked of you in the early days of Datadog?

1:23:44that investors... Yeah, some investors hinted that it would be easier for us to raise money if we went to the Bay Area and also that there was more talent there for what we're doing, which is true. There was more talent there for what we're doing. How is Datadog a different business in your mind than it maybe would have been? I realize it's hard to totally know, but again, counterfactuals are always difficult. I would say, just looking at the companies we competed with, because when we started, they were like every single major VC fund had a champion. Like they had a company led by super smart people that were way more to market than we were.

1:24:25Like they had worked at the hyperscalers before or work in the assistance management field, which my co-founder and I hadn't. So these people had all the ingredients for being successful. VCs had already backed people in this monitoring, observability. Or they did shortly after. But, you know, there was always that. And we were a lot more successful than they were. And I think part of it is we were closer, further from the tech world, but closer to the real world. So less into the echo chamber of what kind of makes sense to the tech community right now. And more into the, what are the real problems that the real companies have about this?

1:25:07And, you know, who can we solve that? That's one thing. The second thing is, look, we were not nearly as hot as the other companies. So we could never think that we had it all figured out and we just needed to ship the product and the customers would come. We were always super scared that we were not going to get it right, that we're going to be out-executed, out-founded by just about anybody out there. and so we focus super hard on those early customers and you know all of the values we discussed earlier you know whether that's the efficiency of the business but also the humility in front of the customer all that you know really comes from that and i think that's a that's a risk i see today by the way when i see um young founders uh getting super super successful very very early in terms of the the fundraising traction i worry a lot that they're not going to be set up for success.

1:26:03I see that too with AI, for example, right now, where a lot of brand new companies raise amazing amounts of money without much to show initially. And the risk there is really to fail to understand that. Yeah, but at the end of the day, you're just here to solve somebody else's problem and your focus should be completely on that. Anything else, whatever anybody else is telling you about how great your business is doesn't mean anything because you haven't solved that problem for the customer yet. It seems like every successful company has at least one difficult fundraise. And I think one of my views is that if it comes earlier, it's better than coming later because it puts all those principles.

1:26:44You don't need to culturally reset all of that stuff along the way. So I guess to some extent, the early days being more difficult maybe was a benefit to the ultimate success. Yeah, and look, being efficient and disciplined is a good thing. In the long run, it works really, really well. So if I look back at the markets a few years ago, valuations were crazy. There were no interest rates, and everybody was spending, even on public markets, everybody was spending a ton to grow. After that, there's been quite a bit of contraction of the multiples. The companies had to be profitable all of a sudden in the public markets and in the private markets.

1:27:30And I think it really was very, very painful for many companies in our space as they had to turn on a dime and all of a sudden they were not able to invest anymore. In our case, it didn't change all that much. So we changed the dial a little bit. So we grew profitability a little bit further and faster than we would have otherwise. we slowed on a little bit of hiring just because we're not completely sure what the uh the future would look like uh but you know we were still able to keep investing you know 30 percent of revenue into r &d and that hasn't changed the posture of the company all that much i would say there's a lot of long-term benefits to building a company that is um you know disciplined and profitable uh your sales pitch to future founders uh that are thinking about picking a location a headquarters uh do you think all the things you said earlier about ability to focus on the customers and being removed from silicon valley does that still hold true in the world that there's more venture firms here and would you recommend new york for the next generation i think so too i think look there's definitely some trade-offs i think if you uh for certain types of talent there's still a lot more talent in the bay area than in new york like you'll have more choice that's a given on the flip side that tenant typically comes with a more employee turn so people change jobs more it's there's more places to go to for one thing but also it's more in the culture like it's a bit weird to stay a very long time you know in a place you know in the area whereas in new york it's uh more common uh like if people are happy with their jobs and treated well and working on interesting things that tend to stay longer and then if you go to europe which is the other side that's even even more so like people always say even longer um so for us you know we struck the right balance of uh um uh employee tenure and uh choice of talent by being in new york i think it's a great equation there too and by the way i'm a firm believer in long tenures um i think you learn from your mistakes um and you need these feedback loops i think we it's a it's been a theme yeah and the feedback loops take years in what you built um so if you are in a job for a year and a half uh you ship something six months in uh you when you leave you still think it was a genius idea uh you haven't seen the many ways in which it was not great or not perfect um and you haven't learned um so i compare that to having a uh you know a 10 miles experience of running a marathon you just have no idea.

1:30:08And I think when we hire, by the way, one thing we look at is, did people build longer successful tenure? Did people spend three, four, five, six years at a place? Because typically when you do that and you grow at the same time, that's when you actually accrue experience. People being promoted just by jumping around actually doesn't work that well in the long run. It might work a little bit in the short term, but in the long run, you don't actually experience the same way. Super interesting. Olivier, thanks for doing this. All right. Well, thank you very much. Yeah, this is great.

1:31:05Thank you.

1:31:35Thank you.