Dev Ittycheria - The Database Evolution - [Invest Like the Best, EP.373]
14 May 2024 · 71 min
MongoDB CEO Dev Ittycheria discusses three major tech waves—internet, cloud, and AI—and how value accrues at the bottom of the stack. He shares lessons from AT&T Bell Labs and founding BladeLogic, and explains why databases must stay relevant as AI reshapes infrastructure.
Chapters
I know firsthand how complex the tech stack is for asset management firms, and seemingly every new tool and data source makes the problem even worse, adding more complexity, more headcount, and more risk. Ridgeline offers a better way forward, one unified platform that automates away the complexity across portfolio accounting, reconciliation, reporting, trading, compliance, and more, all at scale. Ridgeline is revolutionizing investment management, helping ambitious firms scale faster, Operate smarter and stay ahead of the curve. See what Ridgeline can unlock for your firm. Schedule a demo at ridgeline.ai. Hello and welcome everyone. I'm Patrick O'Shaughnessy and this is Invest Like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. Invest Like the Best is part of the Colossus family of podcasts, and you can access all our podcasts, including edited transcripts, Show notes, and other resources to keep learning at joincolossus.com.
Patrick O'Shaughnessy is the CEO of Positive Sum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of Positive Sum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of Positive Sum may maintain positions in the securities discussed in this podcast. To learn more, visit psum.vc.
My guest today is Dave Ittycheria. Dave is the CEO of MongoDB, the developer data platform with tens of thousands of customers in 100 different countries. He joined the company as CEO in 2014, taking it public in 2017, and now approaching a decade of leading MongoDB to become a go-to choice for the most sophisticated organizations around the world. We discuss Dave's philosophy for constructing an exceptional enterprise sales organization, why he feels a leader must be incredibly judgmental to drive excellence, and how he plans to guide MongoDB through another technological transition. Please enjoy this great conversation with Dave Ittycheria. So we were just talking about what it's like to live through technology transitions. And often I talk about this with investors from the perspective of what opportunities does this unlock that weren't there before? and lots of investors have made fortunes around some big platform change or something. But I'd love to focus on it from the perspective of a CEO and operator who's running a business and has run other businesses through other technology changes and transitions. And just begin by having you riff on this experience. We're going through a huge one maybe right now. Everyone's trying to figure it out. So what's it like from the trenches?
Obviously, the transition we're talking about now is this transition to AI and what it means. Obviously, when OpenAI released ChatGPT, Kind of made AI feel real for people because all of a sudden you can use general common English language to engage with a computer and give you answers and generate content that never happened before. So it kind of made things feel much more real where before AI was the purview of machine learning and engineers and data scientists. I've learned a couple lessons because I've been through a number of these. I would say I've been through 3 transitions, the move to the internet in the mid to late '90s, Obviously cloud and mobile about a decade ago. And now obviously we're going through the AI transition. A couple lessons learned is one is value always accrues first at the bottom layer of the stack. Think about telephony or the internet. In March of 2000, Cisco was the world's most valuable company. A lot of people thought they were a linchpin of building out the broadband internet and everyone wanted high-speed internet access. But March 2000 is also when that bubble burst and people looked back and said, was Cisco really valued fairly when it was valued like, I think like 300 times PE multiple, which doesn't make obviously a lot of sense. So the obvious question is, now people look at Nvidia and saying, is Nvidia really the Cisco of 2000? Or some people are asking, is Nvidia the Google of 2003? Even though they've accrued a lot of value, they're on the cusp of being the seminal company For the next 10, 15 years? I don't know the answer to that question, but one thing, Nvidia's not trading at 300 times their PE multiple. There's obviously tons of demand of compute. And one thing we do know is that the more compute you have, the bigger breakthroughs you can have in these AI models. So one is the value is definitely first accruing at the bottom layer of the stack. But I do think, and that's where the I is going in the ROI equation, but the returns will come in through the apps that customers see in terms of whether you deliver great customer experiences, whether you drive a lot of cost out of your business through automation, or whether you either create new business models or disrupt existing business models with the use of AI. So I think that's on the come. The analogy I use with my team is the iPhone App Store. When it first came out, it came out a year after the iPhone was released. The first set of apps were incredibly trivial. You may remember the flashlight app. You may remember stupid apps like iBeer where you could simulate drinking a beer from your phone. Why people would build those apps was still not clear to me, but they were very simplistic and trivial. But then all of a sudden, when people really viewed the iPhone as an important computing device and people were running businesses from their phone, or consumers were really having amazing experiences, you had things like Uber and Airbnb and enterprises building iPhone apps. I can essentially, when I'm not in front of my computer, I can use my phone to do work, which is pretty profound when you think about where we've come. So I think the same thing's gonna happen in the AI world where we're gonna go from these simple chatbots that give you answers to questions and tools that help you summarize and research information to doing things far more profound, you know, leveraging real-time data to really make smart decisions about how you're running your business.
What is the hardest part about running a business that has obviously existing product, existing customers that was built not on top of AI or with AI for a long time and facing down one of these transitions. This is sort of like the innovator's dilemma question, I guess. How does it feel to you right now running a very big business and watching this thing unfold?
Obviously, it can be both exciting and scary. There's some degree of, is this an opportunity and a threat? In some ways it can be both. And I think what obviously we're working on is trying to really understand, for us, our primary customer is the developer and how does the developer workflow change in a world of AI. I'm not one to believe that you don't need more developers because all of a sudden developer productivity grows 10x. There's no development team right now that doesn't have a backlog of things they wanna do. And I think if you look at every generation technology transition from the mainframe to client-server to the internet to cloud and mobile, the cost of building apps went dramatically down. So one, you had far more apps and a lot more data. And I think with AI, you're gonna see a stepfold increase in developer productivity, which means that you'll see that many more applications. Consequently, I think we're gonna be a beneficiary of that. But that being said, how do we position ourselves to be a winner? We think we have a flexible platform. We think we have a highly scalable performing platform. We see thousands of startups building AI apps already on MongoDB. So to me, that's a good crystal ball into the future in terms of where large enterprises are going. But it's still very, very early days. Then the question is, How much of the workload do we need to own ourselves versus where do we need to partner? For example, when we launched our cloud business, this was in 2016, year before we went public. A lot of people thought we were crazy. We were the first infrastructure service that was launched across the hyperscalers. And a lot of people thought, wait, you're gonna partner and compete with like Amazon, Azure, and GCP? They said they're gonna eat you for lunch. And what they didn't fully appreciate was that The product market fit for MongoDB was really strong, but people didn't really wanna be in the business of provisioning, configuring, and managing MongoDB. They wanted to be in the business of building apps on MongoDB that transformed their business. And that business, when we went public in 2017, was 2% of revenue. Now it's 68% of revenue. So we really built that business as a public company. We obviously saw a big, big opportunity as a big driver of our growth. When I joined the company in 2014, we were doing about $30 million revenue. Now we're close to a $2 billion run rate business. So that's an example where we saw an opportunity and we really doubled down with this technology transition to cloud, the way people were consuming infrastructure as a service and felt we had a big opportunity.
I think probably people listening, maybe I put myself even in this category, take for granted that a major part of the world's technology today lives on top of databases. I don't think anyone really, if you think about like any system, it's a database, and an interface and a couple other things. The database is a common theme across basically every digital system. And I doubt many people have stopped to think like, wait a minute, what is a database? Who runs that? Is that Oracle? Is that something else? Like, what is the history of this? And I'd love you to offer your perspective on just the importance of a database. You run a database business, the role that it plays, why there should be more than one of them, why different kinds of databases help us accomplish different things. This is like a fundamental building block of the world's technology. And obviously Mongo is one of the few examples of a very modern database company. A lot of them are very old that has succeeded. And so I'd just love to hear you describe how and why that happened.
Just at a very basic level, if you go to any website, whether it's a shopping website or travel website, it's all about the data. So imagine going to a shopping website and there being no data. It'd be completely useless. Same with a travel website. So when you think about what a development team has to do, about 70% of their time is spent working with data. How do I present the right information or the right data at the right time to the right user with a relevant context? And so working with data takes an enormous amount of effort for a developer. So a database plays an important role for how people think about building and constructing applications because it's so much about the data. And one of the challenges in the database business is that if you don't have developer adoption, don't have a business. So when I joined MongoDB, one of the knocks on MongoDB was there's been a whole generation of modern databases that have tried to be the next Oracle or the potentially the Oracle killer, but they've all failed, whether they're XML databases, in-memory databases, graph databases. A lot of my friends said, why do you think MongoDB is gonna be the winner? And when I thought about this problem, one of the things that got me excited about MongoDB when I joined was that the developer adoption of MongoDB was very high because what developers were really excited by was that the way All other databases made you work with data was in a tabular format. A database is— think about it as really like an Excel spreadsheet on steroids, and everything is organized on rows and columns. What the founders of MongoDB did was they came up with this novel approach of organizing data in documents. And the reason that that was novel was that it really aligned to the way developers think and code. So all of a sudden, I didn't have to go through this cognitive load of translating what a product looked like into data sitting in a bunch of tables, or what a customer looked like, and then decomposing that customer into a bunch of data sitting across different tables, whether it's name, location, order history, et cetera. And so if you can keep all that information in the context of one document, all of a sudden it's much more natural and intuitive to work with that data. And that's why MongoDB's developer adoption really took off. And it, and we truly, we are the most popular modern database in the world. So that's a reason why databases are so important. So when you think about an application, whether it's a gaming application you're using at home, whether it's a mobile app you're using on your phone, whether it's an enterprise app you're using on your computer, there's a database behind that application. That's the persistent data store that stores that information. And you could argue, I mean, the joke we make is every web app is basically an HTML wrapper or doing a CRUD function on a database. Databases are incredibly important and they're also very sticky. I don't think I'm telling any lies when I say Oracle's not exactly the most liked vendor in the world, but there's still tons of Oracle databases around because it's such a sticky application and it's very hard to move applications once they've been built on a database from one database to another.
If you think about the most exciting version of MongoDB in 2040 or something like that, like this deep into the future, what adjacencies do you think where you are today allows you to bleed into over that kind of long-term time horizon? I think you're 10 years in now at Mongo. So a similar period of time, let's say, in the future, what would get you the most excited about how a company like yours can help developers and others enable yet more cool things to build?
2040 is a long time away, so it almost feels, especially with— in this world of AI, it seems like 3 months is a long time. Who the hell knows? I would say our whole goal, our whole strategy is to really actually get the database out of the way of the developer so that they could really focus on building great applications, embedding really great logic to enable people to do wonderful things. And so the problem with existing databases is that it takes such a tax in figuring out how do you work with data that so much time and effort is spent by developers working around the constraints of the existing database. Our goal is to remove those constraints so they can just focus on building great business logic. Obviously, with AI and all the reasoning capabilities that come with AI, the power of these applications will be far greater than what even we see today. And how the transformative impact of what it'll do to businesses, I think, is to be determined. If I knew all the answers, probably not be talking to you right now. I do think you will need an online data persistent store. One of the things that's become clear with these large language models is the switching costs from going from one model to another model is actually quite low. Because you can go from OpenAI to Anthropic to Llama fairly easily and start engaging with it. Now if those LLMs start embedding memory, where now they have a history of what Patrick has asked, maybe history of all of Patrick's activities, all of a sudden, if that foundational model has a history which is stored in some data persistence store, all of a sudden, the switching costs now become greater because you don't wanna lose all that history. So that's an example where, like, databases will play an increasingly important role As people start using AI, but leveraging also all the history of what you've done, what actions you've taken, who you kind of communicated with, et cetera.
You're one of a very rare breed. Maybe it's you and Slootman who are active and a few others that you could name that have founded, led, been the CEO of multiple different large technology companies across different periods of time. And so it makes me very curious about the sort of formative experiences for you as a founder, as an operator, as a CEO, going all the way back to however far back you want to go. I'm just curious if you think about your timeline and try to bring to mind the most formative experiences that you went through that have led to where you are today and how you think about the world. I'd love to hear about a few of those, and you can begin with whichever one you think makes the most sense.
Well, first of all, it's very nice of you to compare me to Frank. Frank, I think, is on a very different league. I have a lot of respect for him. He's just recently made the decision to retire, which was a little surprising, but his track record is second to none. With regards to the lessons I've learned, one of the big lessons I've learned is that to drive excellence, you need to be incredibly judgmental. And most people, when push comes to shove, are afraid to make the decisions they need to make to be truly successful. They're not willing to hold people accountable that need to be held accountable. They're not willing to be extreme about the product decisions that need to be made. the way products are positioned, where they're priced, and they're not also willing to be extreme about the go-to-market decisions. And what I find is most people fold with the pressure to make hard decisions. And I think that's why there's a lot of very average and mediocre companies out there. And I think really confronting problems directly and dealing with them directly, most people are social animals. Most people don't want to have a painful conversation. Most people don't wanna point out the flaws and what people are doing. And so in many cases, you have what have been these very passive-aggressive meetings. Everyone nods politely, but in the back of their mind, they said, this is probably not gonna work. We work really hard to create a culture where we can be intellectually honest about what's working and what's not working, have fierce conversations about what to do or what not to do, who's performing, who's not performing, and then really focus on executing really well. I wouldn't say we're perfect. There's many times when we also made lots of mistakes. But that to me is one big thing. The second thing I've learned is in the B2B business, I find a lot of founders and CEOs focus a lot on the product side of the house, which makes sense because they typically are technical founders and they're very, very focused around like, if I build a great product, they will come. But the reality is that, and part of the way I grew up was that I grew up early in my career when the best technology didn't always win. You had large vendors like IBM and HP and others who had so much account control that even if you had a better mousetrap, the customer would always pick the safe decision, which was to go with the large, the large organization. And so I realized that not only do you have to build a great product, but you also have to build a ferocious go-to-market organization. And in those days, it was all about sales. But now go-to-market has become much more sophisticated with sales and PLG and so on and so forth. But to me, the magic happens when you can marry a great product with a great go-to-market organization. And that's where you can really differentiate yourself in the industry. And for example, at BladeLogic, my last company, we had such a great sales force that I think about 35 people out of that sales organization became CROs of seminal software companies in our industry. I don't think another company's ever had that kind of track record. And so as much thought as we put into our product and how we position our products, and I'm not saying product's not important. In fact, it's very important. You don't have business, you're gonna have a great product, but that's necessary but not sufficient. In building a B2B business, you need to be just as thoughtful about how you go to market.
What is the mark of an exceptional enterprise sales organization? If you were evaluating 20 of them, not Mongo's but others, is it just idiosyncratic and it depends on each company, or are there things that you would say, no, this means good, this means great, this means bad?
I would say a couple of things. One, obviously it starts with a leader and in terms of how they've designed and architected the sales force. One sign of how good a sales force is, is broad-based performance. You can always have one person who's knocking it out of the park, but you don't want the 80/20 rule where 20% of the reps are killing it, 80% are not, because obviously that doesn't create a great culture and a great environment. So you want to create an environment where people are performing well. So that's an output. So then what are the inputs to drive that output? So to me, the best organizations are very good at recruiting. They're very good at recruiting hungry people who are very smart. And, and who really wanna make a mark. The second thing they're really good at is developing those people. Just because you recruit someone doesn't mean that they're gonna be great. How do you develop them? Not just on product skills, but how to prosecute a deal, how to qualify an opportunity, how to assess where you are in the decision process and the sales process, and what potential risks there are in closing that deal, how to forecast well. One of the things in a high-growth business is your revenue forecast or your bookings forecast is a proxy for your expense forecast. So if you don't forecast well, you can burn through a lot of cash very, very quickly. So those are hallmarks to me of a great sales organization. And then obviously consistency in terms of execution. They're not like a yo-yo. One quarter they're great, one quarter they're not. They consistently deliver on their numbers. So if you have those attributes, then that means you're doing something special. And it becomes even harder in a high-growth business because not only are you trying to make the number, but you're planning for where the business is gonna be 2, 3 quarters out. So you're trying to recruit people, Because you have to assume roughly a 6-month ramp for someone to become productive. So how do you think about territory planning? How are you making sure that the new people who join the organization are set up for success and the old guys or gals don't have all the best accounts so that new people are kind of starving for good accounts? There's a whole process around making sure that you're setting your team up for success. How do you think about, like, one of the things we do is like sell division. So once you get to a certain number of reps per manager, you divide and promote or hire another manager. And so on and so forth. And how do you do that? And who's the right manager to lead that organization, etc., are all things that we spend a lot of time on.
What have you learned? And this is a selfish question from just current experience looking at some enterprise companies that have naturally very long sales cycles just based on the nature of the customer and the buyer and how they work. It's going to be hard to change that. What have you learned about sales cycles, especially if they're longer ones, and how to think about and manage those things? Especially when the juice is worth the squeeze. It's millions of dollars per customer or something like that. Yeah. What have you learned about that kind of motion that's not just a demo and a sale?
I hate deals where it's just a very long sales cycle because there's always a chance of something going wrong. But if you think about any sales process, any sales process is essentially designed to address 3 core questions. Why does the customer want to do anything? I.e., what pain or problem do they have? that's gonna force them to take action. So that's with the discovery part of the sales process. You try and discover what pain or problem customers have that are relevant to what you can solve for. The second phase of that is why MongoDB? Why is MongoDB the best choice to solve that pain relative to all the alternatives and substitutes available? And then the third part of the sales process is why now? Because you could do the first 2 things, but the customer can easily kick the can down the road. And in many cases, that's the struggle most salespeople have is not that they lose a deal, but the customer never makes a decision. Can you create or manufacture, or is there a compelling event you can use to force a customer or induce a customer to make a decision sooner than later? So those 3 questions, I don't know how you can forecast a deal if you don't have answers to those 3 questions. So that's essentially how our sales process is broken down. Then there's certain interim steps in the sales process that tell you Are you on track to kind of getting a deal? Have you met with the economic buyer? Have you qualified how much budget's available? Have you qualified even that this is a priority for them? And because you're not just competing with your own competitor, you're competing with other vendors in other spaces for budget dollars. And so how do you know, is this problem that you're solving for as important as another problem that another vendor might be trying to address? And then obviously, what is the decision criteria? One rule of thumb we have is you should never be answering an RFP. Because invariably, if you're getting an RFP that you've never worked on before, some other vendor has written the RFP. So what that means is you have to set the table on the decision criteria. How is a customer gonna make a decision? What features or capabilities are they gonna weigh, and how are they gonna weight them relative to other things they can consider for them to make a decision? Have you educated the customer and built what we call champions who will understand the value of MongoDB and understand why for their own business, MongoDB is the best choice. And then building a champion. A champion we define as someone who's selling for you when you've left the building. Obviously, someone who's a change agent has power and influence in an organization and is really selling for you after you're not there. There's a big difference what we call between champions and coaches. Coaches want to see you win, but they're not gonna take either any personal risk themselves, or they just don't have the credibility or juice to kind of influence a decision. But they can be helpful to kind of give you some insight. or radar into what's happening in the account. But ultimately there's a champion for every deal that are closed. Sometimes you may not know who your champion is, but there's someone who's advocating for you when you're no longer in the room or advocating frankly for someone else. And you've gotta make sure your champion is more powerful than your enemy's champion. And that's all part of the sales process.
The champion idea reminds me of the first thing you said, which is that most people don't want to make hard decisions and confront trade-offs. And it makes me wonder what your first experience with this was from a personal standpoint that made you aware of or suited to or better wired to be decisive, have judgment, make decisions, make trade-offs.
I started my career at AT&T in Bell Labs, and then I moved into the business side. There's some very talented people there, and this is the old AT&T, not the AT&T of today, but there's some very talented people there. But I saw a lot of passive-aggressive behavior. And I saw there'd be a meeting and the senior person would essentially advocate for a decision. Everyone would nod politely. There wouldn't be any fierce debate, but then people leave the room and, you know, you could see people's eyes rolling saying, that's never gonna work. And to me, I view passive-aggressiveness as a form of duplicity because you have to create a culture where people are free to say what they think constructively about a particular idea or a particular decision. Because I always believe all of us are smarter than any one of us. And one of our core values at MongoDB is intellectual honesty, because I abhor passive-aggressive behaviors. That was one thing that I learned not to do. The second thing was when I founded BladeLogic, I got my first round of capital 5 days before 9/11. So 9/11 happened, the bubble burst. So it was a pretty tough time to start a business. So I had only $6 million wired to me. We were essentially trying to build a business. We were using a direct sales force. It was a pretty tricky time to build a business from scratch. And ultimately we raised $29 million, of which $7 million was still in the bank when we filed our S-1. So we were pretty efficient in how we used our capital. And that was a forcing function saying I didn't have time, the luxury of being patient with people who aren't working out. And one of the lessons I've seen, and I've also been an investor for a little bit, is that sometimes raising too much capital breeds bad behavior. Because it takes the pressure off. When I had very little capital, if something wasn't working out, it wasn't like, hey Joe, sorry, it's not working out. I'm going to put you on this special project. I know you're a good guy, but it's— the answer was, Joe, it's not working out. It's better for you and for us that we have this hard conversation now because I just can't afford for this not to work. And you treat the person with respect, but you move on. And so that builds muscles in terms of dealing with problems directly, not kicking the can down the road. And so many management teams kick the can down the road. If you ask anyone, Did you ever fire someone too quickly or too late? 99.9% of the time, they'll say they fired people too late. Why? Because they introduced hope into the process. And we still do that even at MongoDB. People say, oh, give that person more time. He or she just, you know, needs more time to get a sense of how we do things. And invariably, the answer was staring you in the face, but you just didn't wanna acknowledge it. And so that was also another lesson I learned is deal with problems head on and quickly. And at BladeLogic, I went through multiple rounds of leaders. And not that I was purposely looking to change leaders, but leaders can come and go because they're good for a certain stage of growth, but then they tap out. Even at MongoDB, the leadership team I inherited is no longer here. When a business scales, not everyone scales at the same rate. One of the things I've learned in life is that if you see a problem and don't act on it, that problem is no longer that person, that thing, that problem is you. If you have the authority to solve that problem, you're not doing it, then you're the problem. I always feel like whenever I see something bad, if I don't act on it, then I'm actually accepting mediocrity, or I'm accepting poor performance. And that's contrary to everything that we're trying to do. And in some ways, you're penalizing all the good people who are working really hard because you're accepting mediocre performance from the other person, and they're actually penalizing all the good people who have crammed the constraints. Or the limitations of this other person.
One of the ideas of yours that I like best when I was reviewing kind of your history and your thinking was this idea that people perform to the level that you inspect, not that you expect. I love that idea. Can you just like explain that philosophy and the mechanism of how you put it into practice?
The short answer is that if grown adults were supposed to do what we asked them to do, you wouldn't need that many leaders or managers. You know, you would have Theoretically, one leader and a bunch of individual contributors. But the reality is that human nature doesn't operate that way, and you need people who can challenge and push you. And when people know that there's a high degree of inspection, there was a joke at BladeLogic was that BladeLogic is a place where there's a lot of sunshine because there's no place to hide because we constantly inspect what's going on. And when people know that their performance will be inspected, that there'll be constant review of what's going well and what's not going well, which is healthy. It's not mean that the person's bad, but sometimes they're running into an issue. Sometimes that issue is bigger than they can solve. It elevates up and saying, hey, we gotta figure out a way to respond to this issue because this person has it. We're gonna see this with other people. That just creates a very healthy dynamic, and it also creates a bias to action. So people who thrive in those kind of environments love it because saying, hey, when there's problems, this company really cares and wants to solve them. But it starts from really understanding what's going on and deeply inspecting what people are doing relative to the goals of the next Yeah, it's a beautiful idea and I wonder if it ever gets exhausting.
Does it ever tire you out to constantly have to inspect every aspect of something going on, or are you wired to just enjoy that and do that well?
Well, to be clear, at a certain scale, I can't be involved in every meeting or every decision. There comes another approach, but at the face level, it is exhausting, right? This is one of the reasons why people don't want to do it is that It takes energy to say, Patrick, what's going on? This project is not tracking. What are you doing? What's breaking down? And really having a very, frankly, a heart-to-heart talk about why is this project not tracking? And most people have a very superficial conversation. You'll tell me, Dave, it's okay. This is just a temporary setback. We're all good. And if you don't really ask the next set of questions, it's very easy to assume, oh, Patrick's got this. And then 3 months later, the project fails. And so it does take energy and effort. And I think that's one of the reasons why people don't like doing that. With regards to as the business scales, one of my other axioms is that bad news travels very slowly up the organization, but very quickly down the organization. So imagine a situation where a sales rep's in front of a customer. Customer says, I'm gonna throw you out. I'm really unhappy about the quality of service I'm getting, blah, blah, blah. The rep tells their manager, oh my God, we have a problem with Acme Company. And then it slowly moves up the organization. In a typical organization, I may hear, Dave, we're having a little problem with Acme Company, but we're all over it. And if I operate in that way, I'm saying, okay, no big deal. They're on top of it. And then a month or two later, we found out that Acme Company churned. My philosophy is different, is that if I hear bad news, I immediately start digging in. And invariably, and because I know when I hear bad news, I know 2 things. One, I'm the last to know. And 2, it's Far worse than what people tell me because the filtration process of sending bad news up the organization dulls all the sharp edges of that bad information. So a holy crap moment with a customer, with a rep is now, hey, there's a small issue with Acme Company. Now, we don't have that culture here at MongoDB. I'm just describing what a typical organization goes through. And that's why so many people get caught flat-footed when they get surprised by some bad news because they always assume that things were far better than they were. So our culture is the opposite where, and obviously I can't be in every meeting or every decision. So I do sampling whenever I see some bad news. Even today, I sent one of our leaders feedback on one of his people because I had a very mediocre experience of saying, if this person's coming up and showing up to me in a very mediocre way, not very well prepared, nothing really innovative or creative in what they were doing, how are they showing up to everyone else in the organization? And so that generated a Slack message from me to the leader saying, hey, I'm really concerned about this person. And so I'm always assuming that if I see something bad, it's far worse. And if I don't do anything about it, no one else will.
In addition to this, I think for sure the average company is low on inspection. Like that's the default inertia mode or something. In addition to that difference where Mongo is much more on the high on the inspection spectrum or something, where else do you feel like Mongo is the most different from the sort of like average company? That's intentional on your part?
We are building and selling a very technical product, and there's obviously other companies who have very technical products. What I would say is we've had to deal with the open source dimension, and then we've also had to deal with like building a traditional enterprise software. Well, now it's a subscription software delivery model and then a cloud model. So I would say one of the challenges I worry about in our business is that we are like a multi-product multichannel business. Yes, we're $2 billion in size, but there's a lot of $2 billion companies who have one core product and one core channel. So how we think about like organizing, doing capital allocation across the different product sets as well as the different channels is something that we spend a lot of time and energy on. And my worry constantly is, are we overcomplexifying the business? I think there's value in simplicity. So always trying to figure out, do we really need to add in any channel? So for example, our go-to-market channel, We have a direct high-end sales force. We have a mid-market sales force. We have a self-serve channel, and then we have a partner channel. All of those organizations play an important role. We also have expanded our customer success functionality. And so our customer success people, because you're selling the cloud service, play an important role in understanding and assessing customer health. Then they have some upsell opportunities as well when they see opportunities that the customer could take advantage of with MongoDB. It's a fairly complex go-to-market. I'm not necessarily saying it's great that we have it so complex, but it's just a virtue of— we're going after a very large market and a one-dimensional channel model wouldn't work for us because how big our market is.
You are an interesting breed as well because you've done lots of investing. You led an early round in Datadog. You've made lots of really good investments. You're on a bunch of boards. I'm curious, the investor in you, how that bleeds into thinking about capital allocation within Mongo. You mentioned that maybe because of the complexity, there's more opportunity or more requirement for capital allocation thinking? What is your framework for thinking about allocating capital inside the business?
I mean, it's all about where do you get the best returns? I will just step back and say, being on boards and being an investor really helped me appreciate being in, in an investor's shoes when they're coming to my board meetings. Because it's very easy for management to get frustrated with investors, but then you really appreciate the pressures investors have in terms of they're under the gun for their LPs and so on and so forth. And it's easy to say, But it's really hard to understand until you live in their shoes, where you've been in a partner meeting and you're doing a portfolio review and you're seeing why some companies are being successful and why they're not. One of the interesting lessons I've learned at being an investor is there's an inverse correlation between work and outcomes. Your best performing companies, you show up, kind of eat the donuts and leave because they're doing so well. And where you're doing a lot of work, you're helping the management team rebuild the business, maybe helping them hire people, that may be the companies that are struggling. So it's a very weird dynamic. At BladeLogic, I used to go to my investors, I never really hear from you that much. And they go, Dave, that's a good thing because if you heard from us a lot, that means you'll be having serious problems. And it took me a while to appreciate that. But I would say back to your question around capital allocation, we take an orientation around like what's generating the return. So I've been old enough where I've seen good markets and bad markets. So obviously for the last 10 years until '22, Now with the benefit of hindsight, everyone realized that was a really good market. But for us, because we had seen bad markets, we never really spent money like drunken sailors. Just to put things in perspective, when we went public, we were trailing $100 million in revenue and negative 38% operating margins. Our numbers weren't exactly like super compelling, but as a public company last year, we did 16% operating margins. And I said, we're now approaching a $2 billion run rate business. We've shown almost 55% plus operating margin improvement while growing the business very, very quickly. So our capital allocation process is all about where do we get the best returns, having good discipline about investing here and not investing, divesting on certain investments when they're not working out, and just constantly asking ourselves what's working, what's not working. And are we perfect? By no means, but we try and be very disciplined about how we run the business.
Can you explain your philosophy of recruiting? It sounds like that is a key thing that you've always focused on in your businesses, and I noted this at Mongo too. What do you think is the most important part of how you think about getting the right people into the business? Anything that you've done that you feel is especially impactful?
I think one of the things about recruiting, most people make the common mistake of just focusing on what the person's background experience is, where they work, what skills they had. And maybe like what successes that they can talk about. I think a big part of recruiting is trying to figure out what makes a person tick. What is it about them? What is it about their upbringing? What drives them? What motivates them in terms of who they are and where they wanna go and what they wanna be? And I think if you don't really understand that underlying psyche of the person, how do you know what you're really getting? It's one thing to say like, hey, do you have experience building product? Do you have experience selling enterprise software? But how do you assess someone's values? Do you believe in the value of hard work? How do you measure grit? One of your common guests that I love made a statement that I completely agree with, was Jeremy Giffen, who talked about that the only enduring edge in life is psychological, as human nature doesn't change. That was like words outta my mouth. How you manage grit, how you manage your ego. Are you comfortable with low status? Are you comfortable being unconventional? Can you delay gratification? Do you have long-term orientation? Those are keys to being really successful, but it's so hard to do because it's so contrary to human nature. So how do you like find someone who can really do those things and what drives them to do those things? I've heard some amazing stories about people. I ask them the question, what's the most difficult thing you've ever endured? And I keep it generally open-ended. And some of the stories you hear about what they had to deal with in their upbringing, they were, came from broken home or they came with very few resources. and they're so driven about making sure that their family and their children never have to go through what they have to go through, just tells you this person is intrinsically motivated. We used to joke at BladeLogic, if someone has some character flaws, if the parents couldn't fix their character flaws growing up, there's no way we're gonna be able to do so at a company where they may spend X number of years at. So for us, trying to really understand the person and who they are and What they want is important. So now one way to qualify that is trying to ask them questions about, okay, help me understand what school you went to. Help me understand what major you picked and why'd you pick that major? Help me understand why you went to this company and then why'd you go from company A to company B? Because in some ways, those are some of the most important professional decisions you can make in your life. And if someone is not very thoughtful about why they went from company A to company B, then the question I'm gonna say is how thoughtful they're gonna be Prosecuting a deal or when they're making a decision on a product or when they're thinking about a new idea to come up with. And so that gives me a sense of how thoughtful they are and what makes them tick.
What's the most difficult thing you've ever endured?
I've set myself up for that question. I've shared this before. I came from a broken home per se. My natural father was not a very good person. He was a misogynist. And so my mother really had a tough time when I was very, very young in the early, late '60s, early '70s in India. Divorce is a very unspeakable thing. My parents, my grandparents were reasonably well-to-do people, and so it was a black mark in the family. So my mother faced a lot of pressure to stay in the marriage, and I give her so much credit for refusing to do so. So I grew up in an environment My mother ended up marrying my stepfather and who I consider my real father, and they decided to leave India because my mother realized the stigma of being divorced would be too painful for both her and for me staying in India. So we ended up emigrating and I lived all over the world and then lived in Africa, lived in Canada, lived in the UK for a while, and then moved to the US. Part of me has always felt like, am I good enough? Because in some ways I'd had this very weird upbringing. I'm a Christian Indian, so I'm a minority in my own country. Only about 2% of India's population is Christian. So even though 1.3 or 1.4 billion is still a lot of people, but you're a very small minority coming from a broken family. You know, I always had this like stigma about being good enough. And then when I was applying to college, my parents were living in Africa. My dad worked for an oil company and decided he wanted to emigrate to the United States. They kind of eviscerated the balance sheet. He went back to grad school, got a job in the aerospace industry. income level basis, they looked like a fine middle-class family, but the balance sheet was eviscerated because they'd used all their funds to kind of pay for going back to school. And so I had a chip on my shoulder going to a state school when I got accepted to some quote unquote more elite colleges. And now I look back, I'm so grateful for that chip on my shoulder. But like, it was always like, I want to prove to myself and prove to others about, am I really good enough? I've got all this baggage and background. And so That's, I think, one of the reasons back to why I asked what motivates people. My motivation is to prove to people that I'm good enough, to prove to people that I'm just as good as people who graduated from an elite college and may have had a more quote unquote normal family childhood. Looking back, I think it really served me well.
Objectively, you've proven that. I'm curious then if it persists as a source of motivation or if that has morphed into something different.
Oh, it definitely persists. I don't think you lose your upbringing. Any setback, you always start questioning, oh my God, am I good enough again? Any bad decision, you start questioning yourself. And so I don't think that ever disappears. I think sometimes you can suppress it for a while if things are going reasonably well, but I think it's always there.
Who is another leader that you've learned the most from observing?
I would say one of my key mentors was a guy named Steve Wolsky. So I had raised money for BladeLogic, but I had never actually worked at a software company, and obviously I'd never been a CEO of a software company. I was very self-aware to say there's a lot I don't know. So Bessemer and Battery were my 2 lead investors. So I went to the Bessemer folks and said, who's the best CEO in the Boston area that you can refer me to that I want to go speak to? This guy named Steve Wolsky, who was the chairman and CEO of PTC. I said, great, gimme his number. They said, here's his number, but good luck. He eats nails for breakfast and he might never return your phone call. I kept pestering him and then he finally returned my call. Me and my co-founder went to visit him. We had a good conversation, but then he kind of said, okay, let me think about it. I'll give you a call back. And I kind of said, oh God, is this the, I'll call you, don't call me kind of response? Turned out he did call me back and I used to go visit him about once a month at his house. in Chestnut Hill in Massachusetts and just walk him through what's happening in the business. And he was so valuable to me because he obviously had built— if you look at PTC, they were one of the great companies in the '90s. They built an amazing business. They delivered 40% operating margins and grew north of 100% for literally like, I think like 10 years straight. And they had also built an amazing sales force. And so he was very helpful to me to kind of understand how to think about building a business, how to think about dealing with a board, how to think about capital raising. Because it was a very tough time. As I said, raising capital right before 9/11, we're in the nuclear winter of tech. Investors were very skittish because they've just seen their portfolios crumble and any new investments, if there was any sign of hint of trouble, they'd panic because the last thing they want to do was see a new investment start struggling. So I felt a lot of pressure and he was really helpful to me in terms of understanding what it meant to be a CEO. And he really informed my leadership philosophy around marring product with go-to-market excellence, thinking about how to build a great sales force. He helped me recruit a bunch of CROs, including one guy named John McMahon, who's a legend in the space. He was a CRO at BladeLogic, ultimately became COO, and then he also worked with me and joined the board at MongoDB. So he was incredibly helpful to me. And the thing I really liked about him is I always felt safe that I could ask him any dumb question and he wouldn't belittle me. And I think, you know, one of the advice I give people is to really have someone that's a mentor to you. You gotta be able to open up the kimono. You gotta be able to really share your deepest, darkest worries and be able to put them on the table. And one of the things I realized is being a CEO is a very lonely job because you really can't open the kimono always to your board because you're worried about how they're gonna react. You can't always open the kimono to your team because sometimes you may be thinking about an org change that could actually marginalize someone on your team and they're not gonna be too happy about it. So having someone you can go talk to is super important. Steve played that role for me. I will be always very, very grateful to him.
What's your deepest, darkest worry at Mongo?
I mean, how we navigate right now the AI wave is something that is really important. It's really the future of how software will be built, and we want to make sure that we're a key component of the tech stack.
So how could that go wrong? AI gets adopted, it's everywhere. It goes really badly for Mongo, the pre-mortem here, like how would it go really wrong?
If people feel like MongoDB is not the right architecture for the best AI applications. Now, I don't think that's gonna happen. It's kind of like people think about using Oracle for a new modern application. I can't think of a startup today who's building on Oracle. It would worry me a lot if the next generation of companies and the next generation of apps, people felt like MongoDB was not suitable for those applications. That means like we need to work on our product roadmap, make sure we're building out the right capabilities, being responsive to customers because it's very easy to become complacent.
Do you think that there's any chance that AI is not the thing that everyone seems to now think it is and that it's not as transformative as is the very common consensus today?
No, I think AI's going to have a massive impact, but I think you raise a really good point. I was just telling people yesterday, I said, when I wake up, How much is AI influencing my life? Like the internet today has had a massive impact on our lives.
Every day, all day. Yeah.
Exactly. How much is AI really impacting life? Yes, you may get some hints about writing this note maybe a little bit more crisper than you originally thought. Yes, if you drive a Tesla or something, you can see the benefits of autonomous driving, but it's not really impacting your life on a day-to-day basis. But I always believe people overestimate the impact of new technology in the short term, but underestimate in the long term. The reason for that is that I think technology adoption happens in S-curves. And so it's very easy to take a couple data points on the rise up and extrapolate too much. Conversely, it's very easy to take a couple data points on the downward slope and extrapolate the dissolution too quickly. But if you look at the S-curve adoption for technologies that have really taken hold, it over time goes up and to the right. Now, there's clearly technologies that have not done that. I think blockchain and crypto, the jury's still out about those technologies, AR and VR. I think there's still some questions about how impactful those technologies will be. But I definitely believe AI is gonna be incredibly transformative. I think the way it's gonna show up for people is back to the way we started this conversation. It's around the applications. A lot of people thought software would be really disruptive and dislocate a lot of jobs. But if you look at what happened with software, pre-cloud and pre-SaaS, only the largest companies in the world were able to access the best software, the best CRM software, the best HR software, the best supply chain software, etc. When software became democratized, the small companies could take advantage of the best software. And so it just grew the market overall in such a big way. So a lot of people worry that AI will go after the white-collar jobs, the services jobs, legal, accounting, finance, et cetera. I would argue, and that's a potentially a pessimistic view, I would argue, yes, the cost of delivering those services will come down. But now small businesses will be able to leverage the best legal minds, the best accounting minds, the best financial minds, much like the SMB companies could take advantage of the best software that only the top-tier Fortune 500 companies could do so before. So I think this will be a net positive for everyone, but I do think it's going to take some time.
The list of investments that you made is pretty impressive 10+ years ago at OpenView. What is your investment philosophy? Like, what is it that you're consistently looking for When making an investment in another technology business outside of one that you're running?
What I look for is a big market because by definition your outcome is directly correlated to the size of market you're going after. 2, I look for is what is the defendable technology advantage that the company has and what proof points are there to prove that it really has a durable advantage. 3, I look for investments is a CEO who's smart but also coachable. And the coachable part is important to me because I don't believe that there's a compression algorithm for experience. Some people just learn faster than others. And I don't expect a CEO to do everything that I'm telling them to do because that's why they're in charge. But to me, I worry a lot if someone doesn't feel like they have all the answers. And I think vulnerability is a strength, not a weakness. And so Jyoti at AppDynamics and Olivier at Datadog are 2 incredibly sharp, people and they both built fabulous multi-billion dollar businesses. But they're also, while they, we would have fierce conversations, they would listen. Sometimes we'd agree, sometimes we wouldn't agree, but it was a very healthy conversation and they were both very, very motivated to build great businesses.
In the early stages of a business, how do you know when the product is ready for that bigger go-to-market investment and explosion? I guess the product market fit question, like how in your experience Do you know when a company with its first product or Mongo with its second or third product or whatever is onto something sufficient to like pour fuel on the fire?
To me, it's if the customer comes back and buys more, because any customer can buy something as a science project. And this is a trap I see a lot in the database space. So I'll get calls, diligence calls from investors saying, hey, do you see this company? They have some single-purpose functionality and they have a nice logo, set of logos. This space is so big. Someone's going to try something for some corner case. The question I always say is, yeah, but can they prove that they can repeatedly get more business from that customer or show a pattern of getting that for that same use case, winning other customers? And so to me, one hallmark is like a product market fit is the customer coming back and buying more. So, you know, people call that NDR or for public companies, you want rates of 120% and higher where if you look at the same cohort a year later, are they spending net of churn Are they spending 20% more than they did the previous year? And so that to me is a very good sign of the fact that you have something real. How easy or difficult is it to make that sale? Because if it's a very complex go-to-market process and you have to jump through 17 hoops, then I would worry about, is this like a unicorn that very few customers will go through all that pain to acquire? Or conversely, is it really easy? So one of the things that got me very interested about Datadog was I invested when they were doing about $1 million in revenue and now they're north of $2 billion. What I saw was the month-over-month growth of existing customers was 5% month over month, which is phenomenal. And so what that told me was not only it was easy because they were closing a lot of customers with a fairly junior sales force, so it wasn't a very complex sale, but the customers were also growing very, very quickly once they bought. So that to me was a great sign that this was— that they had really nailed product-market fit.
In addition to AI, which is obviously the dominant one, what else going on in the technology ecosystem is most interesting to you today?
I think security is an area that will always be important. And as you come out with new solutions to existing problems, people find workarounds to find new ways to break into—
Attack.
Attack, yes. And so to me, that's a space that unfortunately it's a tax, but it was a tax that we all have to pay because we all care so much about security and naturally so. But to me, the security vector is something that will just continue to be incredibly innovative. And now with AI and the notion of potential deepfakes and all the implications that come with AI, I think the security vectors will have to expand to figure out, is Patrick who he really is when he's calling me or sending me this email or the Slack message? And I think that's going to continually be an area that requires a lot of investment.
If you think about like handling the most contentious things that you have to deal with, As a leader of the business, what comes to mind and what is your like method of handling something hard and contentious?
Most of my issues are people related. I, I joke with my head of HR that I feel like I'm a glorified head of HR because 70 to 80% of my time's all around people. Who's moving up and why? Who's moving sideways and why? And who's moving down? Why is there a lack of alignment between different teams? And we're all kind of imperfect creatures. Like everyone has their strengths and weaknesses. And in times of stress and tension, you see people's weaknesses showing up. And so a big part of my, where I spend my time is all around people issues, whether it's with my direct team or with structural issues around people issues around comp, people issues around like culture. We spend a lot of time, for example, on leadership development. What I said is one of the struggles young leaders have is knowing how to hold people accountable. Yeah. I tell people, If a leader is incredibly self-aware, knows how to recruit, and knows how to hold people accountable, they will be a fantastic leader. But those are skills that you just don't absorb. Maybe you can learn from observation, but if you have a program, you can help people develop those skills, that becomes incredibly powerful. So we spend a lot of time on leadership development. It's actually scaling that middle management layer becomes a very, very important role in terms of the culture you create and your ability to execute. Because at the end of the day, I'm not really making lots of direct decisions myself. I'm leading through others, and ultimately others are really driving the business day to day.
What are your preferred tactics of accountability, of keeping people accountable? What has worked best for you?
Again, most people struggle with knowing how to keep people accountable. So we have this 3-step process that we encourage people to consider. The first one is you need to be very, very clear on expectations. That's the first mistake people have. They're not very clear on expectations, or expectations very fuzzy. By definition, if you have a fuzzy expectation, then you're setting your person up for failure because they don't know what good looks like. So one, you should be very, very clear on expectations. 2, when they miss an expectation, the initial approach you take is that the onus is on you, their manager or their leader, that you weren't clear enough on the expectation. So they misunderstood why that expectation was important or why the expectation was partially met or unmet. And the point is, is that you're not beating them up. You're saying, you know what, I wasn't clear. I should have done a better job explaining the why I should have, like, so I'll give you a simple example. Say, Patrick, you run a team and, and every week I say, Patrick, I need an update from you on what's happening. Say you're running customer service, a success function, and saying, I need an update every Friday on what happened the week and what trends you're seeing. And Friday goes by. I don't get anything from you. So I'll come to you and say, Patrick, maybe I wasn't clear on why this is important to me. The reason this is important to me is really gives me a picture of what's really happening with the customers, what the feedback is on the products, how their buying behavior may be changing, what potential competitive dynamics are happening. Our competitors may be underpricing us, et cetera. So Patrick, are you clear on why this is important?
Yes.
Okay. I got it. Now the third step is now if you miss it again, It becomes very easy for me to hold you accountable because I've done steps one and two. I've made it clear what the expectation was. First time was missed. The onus was I made the mistake, not you. Next time you make a mistake, there's no place to hide. But most people don't do step one and step two. So then you can barely get at the end of the year. Patrick, I'm gonna give you a meets expectation. You're like, meets? I thought I was doing a great job. Well, you missed your and then you'll be like, well, why the hell didn't you tell me? It becomes a very dysfunctional conversation. You get demoralized, I don't feel great, and God forbid, maybe you start thinking maybe MongoDB's not the place for you. So this is a thing that young leaders really need to develop. And young leaders know how to hold people accountable in a constructive way. They will have a dramatic impact in their career.
What else have you learned from Andy Grove that just makes me get in like an Andy Grove mindset or something? That very nice, simple, elegant way of approaching management.
Love Andy Grove. I think he was truly one of the seminal leaders of our industry. The best thing I've learned from Andy was that there's only 2 reasons why people fail. One, they failed because they didn't have the skills to do the job, or 2, they failed because they didn't have the will or the drive to do the job. And if you net it out, that's the 2 reasons. And people overcomplicate things and all that. So we call that the skill-will matrix. Do they have the skill to do the job and do they have the will? And invariably, We find that if you ask people to, on a 2 by 2 matrix, to plot people, invariably, let's say they have high will, but kind of, they don't have necessarily all the skills to do the job. But then say someone who has a skill to do the job suddenly is not performing anymore. And why did their will change? Well, maybe they felt they should have been promoted and they didn't, and they get demoralized. Maybe something's going on in their personal life that's affecting their performance. So that skill-will matrix is an incredibly powerful way to assess your team and say, What gaps or problems or issues do I have with my team? If you map people on those 2 dimensions.
Anything else in the vein of that very elegant 3-step process for setting expectations? Any other tool in the toolkit like that that you find yourself using again and again in the management of the business?
Don't ignore bad news in your house. If your dog poops on the floor, are you gonna step over and keep walking? You're gonna get your pooper scooper and come clean it up. Similarly, like, if you see bad news, you can't just ignore it. Your responsibility is to investigate and really get at the root issue. And invariably, you always find out when you ask someone, hey, after you fired someone, just, oh my God, I found out so many more problems. The point is, again, like I said, bad news travels very slowly up the organization. So even you as a leader, you're only seeing a tip of the iceberg. What happens is that when that person leaves and you start really digging in, you said there's so many other problems I didn't see. Another potential thing that I find is really, really important is a tell that I use is when a leader's not scaling. The biggest tell for me is they're losing their team. Because again, one of the axioms I have is you can usually fool the people above you. You can sometimes fool the people around you. You can never fool the people below you. Why? Because they see how effective you are in solving, resolving problems for them. They see how effective you are in the decisions you make. They understand the rigor and logic you're making, or the lack of rigor your logic in making and making decisions. So they get to see who you really are, but you can kind of mask some of that to your peers and to your boss. So when I first joined MongoDB, one of the first things I did to assess the leadership I was inheriting was to kind of meet the whole, you know, leaders across the business. And it became very clear to me who were the good leaders versus the bad leaders by the quality of the team they had. And I look at like attrition data as well as the people they were hiring. The inverse of that is I find A's hire A's, B's hire C's, and C's hire F's. So as soon as you have a bad leader, all the good people leave and the quality of people they're recruiting is far lower than the team they inherited. So those are all tells about how effective a leader is, and that's usually a sign that you gotta go take some action.
Do you feel like there's any major unfinished business at Mongo?
Oh, big time. We're constantly getting pushed on product. We have a very scalable platform, but we have customers who are demanding even more performance and scale. We have a whole bunch of features that customers are asking for that we need to kind of work on. We're pushing ourselves on the go-to-market side to become more efficient as we scale. Investors wanna see the classic rule of 40, high growth but increasing profitability. One of the challenges that we have in our business is that we're not a technology where we make a centralized decision. We're not like an HR platform where everyone's standardized on Workday or everyone's standardized on CRM where everyone's standardized on Salesforce or even say like a data warehouse like Snowflake. We have to win business application by application or workload by workload. So that can be a fairly expensive sale, cost of sales. And so how do we reduce that by becoming a standard? How do we create virality by getting developers to self-select us more quickly? So those are things we're constantly trying to work on and become better at. And obviously it's a very competitive space. We're competing with the hyperscalers, we're competing with the legacy vendors, always competing with new entrants.
On the point of investors and how they view your business, one lens beneath growth always is the defensibility of the business. If you continue to be successful, the profit pool is there that invites new entrants. They want your profits, you know, they want to come for them. So you have to have some sort of sustainable differentiation around the business. Do you think about architecting that? Is it something that as you strategically think about the business, you're returning to over and over again? Like, where's the power in the business? Where's the defensibility? Is that an active part of your strategic thinking? And if so, I'm just— I would love to get let into the room on how you apply that concept to Mongo specifically.
Well, I would say in general, you always care about churn, right? Because by definition, your durability business is an inverse of your churn rate. So you always care about the churn in your business, but it becomes even more profound in consumption business, right? Because consumption business, you recognize revenue by usage. So consumption business gives you a real-time view of demand. And sometimes your consumption goes down because it's not been anything you've done wrong, but customers' online business is slowing down. Maybe they're selling 100 widgets a day. Now they're selling 80 widgets a day, and there's not much we can do about that because their consumption of our underlying platform has gone down by 20%. But sometimes you can also see, hey, something's going awry because either the performance of the system is not as good as it should be, or maybe the cost is going up disproportionately to the usage. And maybe it's because they've misconfigured their database schema. Maybe they've misconfigured some parameters. Maybe the indexes aren't optimized. So there's things we can do to really deliver a superior performance. And that's why we've really invested in customer success function. Because in a consumption business, it's not like we sell something and move away. We're engaging with the customers almost on a daily, worst case weekly basis to understand what's going on. So we care a lot about that, even though inherently databases are very sticky. They're one of the stickiest technologies customers will use, but we don't take that for granted.
Another book that I've seen you reference is Talent Is Overrated by Jeff Culvin, I think is his name. I'm curious what you learned from That book kind of in the same spirit of what you learned from Andy Grove?
It's been a while since I read that book, but the takeaway for me was that if you're a startup, if you raise a little bit more money or acquire better talent than your competitor, that has disproportionate outcomes. Like an athlete, if you are an athlete and you get recruited, say you and your friend, you tried for like the A team and you're on the B team and one of you makes the A team. Now all of a sudden that person is playing with a better set of players around them. They're getting better coaching and all of a sudden their performance is increasing exponentially. So basically putting yourself in a position where you're working with the best people around you delivers higher performance. And I've seen that. I have a son who's a Division 1 athlete who I saw that happen as he grew in his career. His development grew exponentially with the better players around him. And the same thing with startups, the quality investors, the quality of people around you, can have a disproportionate impact on the outcome that you have.
What have you learned from Roelof being on your board and working with your business?
Sequoia has been historically our largest investor. I really admire Sequoia and Roelof for a couple reasons. I historically really respected Sequoia for how disciplined they are. Like a lot of venture firms out there saying we're very founder-friendly, and I've been involved in some situations where investors don't want to shoot the CEO because they're the founder, because they worry about the reputational impact around them. So they'll say you should get a COO and they do some weird things organizationally to preserve their good name, but in some ways hurting the business. I always respected Sequoia and how disciplined they are about everything starts with building a great business and working from there. Obviously they want to be supportive of founders. One of the things I really respect about Roelof, I've been on boards where the largest shareholder feels like they have to have the loudest voice in the boardroom. That can get a little tiresome because sometimes it's other people who have more insight than necessarily the largest investor. And one of the things I really respected with Roelof is that Even though he was always the largest investor in MongoDB, he would listen very carefully. And when he spoke, the signal-to-noise ratio was very, very high. And so he didn't try and use his ownership percentage to kind of pound the table and all that. He would really like to understand the business. And when I joined the company, it was, the company was in quite a fragile state. So he was very, very supportive in making sure I was set up for success. And there were times when there were some challenges in the business when I would ask Roelof for help and he would help me in a nanosecond. And so he's always been there for me when I needed it, and I really respect that. Again, back to the point that the CEO job is a very lonely job. And so when you want your board to help, it's really helpful.
What are you most excited for next in the business?
It's really this transition to AI. I think it's gonna be a multi-year transition. How we position ourselves and navigate this transition is gonna be really, really important. I think it's really exciting. You know, this is just another day doing the same job day in, day out. It can get a little boring. Obviously, we're also growing as a business. One of the things that gives me the most joy is when employees come to me and tell me how grateful they are because the value they've created at MongoDB has enabled them to either put money away for their kids, buy a potential home or a second home, and just given them a certain level of economic security that they didn't have before. And there's nothing that makes me feel better than to see the impact we're having on our employees' lives. And I always tell people, don't come to MongoDB for a job, come to MongoDB to build a career. I draw this picture where the slope of the line before you come to MongoDB, there's a black box where MongoDB, and then the slope of the line you're leaving MongoDB is at a very different level. I said, so my goal is that the skills you gain here, the relationships you build, and the experiences you have, will shape who you are for the rest of your career. And hopefully that's taken hold.
David, so much fun talking to you and hearing about the business and all the lessons you've learned. I think you might know my traditional closing question for everybody. What's the kindest thing that anyone's ever done for you?
I think believing in me. As I shared with you, I've always had this inner doubt about am I good enough? And as many people believed in me when maybe I didn't think I deserved it, whether it's, like I said, Steve Wolsky believing in me when I had no experience building a software company, It's investors who believed in me and investing in MongoDB when there were questions about would MongoDB make it, whether it's people who believed in me coming and joining the company and trusting me on going on this journey. My wife who's believed in me at times, maybe I didn't always deserve that belief. That's something I'm so, so grateful for.
A simple and wonderful place to close. Dave, thanks so much for your time.
Thank you, Patrick. It's been great to be here.
If you enjoyed this episode, check out joincolossus.com. There you'll find every episode of this podcast complete with transcripts, show notes, and resources to keep learning. You can also sign up for our newsletter, Colossus Weekly, where we condense episodes to the big ideas, quotations, and more, as well as share the best content we find on the internet every week.
More from Dev


20VC: MongoDB CEO, Dev Ittycheria on Why Sometimes You Have To Be Inefficient To Be Effective, The 2 Different Types of Decisions and How Great Leaders Respond To Each & Why Value To Overhead Ratio Is The Metric To Use When Selecting Investors