Dave Link of ScienceLogic joins Nick to discuss A 20-Year Journey from the Garage to Nine-Figure ARR, Reinventing with Every Platform Shift, Avoiding the Innovator’s Dilemma, and Future-Proofing for Generative AI. In this episode we cover:
- Transition to Venture Capital and Market Evolution
- Navigating Platform Shifts and Generative AI
- Leadership and Team Building
- Managing Expectations with Venture Capitalists
- Future of Generative AI and Data Quality
- Personal Habits and Leadership
Guest Links:
The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area.
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Dave Link joins us today from Reston, Virginia. He’s the Founder & CEO of ScienceLogic, a leading AIOps and IT observability company. Before founding ScienceLogic, Dave was an SVP at Interliant and held leadership roles at IBM. He launched ScienceLogic in his garage in 2003, bootstrapped it for seven years, and has since grown beyond Unicorn status into a global company with over nine figures in ARR. Dave, welcome to the show!
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Great to be with you. Nick, yeah, such a pleasure to chat again. Why don’t we start out just with a quick backstory to becoming an entrepreneur? You know, I’ve had that in my bones since an early age, I had probably four or five businesses. As a young teenager, I had a lawn cutting business. I grew the biggest paper route in in our town, selling one paper at a time, door to door and and then I started on the side, another business with my my parents, repairing old engines and reselling things and trading things. So that mindset was always core to who I was, and at the same time, I had a w2 job working on a golf course. So I just loved work. I loved accomplishing things and learning, tackling a new task, figuring it out and getting to the other side. Awesome. And so, you know, you left IBM, you started science, logic. What was the initial insight there? I had been looking at this problem for much of my professional career, managing networks, managing infrastructure, delivering that great service quality to a user through an application that was delivered in the early days of kind of the internet, before the internet, CompuServe, which is where my first career started, I got to really understand networks and systems and applications through that job. I was there about nine years, almost 10 and then I went to IBM and led some product teams where we were taking really the best technologies out of the globally renowned labs and getting them to market in internet speed. And that was an era where the marketplace was evolving so quickly, but you really had to formulate something that would have a quick time to value, very different than a prototypical IBM software product of the day, and that then led to a job at interliant, where we became the largest application service provider. While I was there, we were delivering in the early days of SAS, Microsoft Exchange as a service, before 03 65 PeopleSoft as a service.
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I’m I’m really dating SPS, Lotus, precursor to SAS. Yeah, exactly. And, and what I learned was It was super hard to have all the different technologies come together to deliver that perfect experience to the end user. And if we didn’t have the right observability, we could never get it right. We could never be proactive. We were always going to be reactive, taking a call on a service down issue and then scrambling. And that is a very defensive position to be in. So that light bulb moment was the industry’s broken. We were using 1215, tools to try to operationalize that service delivery, and it was operational chaos, and that was the light bulb. That’s like, I’m going to solve this problem. I know the problem. I’ve been looking at the problem my whole career. I understand what an end user expects, and I understand what the operators expect, and the industry is not delivering a great outcome to users, and I know what that outcome looks like. I know what it should be, excellent. So, so Dave, you bootstrap for seven years, right? This is an eternity in tech. Was that discipline a competitive advantage, or did it come at a cost in an industry that sort of reward, rewards speed and capital? You know, I think that the DNA of the company and the culture of the company was always to figure things out and do more with less. We started out that way, candidly, right after the.com bust, you really had to build, at that time, a company that had a viable product customers, a revenue stream and product market fit. If you didn’t have that, you weren’t going to get investment at that time. There just wasn’t as much money floating around. The average a round investment was one to $4 million at the time. Our a round ended up being 15 million. But we were already a going concern. We had customers, we had revenue. We were slightly EBIT positive at the time.
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Time, and what, what I learned through that process was the team really had to hone in on market fit. We, you know, we were just pushing so hard to get it right for the customer, to get it right for not just one customer in a bespoke way, but
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a large swath of the market, and so we focused on a set of highly differentiated feature functions that made it really obvious. We actually just tried to be the opposite of everything that you buy in the marketplace, so that we could create that differentiation that, at a glance, was really clear, crystal clear, that people could identify with the pain they were going through, running and operating complex IT environments without the right tools or with seven or 10 tools, but really needed one, one way to look at all operational performance, fault, configuration, data sets in one tool. And that really didn’t exist at the time. It was very hard to accomplish that. You had to stitch together two or three tools. You had to create your own back end integration and then your own portal to visualize it, your own set of dashboards. So we solved those three problems in one product market fit. And why did you take the money then you bootstrap for many years. It sounds like you found product market fit, you had success, and then you took a $15 million a seven years in our vision at the time was that the market was evolving rapidly beyond our one brick at a time financing approach. You know, I had a half a million dollar line of credit that I was using on our house. We had five credit cards. We were using all kinds of clever ways to manage cash flow and make make payroll every two weeks. It’s relentless. It doesn’t stop. Clever. And so that takes you only so far. Looking back, I probably waited too long to get the right capital in the business for the market opportunity we have we had in front of us at the time, but it did create that DNA in the company to figure out how to do more with less. And we’ve achieved over 100 million in ARR. We have more ARR than we have primary capital invested in the business, which is not common these days. And I think that that DNA carried through. What it also really led us to focus on is making sure we were delivering value to the customer. Because we could not afford to lose the customer. We had to keep growing the customer. Our NDR had to be 131,
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41 5200, plus. In those early days, we made the Inc 500 a couple times the Deloitte fast 500 I think we were at 58 the first time we we joined it. And so that got us notoriety. And I had many inbound calls from institutional investors. And ultimately we realized one huge catalyst, a moment in time where everything changed. Amazon came out with AWS cloud computing that took virtualization to another layer, another layer of complexity, with containers and scale out applications. And that was a moment where we realized to to fund R and D ahead of when you have the revenues coming in from managed Amazon infrastructure solutions, because more of our customers were taking their virtualized environments and putting them in the cloud, but they wanted to see that hybrid view. They wanted to see infrastructure no matter where it was. And we had to then invest ahead, to invest, really in the early days of experimentation with figuring out Amazon’s API in the early days, it wasn’t perfect. It was It would only feed you so much data with so many queries, and then you had to buffer data. It was very complex to get data out at operational speed. And I realized that was going to change everything. It was going to change the way the world worked, change the way it worked, and we need to get ahead, and we need how to have the right capital and hire the right team to really change the trajectory of our business. And it’s one of those things that we like to talk about internally every five to seven years. We really have to rethink the business, reinvent the business technology is moving that fast, and these compute architectures that change over time, cloud computing was another compute architecture change enable a whole new raft of applications you got to be ready for in an operational tool like ours. So Dave, I want to come back to the financing stuff a bit later, because this is super unique, right? I’ve been hosting the show for 11 years, and we’ve never spoken with a company that’s had this much success over 20 some odd years, in a different fashion to what is typical. You know, most people come on and they’re kind of in the Blitz, scaling.
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And, and you’re different, but, but just to pull on that thread, you know, you saw all these different platform shifts, all these different paradigm shifts as you’ve built this company, you’ve gone, you know, the the market’s gone from mainframes to client, server to cloud to now generative. Ai, so to start on this, you know, how have you navigated such significant shifts and continued to thrive and grow. Well, we’ve just had to do it again, and I’ll just give you the most recent example. Three years ago, we saw the early stages of generative AI as a magical capability to summarize very complex log files. Log files are heavy in text. They’re not uniform, and often you might pour through 20 million log files to get to seven that matter. The seven that matter you need summarized in a way that’s human readable, because sometimes log files are machine readable, but the human, only the application developer can really decipher what it is, and you need that really uplifted from a context perspective to a level one, level two engineer, not the developer. So ideally, when you’re operating you’ve got to abstract data, summarize it, and then make a recommendation. And we realized that we weren’t leveraging Gen AI, but it was, it was coming. And so we decided to basically create an initiative called internally, V next. So this was three years ago, and we basically decided all the really great work we’d done to get to the success we had with the company thus far, throw it aside. We’re going to start the company today like a new co brand new. And if we were to start today, a company today solving the problems that we want to solve, what will we do? How will we do it differently? What technologies, foundationally, will we use to get there? So it’s what you were doing in previous platform shifts as well. Dave, yes, yes. So this has been kind of a recurring motion where I mentally, every three to five years, say, I’m going to I’m going to work with the executive team. We’re going to take a quarter and we’re going to have a series of strategic meetings throughout that quarter, usually once every three to four weeks. They’re one to two day meetings where we reassess everything. We start fresh, and sometimes they were conclusive as to we need to re, architect, re platform. Change our messaging, change the sales motion, change the target audience, change the personas. In some cases, we made holistic changes, like the one three years ago, where
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the next it will be, the next version of our product for seven years out, for the future, maybe, maybe three years out, three to seven years out, and and that has been kind of one of my management paradigms, that technology is moving so fast when you have these big compute shifts from client, server to cloud to now Gen AI, the whole application landscape changes, capabilities change, and if you’re not aligned, to really rethink, almost deprecate what you already know and try to start fresh with what you don’t know and what will be someday. That’s what we did, and what we realized was the future of our product would be less about presenting 1000s of data points in an at a glance dashboard, and more an interactive advisor to a level one, level two engineer who’s talking to a technology to help them do their jobs and to solve problems that perhaps a level one engineer can’t really solve because they don’t have the right expertise. But with the future of what we can bring to them they can’t, and that was our identification to analysis and countermeasure, or yes, all the way through root cause, solution and resolution. So question on that like and I’ll give two anecdotes that just happened recently. So So one is, I was talking to an entrepreneur the other day that’s had tremendous success. And a data point he gave me is that every major phase of growth that they’ve gone through, the leadership team in place couldn’t make the leap. So ultimately, the team changed fundamentally at each layer of growth. Another thing that I noticed in my career at Danaher is when we would do strat planning. You know, a lot of the people in the business were, it was difficult for them to look at future states with fresh eyes, right? You talked about fresh eyes like reinventing the company like So how have you accomplished? You know, this fresh.
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Eyes concept, how have you structured your leadership team and your new co projects in order to capitalize on these different phases? It’s not easy, because that institutional knowledge and behavior is so strong and so it’s so easy for that to overcome and to second guess change. But you can’t let that run the course of the business. You have to fervently believe that the future actually is different. We need to look at it with a fresh set of eyes. So very often, I could not do that with the exist the existing team would not allow me to do that unless I had on the team somebody who basically did not have the institutional memory and could come in, not worried about the past, really thinking about the future. Most recently, we realized, as we sat down and thought about what is the future three to five years look like? 10 years? What is the future going to look like? We realized that Nick we didn’t have anybody in the company that had the technical chops to do this. So we then set out and looked at 250 companies that we could buy. We started with what we knew we wanted to have in that company, that technology, that founding talent, and how that would complement our vision for the future, knowing that we could not get there ourselves, we already had customer commitments. That’s a huge once you get to a certain size and scale, 100 million plus, which we were at the time, customer commitments, they are relentless. They just keep coming as you every next new deal that you get in X, next new product that you want to launch, those commitments get embedded. They get in long term plans. Those plans get communicated. They get etched in stone. So we truly had to break clean a new team, a new philosophy, new viewpoints that we left not to be merged into the host. We left them as a separate entity to run, operate and create this. You know, Cisco did this quite successfully for many years of of their most profitable products over the last two decades, they brought a team in that they started with a totally fresh concept, and they changed the way the technology and the future architectures of Cisco’s products delivered value and how they leapfrogged the competition From a thought perspective. So I like to think that you can do it internally, but my experience has been very unsuccessful. You need an outside catalyst to break through kind of the glass of inertia of companies that are going concerns. I believe it. And you know, one aspect of sort of the innovator’s dilemma is this fresh eyes concept that we just spoke about. Another part of it is that new tech waves are often deflationary, and while they may expand the volume of buyers in a market, they typically collapse price so, how do you navigate that piece right as you’re creating these new cos and positioning yourself to win the next wave? How do you deal with potential cannibalization of your cash cows? So to speak, what we’re doing in the marketplace now is making sure the customer has a quick first time to value and that they understand relentlessly. Actually, we now have it in the product where we’re showing value delivered. One of the values that we deliver operationally is automating tasks that humans used to do. Many people call that agentic, agentic AI. So we have many elements that are agentic within our product, and we now have dashboards that add up with the customers, true P and L details of what they believe that automation is worth, so that they understand each and every day value delivered. And I think that’s one of the things that is lacking right now in some of the Gen AI rollouts is, what are the business benefits? We can quantify them and say, well, somebody in marketing was able to put together sequences for the next email across five personas in two hours versus two weeks. Okay, that’s, that’s awesome. We’re doing that ourselves. So I’m I’m seeing that, and I’m a beneficiary of that. We have to in in our business, make that really apparent and make it easy for the executive teams within the CIO, the CFO, executive teams within company we serve at that persona level, the value.
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We’re delivering. You know, I think it’s the way we’re thinking about the product now, AI really elevates the human experience and gets the level one Help Desk persona to do level two, level three work by taking the context of what we have with machine telemetry and adding that with human content that we bring together for the first time so that issues can be resolved and remediated by a level one tech that he could never do before. So I want to touch more on team building. Dave, you’ve been through many waves. You’ve built a variety of teams, and in some cases, you’ve talked about finding fresh eyes, so people writing new playbooks, you know, the cartographers out there, versus you’ve also had probably a bunch of GMs and people that are excellent operators, right? More of the navigators, right? You give them the map and they can navigate. Well, talk to us about how you’ve built, you know, successful, high performing teams. And you know, do you credit selection or development as a bigger success factor? You’re never done, mentoring, shaping, developing teams, even with the most seasoned of resources that you could possibly on paper, ever find, I like to say, and no offense here, our institutional investors are brand name resume buyers. So if it has a brand or a company where they’ve had success, that’s who they want to hire. And interestingly, I’ve found that not those people are not always super successful. There were elements at play that they were associated with a brand that had unequivocal success. But did they actually create it themselves? Did they have the skills to punch through at maybe a smaller company or maybe a bigger role than they had at that other company. So you have to have the talent talents. Job Number one, you got to be a great leader to quickly suss out talent. You have to have great recruiting by your side. That does we always do whenever we hire somebody of consequence, we always do background reference checks, but they’re blind, and we try to get three to five blind checks. They’re hard to get. You have to have a great recruiter. You have to have a great team really focused on blind references, because getting references are really of minimal value if they’re provided from the candidate. So we would combine that we have a very blind meeting off sheet, yes, yeah, yeah. The recruiters would work through LinkedIn and figure out seven degrees of separation. Who else they could talk to about this, sure and and get, get con context, even with skip level people right then that sometimes that’s really important, the skip level impact that a person had, if it, if it’s a senior role. So talents, job number one, great recruiting, to find it a good a good sense of, will they fit into the team in a way that’s cohesive, or are they going to be an outlier where the host ultimately rejects them? So a lot of important things on recruiting. And then finally, I have all my quarterly meetings, strategy meetings set up at the beginning of the year for the full year. We have monthly meetings. We have every I have a meeting with my direct team every Monday for two hours every Monday, relentlessly, whether on vacation or not. And and what we do is we kind of shape the team into the principal initiatives we have for the full year, and then we break them down by quarter. We break them down by month, and then we have about seven to 10 KPIs that we really churn on. And look at how are the trend lines for those KPIs. So once people get into that cadence, they’re either going to work or they’re not going to work. They’re either they’re going to make a difference and be leaders and say, I’ve got that next challenge. I’ve got to give it to me, and I’m going to run with it, and we’re going to tackle this to the ground and get to the other side of it, or they don’t. They don’t behave like that. And you get that figured out pretty quickly. I think you know, if there’s one thing I’ve learned over time with team with specifically senior hires, you have to make decisive decisions faster about hires that didn’t work. I’ll never forget with our institutional investors in the investor rights agreement, anybody that reports to me that has a C level in their title, CMO, CRO. CFO requires board consent, and in really board interviews. And I hired a CRO, and within 45
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six.
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Days. This is about seven years ago. This isn’t going to work. He’s just like, something’s drastically wrong. He had a great career, incredible performance, the last job, but something was off. Something was off, and I had to talk after talk with him, and I had to go to the board, and I said, You know what? I made a mistake. It’s hard to admit your mistakes. It’s hard to admit a mistake that quickly, but what I learned the board loved, ultimately, my decisiveness when I went through what I had been experiencing with this gentleman that just was not working. We were badly broken, and we weren’t going to get to the success we needed on go to market, on sales with this leader. And so I I then had to recruit a new leader and take on some of that role myself in the interim with the other sales leaders that we had around the around the globe. But I think, you know, hire great talent, great organizational fit, have a good cadence of how you run operate, make sure they fit and figure that out quickly. And if, if they fit and they can start executing, then you can go fast together. If they can’t fit and they can’t execute, then you will not go fast. You’re going to slow down. Everyone wants a silver bullet around hiring and there, there isn’t one. But if there was a tactic or a specific question that you’ve used or had success with in the hiring process, you know, what? What would you leave with with the entrepreneurs out there that are going through this one question that I ask almost every time is this intuitively falling out of bed, what are you best at? What do you enjoy doing the most? Because what I’ve learned over time, Nick is the things that we’re best at that come naturally to us. We kind of crave doing more of that, because it sends off as endorphins. We love it like man, I love this. I love this because I feel great about it and I know I’m good at it, and it feels good to do more of that. Absolutely. Always ask that question. Sometimes it relates to the job, sometimes it doesn’t, but it helps me learn how they think. It helps me learn about how their brain is wired, and then I have to interpret, is that going to fit for that role? Are they going to be great at this role, or are they just doing this role for a paycheck, or are they just doing this role? Because somehow they’ve kind of got into this position, and they’re going with it, and they’ve had some success with it, but it isn’t what they’re great at, and can I make what they’re great at incorporated into the role so that they supercharge their accomplishments in that role? So I usually ask that question, and it’s interesting, people are not great at answering that question. That also tells me a lot about how introspective people are interesting. So another thing that came up in our discussions, Dave is that you advise founders to be crystal clear on their end game from day one, how did your own thinking about sort of your vision and your end game, shape your early decisions. And did that evolve along the way? It did so. The company I was with before starting science logic was a company called interliant. I think I was employee 12. We took it over five years to 1600 employees. We went public. I was an officer of the company. We acquired 16 businesses along the way. It was a roll up strategy of a web hosting and back in the day, web hosting and application service provider ASP is what the industry came to be known. We were the second largest ASP in the in the country, and that’s really where I kind of got my operational chops of the the tools weren’t right to deliver that great high end people, soft exchange, Oracle, financials, those kinds of applications can never fail, otherwise you have catastrophic problems. So, so you really have to have everything operationally, just dialed in. But what that taught me, and what I learned through that process of kind of the the early years of my career, the ASP industry, we we crashed and burned. The music stopped in the year 2000 we had built all these data centers, and the company went to a $2 billion valuation very quickly, but they came back down to a half a billion and and I thought, okay, I know what I don’t want to do. I don’t want to buy a bunch of things. Try to glob them together and not re operationalize the run, operate. I want to build a sustainable business. I want to solve a problem that’s gigantic. I want to solve, solve a problem with a big tam that is badly broken as an industry, because at the time we started the company, every product.
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The network had their own management console. The operating system had a different management console. The database had a management console. The security team had a management console, the network team, every single team, often delivered by the products that you were using in that genre to build the network, to build the systems, and so nothing was really interconnected, and I saw that as a big gap. But I I really started the company thinking about a very big problem, and I didn’t want to just solve a niche. I’ll just solve the network problem. Nope, I wanted to solve the Megillah, I wanted to solve the service quality problem, and the service was made up of many technologies that come together to deliver the service. And so my mindset was we could start something small and tight and just niche, but we wanted to transform the industry. It was candidly, when we started the company that was such. The DNA of our belief is we can do this. We know what it looks like. We know what a better future looks like, and and this is how we’re going to do it, and we’re going to prove to the world that we can do it. We’re not going to take money. We’re going to use our own money. Use. I didn’t take a salary for the first two years. You know, we we didn’t have any money until we started. I think we, we coded and built the product for the first 18 months, and then we started selling. Put in several patent applications that we thought were novel. After we got those in, we started selling. And after we started selling, the selling was pretty brisk, because we we really nailed product market fit and and it was kind of a combination of my journey in technology and seeing how networks and systems and services worked for a user’s outcome that drove us with the vision that there was a better way. We knew what it was. It was a huge problem. Every single company on the planet had it, and nobody had really nailed a simple way to get to a service view. You know, Dave, one of your articles emphasizes that future proofing AI depends more on the data than on the model. While we have you here, I want to make sure we get some insights on this. You know, what do you see as the major risk around enterprise data infrastructure that’s sort of flying under the radar right now. Well, the biggest risk, even with with artificial intelligence, is poor quality data in, bad results out, skewed data in it isn’t accurate, bad results out from a summarized article. So there’s lots of controls that we need to put in place to make sure we have very high quality, high fidelity, accurate information. So I think the the big risk right now is, what are the parameters that we put in place for how new information gets into the data model, and how do we know that that’s fitting a paradigm that we’re we’re okay with, we’re copacetic with, okay. It’s met this criteria of cleanliness, of accuracy, of timeliness. Now, machine data tends to be black and white. It came from the machine. But interestingly, every vendor has their own little idiosyncrasies, where a CPU from one vendor isn’t like a CPU from another and a CPU from another, from a server to a router to a switch to a firewall appliance, it’s all slightly different in terms of the way they provide that information about how it’s behaving. Now that changed a little bit as we virtualized those systems and and that kind of standardized what CPU look like on a virtual instance. Now we’ve containerized those instances and and decoupled different parts of the application processes into containers, and now we’re kind of on this next path of abstraction layers of an application where you’re really trying to figure out what’s going on. So from our perspective, data quality is job number one, and we have to source data quality from 1000s of different methods, bring that into one data lake that normalize the information so that a CPU is a CPU is a CPU across whatever the technology is, and that’s what I mean by data quality, data cleanliness. Once you get to that level of massaging the data so that you know you have consistency across it all, then you can do very clever things, which with myth, machine reasoning, with artificial intelligence, but data quality. If you don’t have data quality, you know everything else is suspect, because you’ll get hallucinate, you’ll you’ll have failures to deliver outcomes to a user with their expectations.
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Bad data quality, they’ll know instantly that doesn’t make sense. That’s not right and and that that then is a quick pathway to it’s a quick pathway to losing the confidence of the customer, and once you undermine the integrity of life is really hard, because the amount of work you have to do to get that confidence back. It’s enormous. It’s an enormous amount of work. Every day. I try to talk to at least two customers a day. So I’ve got one down today. I’ve got one to go, and sometimes it’s three or four, but that’s how you really stay close to what what do they care about? What’s on their radar screen? What are we getting right? What are we not getting right? How do we change a narrative with there are so many challenges in enterprise software these days, where, with you know personnel changes, your sponsors are leaving, they’re moving, and when they move, you have to re energize the relationship. And so it’s that’s a whole nother topic for another session, 100% re energizing the customer over a 10 year journey is a really interesting topic, and we’ve taken some proactive measures to do that. And I tend to be one of those catalysts in our business to help re energize the customer at different levels of personas, not not just at the top level personas, but all the way down to the engineers, amazing, well, and hopefully they move to a prospective customer, you can grab them, yeah or two, right? But, you know, I want to circle back to the financing component, right? So you have a very unique story, right? Built the company over 20 years. You know, you’ve ridden every new wave successfully, but you know, expectations of VCs are, you know, t2, d3, and 300% per year growth, and let’s, you know, rip fast and go to IPO. So I’m curious to get your take on how you manage expectations with VCs, and how you see this environment for private companies evolving? You know, as someone that’s run a company for 20 years, we’re seeing companies stay private longer. We’re seeing, you know, investors are locked up, founders are locked up, employees are locked up. Like, talk to us about VC expectations, investor expectations, and how this environment, you know, is going to evolve in order to serve stakeholders. Well, I’ll go back to the beginning of our our VC investors. One of the things that I think we got right was partnering with the right investors who had a long term vision, Nick and in case, in some in some cases, our investors were balance sheet investors, Intel Capital, where they didn’t have the pressures of a seven to 10 year fund, but there’s now continuation funds, and lots of interesting things that are happening to
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provide flexibility in timelines. At the heart of it, initially, I have regrets my initial interactions with our institutional investors who were on the board was not great. If they would call, I’ll get to that when I get to it. I’m working on a customer thing. If they would ask a question, I’m not going to, you know, I’ll get to it when I can get to it. And that was the first couple years, after six months. I’ll never forget our first investor at the time, it was NEA, and they put in $15 million to the business. The first quarter, we had a good quarter, and they said, Okay, great. Second quarter, it was okay. We didn’t grow as much as we wanted to. And the the VC said, Dave, you know, I can’t remember an investment we’ve made where your balance sheet, you have more money in the bank two quarters in than what we gave to you. What is going on here? Start spending some money on sales and marketing and and so there was the start of spending more time proactively with investors on how to have combustible growth, what we’re going to do to take opportunities and risks to grow even faster. I think at the time, we believed we could get to the public markets, because our growth trajectory was very fast. We have a big Tam. This is a incredible market that has some of those valuable companies in the world sitting within it, and and we really believe perhaps that was the right path for us. But what we have found is that we’ve been incredibly consistent over the years. Our ARR compound annual growth rate for the last 10 years has been about 25%
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CAGR. We don’t always go that fast every year. Some years we grow faster. Some years we grow a little slower. It gets harder to grow faster with a larger denominator, but that has put pressure on the business to have a distribution and so what we did in the last round, we worked with a fund within Silver Lake, and.
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To not only fund the business, but also think about a secondary at that time. This was 15 years in, nobody had ever taken any money out of the business, and we had had great success for the business, but none of our and every single employee had ownership with options, and so you really have to navigate keeping the team motivated. We even had some Nick whether they were coming up on 10 year cliffs, and that’s an immovable object, you there is no sec, you know, variant to get beyond a 10 year cliff of an option grant. So, so I think what, what we realized, what I realized is, I’ve got to figure out ways to get distributions to the team. I’ve got to figure out ways to get distributions to our institutional investors, or show them a path of very consistent growth that’s capital efficient, and that’s really where we are now at this stage of our growth, none of our institutional investors have sold any of their shares. One our original institutional investor did a continuation fund kind of thing and transferred their shares to new view and kept the position in new view. But Intel Capital, Goldman, Sachs and now Silver Lake haven’t sold any shares. The pressure is coming for figuring out the next distribution with investors, that, you know, our job is to make them as much money as we possibly can, and that I really care about. We never try to be too greedy on the front end, front end evaluations, because I wanted everybody to be successful, all constituents. I also want the best for our employees. So we did it. You know, four years ago we we did that secondary and I think after you get to a certain size and scale, you either have to do secondaries or you have to recap the company every so often, with with with fresh money and fresh, fresh eyes. And that’s not too different than where we started. The discussion of really thinking about the business every three to five years, but I’ve been very blessed with the company that our investors have been patient and and we’ve been good compounders of the the growth of the business and the value of the business over that time. What do you think the future holds for you know, later stage, private market companies? Do you think the secondaries mechanism will evolve and improve in some way. Do you think there’s going to be, you know, pseudo public, private investment vehicles of some sort? You know, how do you think we might evolve there? Dave, the current public markets, you know, maybe seven years ago, 50 to 70,000,030 40% grower, 40% grower. Arr company could get public. That’s no longer possible right now for software companies, you really the if you talk to bankers, you need to be in the 300 400 million ARR range, with 1520, 20% growth. Say you’re going to grow 12 to 15, right? That’s the pathway. I think. Right now the system is really broken. I do believe I’ve seen a very smart set of secondary funds with that thematic come to the market. I’ve also seen mature funds be more open to secondary investments than ever before. I’m getting calls like that every single week, and that’s certainly a pathway the peas are looking for with their fresh capital, places to put it to work, that that have good upside and less risk. I think we’ve seen since, over the last three years, since valuations have reset and growth has reset. You know, the rule of 20, rule of 30, plus good growth, is what the PE firms are looking for. If you don’t have that, if they don’t think they can get there without a lot of heavy lifting, then they’re a little gun shy right now, it’s a tough moment in time to get a distribution. I really do think that we will have some new pathways. There are just too many private companies that are good companies, that are viable, that will continue to grow and can grow profitably. I think we’ll have either a new market evolve that allows companies from 50 to two 50 million get public, not through a SPAC, but through a more
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as we known it, traditional process, but one that’s more efficient. Citadel is working on a new market in Texas, I don’t know how much your audience have read about that. I’ve been watching that carefully, because we have too many companies that need to get to and actually a lot of public market investors then want access to this 100% asset class. They can’t get access to the asset class.
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Yes, so I think somebody is going to break the glass here is this now, glass ceiling of NASDAQ and NYSE, and create a new market opportunity for companies like science, logic and others probably in your portfolio, to get liquidity in ways that aren’t as secondary and aren’t PE I’m not sure what the final shape of that is, but I’m I’m watching that carefully. Dave, if we could feature anyone here on the show, who do you think we should interview and what topic would you like to hear them speak about? Well, in a perfect world, that would be Satya, the CEO of Microsoft, and because I your audience of technology investors and technologists, he has such great insight about what’s around the corner that isn’t obvious to all of us looking straight ahead right now, and he conveys that in a layman’s conversation that is so compelling and actually has shaped my my mindset. I mean, I think the thing that I love about Satya is he’s really shifted the company’s culture from know it all to learn it all.
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And he himself is a learn it all leader. And we talked about this earlier, I realized that if I don’t know if I’m not the best person, I’m going to go seek the best counsel, the best patent lawyer, the best finance team, the best investors, the best of the best. If something I don’t have good insight to, I’m going to seek the best of the best and learn from it, and then learn and and skill up. And Satya has really changed that company from a slightly bureaucratic, bureaucratic, know it all company to a learn it all company. And I really admire that that’s hard to do with a business that large. And every time I listen to a podcast with him, I just can’t turn it off. I want to I want another one. I want another one, right is, and especially when you talk about generative AI and the future of where that’s headed in five to 10 years, that is a great conversation. Dave, do you have any habits or behaviors that are a secret weapon? The secret weapon that I have, I try to stay and I’m generally a calm person by nature. I think that’s DNA and a little bit of luck. But the one habit I have is every day I wake up, no matter how shitty yesterday was, no matter all the things that didn’t go my way, no matter what ball didn’t bounce our way, I start fresh. I start so fresh, and I’m going to make today the very best day that it can possibly be. And as an entrepreneur, if you can’t forget you don’t forget it forever. But if you can’t disengage from that that went bad and start dwelling on it and dwell and dwell and dwell and and get into the mindset of would have, could have, should have. That is a very bad use of time. A very good use of time is making today great, solving today’s problems, tackling whatever are the highest sword order priorities today, and I’m really good at that. I do not get caught up in the Woe is me. I can’t believe what just happened yesterday. We didn’t get the renewal. After all, I just, I just missed the quarter. You know that that is what it is. It isn’t what we wanted. But what are we going to do to do to make sure that doesn’t happen again? Or what are we going to make sure to do that, that we get another renewal chance start small, solve another problem for the customer, and that I think I’m extraordinarily good at, and it’s not easy to be good at that. By the way, earlier in my career, I was terrible at that. I would incessantly dwell on that that didn’t go right. I would spend hours on that, hours of my day wasted, hours of my month wasted. You know, we can do that in personal relationships. We can do that in family relationships. We can do that in business. It’s very easy to go there. Yeah, I don’t do that anymore, and I feel better the company operates better when the leaders are not unrealistically optimistic, but are optimistic, relentlessly optimistic. And Dave, what’s, what’s the best way for listeners to connect with you and follow along with science logic? Well, follow me on LinkedIn, follow me on Twitter. And you know, I think the thing that is best is what you’re doing. Listen to podcasts. When you listen to podcasts, you really get to to know a person. You start to know how does their mind work? How do they think? How do they get to where they are? And I think those are the questions, kind of those fundamental questions I love to ask when I meet somebody new, tell me about yourself. How’d you get to where you are? How’d you get married? How did you meet your wife? How did you pick that school to go to? You know, what was it like growing up in that part of the world? And what I’ve learned in traveling the world and meeting with customers all over the world is this world is a lot smaller.
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More than any of us realize. It’s just incredible how many connections you have with people at a basic level that are very consistent, no matter what race, religion, belief system, part of the world they’re from. There are certainly differences, but there are, I have found there are more similarities than differences, and that, I think, is what makes the world go round in a special way. And you know why? Hopefully we find a way to get the world to more peace than where we sit today with, you know, some of these challenges that we find across the globe. I couldn’t imagine a better place to finish the interview, Dave, you’ve you’ve broken the rules, and you’ve done it your way, and you’ve had a lot of success through many different waves, and very excited to see what comes next in this new generative AI wave. So thank you so much for joining us. This was a true pleasure. Thank you, Nick, great to be on with you.
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You all right, that’ll wrap up today’s interview. If you enjoyed the episode or a previous one, let the guests know about it. Share your thoughts on social or shoot them an email. Let them know what particularly resonated with you. I can’t tell you how much I appreciate that some of the smartest folks in venture are willing to take the time and share their insights with us. If you feel the same, a compliment goes a long way. Okay, that’s a wrap for today. Until next time, remember to over prepare, choose carefully and invest confidently. Thanks so much for listening.
