Kumar Saurabh: Building Sumo Logic, LogicHub, and AirMDR and why immigrants make great entrepreneurs

Welcome to Inside the Network. I'm Sid Trivedi.

I am Ross Halladuke.

And I am Mahendra Ramasinghani. We have spent decades building, investing, and researching cybersecurity companies.

On this podcast, we invite you to join us inside the network where we bring the best founders, operators, and investors building the future of cyber.

We will talk about the hard parts of the founder journey, launching companies, getting to product market fit, raising capital, and scaling to an exit.

And yes, we will also be talking about epic failures.

But Mahendra, we're here to make the founder journey easier.

That is correct, Sid, but we cannot make it too much easier because startups are hard. And of course, you already knew that.

All right, YouTube, enough. Let's get started with this week's episode.

Our guest today is Kumar Saurabh, a remarkable innovator, a founder, an entrepreneur whose journey almost took a different path. A PhD, a potential academic trapped in the hallowed halls of some educational institution. But thankfully, instead, Kumar chose the road of being a builder, entrepreneur, and a founder. And the cybersecurity world is much better for it. Kumar's story begins at ArcSight, one of the pioneering companies in the SIEM space, or Security Information and Event Management, before it was even a category. Kumar joins as a software engineer at this pre-revenue company, and by the time ArcSight goes public, he has risen to the Director of Engineering. At ArcSight, Kumar led the corelations team, which was the technological epicenter of the company, developing sophisticated filtering, prioritization, data mining, and reporting engines that would become the backbone of the modern SIEM platforms. As the cloud computing wave began to reshape the technological landscape, Kumar saw an opportunity and co-founded Sumo Logic, serving as its Chief Technology Officer and challenging the traditional clunky on-prem solutions. Sumo Logic was taking the advantage of the cloud-native revolution, offering instant deployment, elastic scalability, and zero maintenance. Kumar was now reimagining how businesses approached data insights and deployment of cybersecurity offerings. Now, in his latest chapter, Kumar is riding the AI wave with AirMDR, his latest startup. As a co-founder, he's on a mission to bring agentic AI into the world of the SOC, or the Security Operations Center, empowering analysts and bringing AI-driven innovations to MSSPs, or Managed Security Service Providers. It's a bold vision, that promises to transform how we approach cybersecurity. And in full disclosure, Foundation Capital and I are investors in AirMDR. Across two decades of his entrepreneurial adventures in cybersecurity, Kumar has accumulated a wealth of insights. He represents the rare breed of a founder engineer who can build products that scale, adopting the latest technology offerings and delivering revenues as well as generating financial returns. Today, we'll dive deep into Kumar's journey, exploring his thinking, his insights, and his entrepreneurial spirit that keeps defining a new innovative chapter with every wave. Let us get started.

Welcome, Kumar, to Inside the Network.

Thanks, Sid. Thanks for having me.

So we're going to talk about a few different topics, and let's start with your immigrant beginnings. You studied computer science at IIT Kharagpur and graduated back in 1999. IIT alumni have gone on to found some of the biggest companies in Silicon Valley, from Zscaler to Sun to Nutanix to Cohesity and many, many more. What makes this group of schools such a hotbed for software and founder talent?

I think when I look back, first and foremost, getting into IITs, when I graduated, and this is probably like 20, 24 years ago, there are only 5 of them, right? And computer science batches are like 50 people. So I don't know, hundreds of thousands of people probably applied to get in. And so you have to kind of show up in the top 250 to get into computer science. So, so the first thing I would say is there is a, there is some, I mean, the selection is not perfect, but there is certainly like people who are strong in, you know, math, science, and engineering, things like that, get into that. So there, there is a first level filtering effect right there that comes in. There's a couple more things I would say. Brand is a big thing, right? So. Even though it's IITs or Indian universities, they're actually very well known all over the world, even in the United States. I benefited from that all across. The network is pretty strong, right? So when I started doing startups, I had people who had graduated earlier than me that were already doing startups, right? Like Bipul Sinha from Rubrik or Anshu Sharma from Skyflow, right? Both of these people are ex-IIT Kharagpur graduates, right? I personally knew them before I started the company. So you have a lot of those role models or people who have done this before. And, and one of the less appreciated things about it is being an IITian gives me a certain kind of familiarity in recruiting talent, recruiting engineering talent, right? So I can talk to any IIT computer science grad and there is a little bit of like that common background, that alumni network.

So.

Over the years, I have found like it's far easier for me to attract really high quality talent, maybe folks that have gone to IIT and things like that. So combination of all of those effects does help in a big, big way, going to IITs and graduating from there.

We had Slavic Barkovich on before, the founder of Dscope and Demisto. He talked a lot about Unit 8200 in Israel. Now that's a very, that's not a school. That's certainly a military branch within the IDF. Would you say that IIT has kind of similar value for founders from India?

I think IITs definitely have a broad, I mean, it may not be necessarily around cyber, but the quality of talent is really pretty high. And you run into IIT grads, IIT alumni in a lot of different positions. And the alumni network does actually help you quite a bit, right? So I can reach out to even Ashu, for example, at Foundation Capital, right? There are a lot of people, ex-IIT graduates, and there is something to that alumni network. People do help out, right? You can reach— I get random emails or LinkedIn, people reach out, and if they have gone to an IIT, there is a little bit— it rises above the rest, and you reach out and you try to help. And I have received the same help multiple times in my last 20+ years.

You moved to the US in 2000 to pursue a master's degree at Columbia. What convinced you to come here to the States rather than build a career in India?

So believe it or not, when I was in undergrad, I wanted to be a theoretical computer scientist, right? And I wanted to do a PhD, right? When you are like 24, you're pretty idealistic, right? And one of the professors at MIT, His student, Luca Trevisan, who actually went— was professor at Columbia, went to Berkeley, unfortunately passed away a year or so ago. I was his first PhD student. So he was looking for a PhD student. He reached out and I was delighted as anything because I had looked at his research papers and they were just pretty awesome research papers. But after a year into PhD, I realized that I'm on the wrong career track. I'll become a professor. If I keep doing what I'm doing and I like to build things. So a year or so after that, I kind of dropped out. So it was pretty much chasing that PhD in theoretical computer science is why I first came to US. It was only after doing one year of PhD, I kind of came to the realization that PhD is not where my heart is. And my, I, I'm like an engineer, a computer scientist. I like to build things. I like to use things that I build. And theoretical computer science was not very conducive for that.

Wonderful, Kumar. So you could have been Dr. Kumar, but you're Kumar, and we still love you for that. From Columbia to Silicon Valley, that's one shift that has occurred inside the United States. And then from India to the US, that's a big shift. You know, there's this theory about immigrants being founders, being scrappy, being hungry, and you see it across the board. What is it about immigrants that makes them, you know, the crazy ones?

I think there are a few things, right? One of, especially from India, I realized that I had the PhD offer, but I couldn't go for a semester because I didn't have enough money, right? So it's like starting a company and for the first time founders, right? You have to find a way to start something from nothing, right? And so I kind of worked for 6 months, saved up enough money for the air flight for the first month of expenses. I'll tell you, this is the resourcefulness. Right. Trying to stretch the dollar, right. Trying to get more done with less, right. Is like, whether you look at many of the stories from Jeff Bezos and whatnot, like frugality and being able to do more with less is a trait that's very useful, especially if you're going from zero to one, right. Because the resources are scarce. You still got to make progress. And I think that is like a character trait that people who immigrate, especially you know, let's say from India or so where the resources might not be that much. That's a big one. The fact that you leave a country that you have spent 23 years and are ready to enter a new country where you probably don't know anybody else, right, is another character trait, is you are ready to take a little bit of risk and jump into the unknown with a little bit of confidence that you'll figure it out. And startup journeys are like that, right? When you start a startup on the first day, you don't, I mean, you might have a plan, but you know, the plan will probably change along the way, but you still have to have the confidence that you'll figure things out along the way. And I think these are some of the common traits that become very handy when you're starting a company, especially from scratch.

One quick follow-up to that, Kumar, is that, you know, you make the leap to land here. There is also this theory about the soil is nourishing, you know, if the entrepreneur is the seed. The community, the culture, the legal framework. There are so many things about the United States that makes it very highly sought after for entrepreneurs. I mean, can you talk, can you flip the script on the other side to say what made you feel welcome here and how did you find your way into the first phase of your career?

I think that, that second bit is probably an even bigger influence, I would say, right? And, and I think even the difference between I mean, nowadays New York has a very thriving tech center and so on and so forth, right? But if I go back in 2001, there was a marked difference between, you know, the tech scene in Silicon Valley versus even New York at that point, right? And the fact that I ended up at a Series A company, right? Pretty much by chance. And to see that company grow and, you know, working with huge— Zomanzi was the CTO, one of the smartest people I know. At ArcSight, right? I was a kid straight out of school. So the ability to work with people like that gives you the confidence that you can actually step out and start your own startup as well, because you have seen the movie once or twice, right? So I think that experience, that opportunity to be part of startups. I mean, nowadays there are other parts in the world where there is a good thriving startup community, but I was extremely lucky to find myself from New York to Berkeley to back in Sunnyvale. At a startup that was a pre-revenue, pre-1.0 customer and almost like humongous amount of luck. The company almost died a year later, could not raise Series B, had a tough time raising Series B, somehow managed to scrap together a $5 million Series B. And then 8 years later goes IPO and a couple of years later after that gets acquired by HP. And I think there are 5 or 6 companies today in cyberspace that have come out from ex-Artite. And ArcSight was a small team, relatively speaking. It was not the scale of Google. So I think that opportunity to be part of startups is a big opportunity for founders.

You know, you talked a little bit about ArcSight. And so let's dive into your career. And you've spent the last 20 years, Mark, really building software for the security operations center. And all of that started at ArcSight, which you joined after graduating from Columbia. You're one of the first few employees there. And ArcSight really helped to create the SIEM, or Security Information and Event Management market. That whole category was built because of ArcSight. Why did you join ArcSight, and what was it like being in security 20+ years ago when everything was new, when SIEM didn't exist as a category?

So I think the reason I joined ArcSight, one, I got lucky because we were going through a downturn, and the big company were not hiring. So thank God, HP and Sun were not hiring because I wonder what my trajectory would have been if I had ended up at one of those companies, right? So I got lucky, is a blessing in disguise that it was going to market turn and happened to be VP of engineering at ArcSight reached out to me. I put my resume on some job site and within a week, right from the day I put my resume on the job site, I think I put it on Sunday, on Tuesday, I got an email saying, hey, very interested. Can you fill out this technical test? 6 questions. 2 hours later I turned around, sent, they're like, oh, looks good. Come by interview on Thursday. And on Friday they made a job offer and I actually accepted it on the spot. I didn't even look at the second, third, or fourth company. So I just loved the people. Like I interviewed with Hugh Jumanzi, couple of people, early employees at Oracle, just loved the team and the problem that they were solving. And I did not know about the cyber. So early days of it was was just going to various SANS courses, right? So I took GCIA and GCIA back when to kind of educate, and Artsight was very good in sponsoring those and training up its employees. Many of them had never been in cyber before so that we can start learning the basics of cyber and start breathing and living that life, right? So, so that way, that was how it felt very early on, and we're working with very early customers in the beginning. Intel was one of the earliest customers at ArcSight. Tremendous learning experience. And by the time ArcSight was at version 3.0, it was a pretty darn strong product. And right around that time, Gartner came around and they started kind of coining the term the SIEM security, and then it became a category. And for the next 5 years from then, ArcSight almost like was always like up and to the right on the magic quadrant for a number of years.

In 2010, Together with your former ArcSight colleague Christian Bitgen, you founded Sumo Logic, the first cloud-based SIEM. What created this opportunity in the market and what advice do you have for founders looking to identify which existing categories are ready to be disrupted?

So I get, I got very lucky. I mean, I felt, in last 21 years, I have felt it 2 times and the second time was just like a couple of years ago. I remember very vividly that Christian Biedgen and Stefan Zier, who was the chief architect at Sumo. So he was literally employee number 3 after Christian and I. All 3 of us went to a talk that Werner Vogels was giving, and he was giving a talk about this thing called cloud and how AWS do it. There was a company that, you know, you put a bunch of, you know, pictures together and they'll build a video out of it, put some music behind it. I even used that for my wedding. And they were running all in cloud, no cloud, no on-prem infrastructure. And the New York Times took something that would've taken $6 million and one software engineer because they could scale it and run it on, you know, 10,000 or 1,000 servers at a time, did that over a weekend in under $6,000. So it was a very compelling case that cloud is bringing a new kind of scale. And we used to say that ArcSite in a way was solving the big data problem,, but it was a scale-up strategy, a scale-up architecture, not a scale-out architecture, right? Nowadays, nobody does, I mean, very few people do a scale-up. Everybody does a scale-out, right? And so that was an aha moment is that, you know, we run into so many scalability challenges at Arc side. What if you could run a cloud-based log management, a cloud-based SIEM, and suddenly you get the scale of 10,000 servers? And all of that infrastructure and you take away the operational overhead. So it becomes easier and easier to operate for the customer. And on the backend, you get a tremendous amount of scale. And we knew that many of the categories, right? I wouldn't name names. Someone in 2020 asked me, how is it obvious that cloud is now going to be the main thing? I'm like, that was obvious 10 years ago, right? Because I mean, this is where you look at these mega trends. And you don't know exactly how the path will take in the intermediate 1-year, 2-year, 3-year, 4-year timeframe. But there is no doubt that in 10 years it is fundamentally going to change architectures, change product categories. And I said, I have felt it 2 times in my, in my career. And the second time, it's the same way I feel about AI. It's like what will happen in 2025, in 2026 might be up for debate., right? But if you look 5 years, 7 years, 10 years farther out, there is no doubt in my mind that it will fundamentally change a lot of product categories, including one that is near and dear to my heart, which is security operations.

You mentioned this kind of insight in recognizing the value of the cloud Kumar. Once you figured that piece out, why didn't you and Stefan and Christian just build this in at ArcSight? I mean, you had all of the scalability, the distribution. In 2010, why didn't you try to build it in?

Without getting into too many details, who says nobody did, right? But this is the classic, you know, this is amazing, right? There is a very great book, Creativity, Inc., Ed Catmull, maybe I'm butchering his second name, right? But he talks about a hungry beast and an ugly baby concept of this, right? So a hungry beast is the part of the business that's working well, right? And ArcSight was a hungry beast, big sales team, million-dollar deals, right? Commonplace. Now you go in and say, I want to do this small little thing in the cloud. It's like, why would you do it in the cloud? Nobody's asking for cloud, right? In fact, 99 out of 100 people will tell you, don't do it in the cloud. It's like, we'll never put data in the cloud, right? So it's basically the ugly child is the ugly baby has to be protected and given enough oxygen to grow. And actually very many large companies, quite honestly, suck at it, right? They accidentally suffocate and starve the ugly baby. It never gets a chance to even become a teenager. And so guess what? You know, that's why I love the Bay Area, the early stage VC and funding infrastructure that is like, hey, if you have an idea of an ugly baby, people take the risk, right? And sometimes it doesn't work out. Sometimes it does work out. So that was the reason. And I've seen that movie play out more than once, right? Where there is a fabulous idea, a big company could have done it, but somehow they never are able to execute very well because they don't fund it. They don't create a protective area around the ugly baby. So give ugly baby enough time to grow up.

And so Kumar, how big was Arcsight when you decided to make this leap in terms of headcount or such?

I think I joke that I have never worked at a company for more than 6 months that's larger than 500, 600 people in my last 21 years. So I would have to guess that it was right around the time where I was thinking 600 people seems like too big a company for me. Things are moving very slow, not as innovative as it used to 3, 4 years ago. And it's not like it happens one sudden day. It's a frog in the boiling water kind of thing. Till one day you wake up and realize it's too darn slow and not innovative enough. And then once some creativity spark goes off, you're like, okay, I gotta step out of this and kind of start things from scratch.

So I think your threshold is the 500-ish mark and you get to kind of jump out at that point.

I think it's not the size of the company. I tell people that impatience is both my feature and my bug. So I'm not a very patient man. And over time I have grown comfortable with that is like when people say, oh, it can be done in the next week is like, what's wrong with tomorrow? Right. And when you ask that question, a lot of people get like, no, it can be done tomorrow. And 9 out of 10 times, if you don't give them a choice, it has to be done tomorrow. And they kind of take it that it's not changing. It has to be done tomorrow. 9 out of 10 times, it actually gets done tomorrow. So, so I think the bigger companies kind of start to lose this a little bit over time, bit by bit, bit by bit. And when it becomes too much, that's the trigger where I go like, why does it take 2 months to do something that can be done in 2 days? And that's, that's one of the telltale signs where I'm like, okay, something gotta change.

And so now you made a leap, you are starting Sumo Logic. I mean, give us a sense of What was the starting journey like? And then what was Sumo at scale, you know, at its peak, customers, operations, servers, et cetera? I mean, give us a sense of that journey from start to its peak.

So I was there for the first 6 years, right? And I think Sumo went IPO in 2020. And if I remember correctly, it got acquired, a PE firm, a couple of years later. When I was there, you know, we were probably doing $40-50 million in ARR. Had, I would, I would probably say close to 1,000 customers at that point. Right. And so I look at this as 3 2-year— my 6 years with Sumo, I split that into, I mean, there was a period, 6, 9 months of the ideation and getting to the point where we start the company. But the couple of years was after that was really building this scalable platform. And then 2 years after that was perhaps the most interesting time period because the early batch of salespeople had come on board., right? And we are starting to onboard customers and the platform and even the cloud was so new that for every 8 quarters, every last 2 weeks of the quarter, I did not sleep all night, right? You're lucky if you get 3, 4 hours of sleep because at 4 o'clock in the morning, something breaks, right? And your pager goes off, you hop on Slack. There are another 5 engineers up at 3 AM and we are trying to fix— it was colloquial, you know, we're fixing the plane while we're trying to fly at faster and faster speed. So that was a great learning experience in terms of not only seeing the business grow, that was one interesting aspect of it, but also the other interesting aspect was how do you take a system that was meant to run 10, 20 customers and scale it 10x, right? In a couple of years or more. And that was a great technical learning experience. And the couple of years after that, the last 2 years was more of a management And I, I actually put a couch in my office because my job became calming people down and stopping them from killing each other because they had a technical argument. In the heat of the moment, those arguments look big, but if you step back, you know, how do you resolve those conflicts? How do you get a group of 100 very strong engineers to work together? I mean, that is a challenge I actually quite honestly enjoyed for a couple of years, but after that. You know, I, I'm more of a builder, whether it's product technology or a company builder, and not as much— I can do management for a little bit. I enjoy that in small doses, but when that becomes 90% of your job, that's not the ideal fit for me.

Yeah.

And Kumar, I think you're one of the rare technical founders who has built things that have scaled very rapidly. For our audience, What are some lessons they should keep in mind as they themselves are building their startups? This notion of designing to scale, what are some things that they need to be very, very thoughtful about?

There are a lot of— I think Google has a pretty tremendous engineering culture, right? And I have also seen companies that don't have the culture and that crumble under the technical debt, right? So if you ignore the technical debt, it grows on you, right? And, you know, Christian and I, Bruno, we many times had, you know, headbutting with our CEO because we're building a lot of feature functionality that the customer wants, sometimes at the cost of not investing enough in the platform, right? And as a CEO now, when the shoe is on the other foot, I have more appreciation for you gotta invest in the technical debt. You gotta invest in the underlying platform. Perform, and somebody has got to champion for that. Another thing, another thing that I would say is like the rigor, and I think the rigor around even things like root cause analysis and so on and so forth, and you're constantly rebuilding the underlying platform. There are some components of the system that we had to redo every year, right? And so we were on V4, V5 of certain components of the system because you scale it 10x And the workload increases another 10x.

Kumar, I want to move over to the topic of GenAI. And you talked about these kind of two cycles that you have seen in cloud, and then obviously what's happening today with GenAI. You've certainly started your third company now, AirMDR, and that was something you founded last year. And I've been fortunate to work with you on that journey. What was the reason behind why you decided to go and build AirMDR? What was this focus on? You know, building an automation-first MDR? What motivated you to kind of say, hey, this is where I want to spend my time for the next decade?

So for a long time, even as an undergrad, I did AI, but AI at that point was minuscule, right? Trivial compared to what is possible today. The scale at which you can build models, all the infrastructure is there today, right? So it's a very different, it's almost like a golden age for the AI. Right. And so, but I always believe that whatever people can do over time, machines will do it better, faster, cheaper than people. And I am perfectly comfortable with that outcome, right? If I have to go 5 miles, I would rather drive. There is no pride in me running. I can never outrun a car. I'd rather drive a car. And even better would be a car that drives itself, just gets it me from point A to point B, right? So I fundamentally believe in that, right? And 5, 6 years ago, I started— automation was the best you could do, right? But you realize that automation is not like— there was a category called SOAR, and I say tongue-in-cheek, there is no I in SOAR. There is no intelligence in SOAR. So someone intelligent has to tell SOAR what to do. And when AI happened, right, it was not just about the language models, but what the language model kind of showed a peek into the world where you can build this AI agent that can actually— AI agent is the vessel of that intelligence. And the UX is much better, right? So you can now— it's not some neural net that you don't know how it works, but it just works, right? No, these days. The models can actually converse in natural language with you. So the UX has become much better and the intelligence has gotten much better. So I really think that, you know, various AI agents, and this is what I believe that will happen in next 1, 2, 3, 4, 5 years, is that AI agents will actually be able to do 60, 70% of the work better than people that are doing that today in the whole world., right? And it will be a journey to get to that point.

Yeah. I think you talked a little bit about AI agents and leveraging them in the SOC. There's several companies that are kind of doing this in cyber. I mean, there's probably 15+ companies. What are you doing that's different? What did you see and you said, hey, this is what the world is not doing, similar to the way you figured out cloud-based SIEM was the future with Sumo?

Right. So I think there are a couple of things, right? Just like at Sumo, right? I remember in the early days, there was a very large bank. I think it was UBS or something. They call us one day and I happened to be the sales guy, the CEO, the two co-founders, we were all in one, my office, right? Happened to be there. We took the call, the UBS guy who says, would you run your software on-prem and we'll write you a very big fat check. And the sales guy just hung up. Uh, thank you. See you later. And we were all delighted that the sales guy was able to walk away from a very big fat check because he understood that the whole point of the cloud is to not run on-prem, run it as a service. The whole point of this AI agent, I believe the ultimate form is to run the AI agent as a service, not as a software that gets deployed in other people, but just do the entire work end to end. I believe that is a far better model. One, it's a far better model for the customer because when I talk to customers, 80, 90% of the customer is small to medium-sized customer. Customers just want the problem of detection response to be taken care of, right? Now there are 1% of the very large companies and I think they will continue to buy software, just like there are still people today that would only deploy things on-prem. But I think many of the cloud companies have shown that you can build a very large company being purely cloud, right? And so the approach that we are taking, we fundamentally believe that it's better for the customer. And more importantly, when you own all the different layers of this stack, right? The data, the detection, the triage investigation response, the people, the processes, you can integrate that much more tightly than if 90% of the stack that you need to operate is owned by some other company that moves very slow and you are expected to produce the results, but you only own 10% of the stack, right? And so this is One of the fundamental differences from almost every other company that's working on the AI agent for SOC, they're mostly doing it as a software and we are doing it as a service and we are delivering detection and response as a service for small and medium-sized companies. And medium-sized companies could be 5,000 people strong.

And by this you mean you're not actually exposing the agent to the customer, you're exposing the end result as a service.

Absolutely. So we are delivering the end result, but we don't put the onus of training, making sure that the virtual analyst is actually working and working well on the customer. We take that on our part. We do provide them visibility. So we are, we believe in 100% visibility to customer. You can lift the hood, look under it, but at the end of the day, who owns the responsibility of making sure AI analyst works really well? It's not the customer. The provider, it's the builder of the AI agent, and the customer gets the outcome. And the outcome that they expect is detection, triage, investigation, response as a service.

In the Bay Area, there is a lot of excitement about AI and its potential to transform security. However, outside of the Bay Area, many companies are more cautious or even skeptical. From your perspective, how does the view of AI in cybersecurity differ between the Bay Area and other regions?

Yeah, that's a, that's a very interesting question. My experience has been that there is something, something either good or bad in the water in Bay Area because there is a heavy degree of optimism, right? And some can even say like unrealistic amounts of euphoria around AI, some of which might be a little bit too far-fetched. On the other hand, right, I've been to— not to pick any place, but I did happen to go to Dallas, couple of times in October. And at one of the dinners, not only people were not believers in the AI, but they were almost skeptical, right? And I think what changes that is a bit-by-bit journey. Like seeing is believing, right? Like if you read a research paper on ChatGPT, you would not believe it. But if you could log in and you can actually get your hands on the keyboard and use ChatGPT, then you'll be impressed., and you'd be wowed. So a lot of that has to happen in the space of AI. The more people become familiar, right? I own a Tesla and I was very skeptical about self-driving till I started using it, and I could notice a change in my own mindset, how well the technology is improving, right? And it's probably, it still needs more work, right? But you can see the progress. And the same thing is happening in AI and cyber as more and more people experience it. They'll become more of a believer and less of a skeptic. And security people are skeptical by nature, right? So that's their default, that's the place where they start. And I think healthy skepticism is good. And I think as they get more hands-on familiarity and they can see the outcomes and the value of AI analyst or application of AI in cyber work and deliver results, that's when they will start changing their opinion.

I think, Kumar, there's a great observation there between geographies, adoption curves. And I want to go back to that part where you talked about Sumo Logic, you're catching onto the cloud wave, but there is this big legacy part that is trying to say, well, can you do this on-prem? And you guys are strong and disciplined enough to say no. Now take that same analog for the AI phase that we are in. And where is the resistance going to come from? How do you break across that resistance?

This is such a wonderful question. We just saw So we did POC with two very large SOC teams, right? One, one had 30 people, one had 80 SOC analysts in the team, right? And one team is full on, they believe in the world where AI analysts should do 80, 90% of alert triage, investigation, response. So they're full into that and they bought in and they're all in there. In the other case, we showed them the technical win. We showed them what was possible with that. But instead of investing in this technology, they went and hired 13 more people on that team. And so this is the inertia, right? Is like, this is why I believe doing it as an MDR has an advantage because even when you give them the technology, show them how it works, show them the outcomes, changing the organization to work in different ways, changing 30 people's mindset, changing the processes, is not something that every company can accomplish. And that is another reason why we are doing it as an MDR, because time is of the essence. I would want this technology to be in hands of as many companies as possible in couple of years, as opposed to taking 6 years to get there.

You know, that's a fascinating observation that between 30 and 80 analysts, one of them is just grabbing onto everything that you have to offer, and the other is saying, Well, we'll go and hire more people. Or if I use the horse cart versus car analogies, like we're going to buy more horses. It's not going to help you to get to your destination faster, unfortunately. So there's going to be an interesting shift here that occurs. This is your fourth startup, Akbar. When you look at the company that's gone public, companies that got acquired in your past, you've done it all. What keeps you excited? What keeps you going? And where do you find your mojo?

I think I honestly find making a little slice of future, being able to see it and then make it a reality in a few years, right? It's a pretty, pretty satisfying thing to do. Right. And, and luckily, you know, there is always every few years there is some new technology so you can move the envelope forward. You can get a little piece of like, and I understand certain areas right around data, around data-driven operations, SecOps, DevOps. These are the areas that I understand. And whenever that opportunity presents where you can take, or you can imagine a much better future, and then you get the opportunity to work on making that vision of the future, make it a reality. I think I find myself blessed that I get paid for doing that, right? In a way, it's like, it's an incredible role. It's an incredible opportunity. So As long as I keep finding opportunities like those, I keep working on those.

So just to flip that around, Kumar, what's your biggest frustration or what do you find holding you back?

I think the part of it is it's constraints and I think it's a healthy— I think I almost feel like constraints breed creativity. I do believe in that. And I think it's not— there are very few things actually genuinely get me frustrated. Right. So it's like, You know, 999 out of 1,000 things are solvable, right? And very rarely are there things that are truly that frustrating, right? So there's maybe that's just the personality type is like, it takes a lot to get me frustrated. I think what gets is how do we get hundreds and thousands and tens of thousands of the customers to kind of go along? That is probably, I find, as the hardest challenge, like building the technology and Showing it in the smaller parts, but getting a whole industry to kind of move in a certain direction. Once you see it happen, it's very fulfilling to see that, but that's also probably the most challenging part of it.

As we go into our last section of this podcast, let's talk a little bit about lessons for founders. And, you know, one of the things I've seen you do really well working closely with you in AirMDR is you have this truly unique superpower in recruiting talent. And that talent includes both finding, you know, high-quality co-founders to join you, having individual engineers joining you, individual sales leaders. You're just fantastic at it. You can convince people who haven't even thought about joining a startup as early as this to come and join. What advice do you have for founders, particularly first-time founders who are looking to hire that critical employee or convince a co-founder to leave their job and join them? In a startup? Like, how do you do it?

Yeah, I think that's, you know, there is a little bit of, you know, meme or debate going on this whole founder mode and manager mode and things like that.

Right.

And I think I come at it from a more nuanced perspective of it. Right. You have to, at many times people say, hey, it's your company. Right. And I think you, as a, as a founder, it's a first-time founder. It's a little bit of like, it feels good to say it's my company, but it really takes a lot of people to build a company, right? So, so the first of all, it's realization that you want other people in the tent and you're ready to give up your Legos, right? If you are going to hold on to all your Legos, then you're constraining the kind of people you're going to attract, right? Because other people want to play with Legos as well, right? So part of it is to figure out which Legos you should give, but whenever you give up the Legos, I mean, the art of the delegation is you are still responsible for the results and the outcomes at the end of the day, right? So how do you strike that balance of giving up? So I'm not a big believer in like micromanaging and controlling everything. On the other end, I'm also not a believer in just get letting the reins, so lose track of the script, so to say. Like you still have to own the accountability. You still have to be close enough so you know when to step in. When to pull in. So that's a fine balance, but that is one of the things. And the other part that— so it starts with the first part of it is willing to give up parts of the company, parts, big pieces, impactful pieces of the roles to other people, right? Trust them to do the right thing and bring them in. The other part that I would say during the interviewing process, right? You're selling, you're also buying, but you're listening, like Any, like most of the sales processes, they have a discovery phase at the very beginning, right? And many of the salespeople, Rick, when I used to go on the sales call, it's like, I want to pitch you what I'm doing as opposed to asking questions and learning, discover. And over time you change your approach. And in the recruiting phase, if you listen carefully and you ask questions the right way, people will tell you what, where they want to go in 2 years or 5 years, right? And then it becomes a collaborative problem solving exercise. Can we get you there here? And how do we make this the best place that you can get? And once you problem solve with those people, 1 out of 10 times you can't make this the best place for them and you won't be able to close. But 8 or 9 out of 10 times, if you go through the process, listen carefully, do the discovery, figure out where people want to go and find that opportunity. And when you find the opportunity that requires giving up the Legos, be open to giving up the Legos. If you do all of those things, you can probably recruit pretty awesome talent.

Maybe a follow-up to that. I mean, most of the time founders aren't actually recruiting from other startups, they're recruiting from larger companies. So the difference is, you know, you're trying to convince somebody to leave their cushy job. What are the things that you use to try to convince those folks? I mean, obviously they recognize that they're not going to get paid as much and they recognize they're going to get real equity, but what's the piece that actually convinces individuals to say, hey, I want to go and do this much earlier.

Like, look, what I believe is that it's a game of self-selection, right? And I think if you want a nice cushy 9-to-5 job, you should probably work at Intuit, right? Or there are many companies where, you know, it's a very— nothing wrong with that. Like, look, I do not judge that, right? That's not for me and that's not for anybody who wants to join a startup, right? And so you can— it's not wrong for someone to say like, look, I'm looking for a Monday to Friday, 9 to 5 job. That's okay. You should go somewhere else, right? I do not try to recruit those people at all, right? I try to recruit those people who are like, who are looking for something more, who are looking to make a bigger impact. And people who have that itch, they might have been working at McAfee, they might have been working at Google, and they feel like they're a tiny cog in this huge machine, and what they do does not make an impact. And if they are talented, right, those are the people that you can very easily attract. Right? Because at startups, you're pretty much the maker of your own destiny, right? And what you do actually has a very immediate impact that you can see. And a lot of people find that very exciting and attractive.

What happens when you hire someone who is not a good fit for a startup? I know there are plenty of talented people at large corporations who have a very romantic idea of what working at a startup would look like. Many are used to having a lot of resources at their disposal. Large budgets, great teams, and many may struggle without having such support at a startup. How have you navigated this problem and has that ever been a problem for you?

I know within less than 90 days, more like 30 or 60 days, if I made a mistake, right? If someone passes the filter where I figure that out after they join, I ask myself a really hard question is like, that's a mistake I made, right? And I do make those kinds of mistakes, but the chances I made those mistakes have gone down drastically over the years. And the way of this is I own, I own what working in a startup is like, right? I don't expect people to work 110 hours, right? It is sustainable pace, but, but it is, it is going to require, like, I will, I tell people, engineers who join, if your product doesn't work on a Saturday or a Sunday or on Thanksgiving or on Christmas, I will call you., right? And I expect you to pick up the phone. If that scares you, you will run. You will not come back for the next day interview after that, after hearing me clearly tell you that, that I, I have no shame in that fact that I will call you, right? So, so part of it is like, it is what it is, right? I'm brutally honest about it. I try to give people a dose of reality before they join, and it's not for everyone. And it is for a certain group of people that just love, I mean, I have worked with people who have worked with me, like there are people at Sumo who've been there 12 years. There are people at LogicApp that joined in early and left the day we sold. So I have found people that want that and they work through that for years in very, very hard situations. So it's about self-selection. There are startup people and there are big company people. Big company people should go to big companies and startup people should go to startups.

That is a very rational and a very wise way of looking at this. So question for you, Kumar, you've worked in the past with 4 of the biggest brands in enterprise infrastructure investing. You worked with Greylock, with Sutter Hill, Sequoia, and Accel. How much does the brand of the firm matter when a founder is picking a VC? And how do you balance the firm reputation with the individual partner you're going to be working.

It's very funny because we started this conversation talking about IITs. IITs have 500 graduates from each one of them every single year, right? So there are probably thousands of IITs, right? If you actually mapped out like where different people of these are, there is a humongous amount of variance, right? But I think it's a signaling, right? If you had a 5.0 or a 4.0 GPA from MIT or Stanford, that does say something, right? So, so brands and institutions have a certain signaling effect, right? So that, that is a fact, right? On the other hand, I think I always believe that at the end of the day, you work with people, you work with partners very, very closely, board members, right? And they, they're part of your team, right? And I think they're part on your team. They are board members, right? So I, I think I would put a whole lot more value on the person that you're working with. You know, how much did they go out of their way to help you either make introductions to customers, other investors, other executives? I have seen firsthand how, you know, board members can be super helpful in attracting and recruiting really high quality, very senior talent, both at Sumo, in prior companies. Even here at AirMDR, working with Sid and all of that, right? So, so I do think that brand does matter. I would probably put 20% of the weight on the firm itself, but 80% of the weight I would put on the person from that firm that you're working with, because that's the person that you are spending a lot of time, sometimes every week.

You know, speaking of, uh, the IIT networks and how these networks have proliferated, uh, how they've gone on to become successful founders. One question that comes to mind, Kumar, is that now imagine you have completed the journey with AirMDR, okay? And there is a young immigrant who just landed at the shores of this great country and is asking you for advice. What are some top 2 or 3 pieces of advice you'd give to somebody who comes in, in terms of building their career, entrepreneurship, and achieving success?

I think on the founder side, right, I think I would give a meta advice is there are a lot more people that have been down this journey before you. And I got this advice maybe in 2004, 2005, right? As a young engineer, I wanted to build everything. And one of my managers said, Kumar, you can go online and check if somebody has already done it. And 8 out of 10 times, 9 out of 10 times, other people have done it. And in the founder kind of a stage, if you're a first-time founder, there is a lot of things to know, but there are also a lot of people who have done that journey before you, right? And people are generally super helpful if you reach out to people and people will take the time, give you 30 minutes, give you an hour. So one piece of advice that I would say is reach out, ask for help, genuinely ask for help and. Starting the company and all of that, that's probably, you know, there is a ton of material on even on YouTube, on podcasts like this, right? You know, you listen to different people's journeys and different decision points that they had to take. So there is a lot of information out there, but one piece of advice would be to, would be to reach out to people who have been down that path before you. And even if one or two people are willing to help you, that can be immensely powerful in terms of guidance, in terms of mistakes to avoid, in terms of questions to think through and make your own decision, but they can give you a framework because they've seen the movie before. If you have seen the movie 3, 4, 5 times before, you can actually predict, okay, here are the decision points you're going to face. And that advice, I get that from board members, investors, other senior people in different kinds of roles. So I find a lot of value reaching out to people and asking for help, advice. But again, at the end of the day, you gotta own the decision. You gotta make your own decision, but getting different pieces of information and input is super helpful.

I couldn't agree more, Kumar. You know, we, we live in a time and a geography that is very interesting. America as a country has been, you know, kind of the landing pad for entrepreneurs from across the world. And what you touched on has been sort of the DNA or the fiber of this country's entrepreneurial zeal is that somebody who is successful is always willing to help, is always willing to engage and give back in a meaningful way. And I think that's what makes our journey also very special. You've done this now 4 times, right? ArcSite, LogicHub, Sumo Logic, AirMDR now, and you continue to not only inspire other founders, but also help them behind the scenes in your own way. So we want to say a big thank you to you for being such a positive force in the world of cybersecurity. Innovations, entrepreneurship, raising capital, building teams. I mean, these are not for the faint of heart. And the fact that you continue to do this each day and every day is a big source of inspiration for a lot of us out there. So thank you, Kumar.

This has been a lot of fun. Enjoyed this discussion. So thank you for having me on. And it was a wonderful conversation.

Thanks, Kumar.

Thank you, Kumar.

Thank you for joining us Inside the Network.

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