This week on Founded & Funded, Madrona Partner Vivek Ramaswami talks to Jack Naglieri, Founder and CEO of 2022 IA40 winner Panther Labs. Jack founded Panther, a leading cloud-native security information and event management platform, because he had experienced first-hand the threat-detection challenges companies have at cloud scale. Growing frustrated with the compromises required by traditional SIEM platforms, Jack took his experiences from Yahoo and Airbnb and set out to build a solution that detects and responds to suspicious activity in real time.
In this IA40 spotlight episode, Jack shares where the inspiration to launch his own company came from – hint it was from a cold email he received. He also breaks down why he decided to take the leap and become an entrepreneur and what it’s like transitioning from a software engineer to a founder and then to a successful founder. Jack also shares details about what it takes to land – and keep — your first customer and provides some advice about how CEOs should be the only ones learning on the job. But you’ll have to listen to get all the details.
This transcript was automatically generated and edited for clarity.
Vivek: Hi, my name is Vivek Ramaswami and I’m a partner at Madrona. Today we’re excited to have Jack Naglieri founder and CEO of Panther Labs, a cybersecurity startup, reinventing security operations, and taking a modern approach to detection and response at scale.
Welcome, Jack. Thanks for joining.
Jack: Thanks for having me.
Vivek: Well, maybe just to get started. Would love if you could share a little bit of background on Panther Labs. What was the founding story? What got you excited about modernizing security operations? How did you get into all this?
Jack: Yeah, it’s a very non-traditional founding story actually, and the gist of it is that an investor found me when I was a security engineer, reached out to me cold via email, and I just responded and decided to quit my job and go pursue it. That’s the very short version. The longer version is, I was part of the team that open sourced this project called Stream Alert. I was the main architect. We built it as an alternative to traditional SIEMs, like Splunk, Sumo Logic, Elastic, and the reason that we decided to build, which is typically the wrong thing to do, to be completely honest. I do not recommend this at all. But we built our SIEM because we really wanted three things. We wanted to be able to operate at a very high scale with a very small team. We wanted to use developer-oriented principles, like detection as code, which we really laid very heavily into that platform. But we wanted, CI/CD, we wanted the automation that comes with developer workflows. And we really wanted higher reliability, and accessibility, and we wanted more control. And then we really wanted structured data. We’ve wanted to put data into a data lake, and we wanted a, just a more formally mature way to handle petabytes of data.
We have failed for so many years as security teams putting this into a tool like Splunk. We’ve just dug ourselves into this hole. The good news is that there’s a ton of alternatives to using something like Splunk, right? You can use data lakes, you can use cloud data warehouses, and there’s so many today. At the time when I was a security engineer, Snowflake really wasn’t a popular option yet. And even Athena, which was the data warehouse on top of s3, was still fairly new as well. So these were really early concepts, but the thing I learned at that time was the phrase security’s data problem. I always think I’m the first person who said it because as soon as I started saying it publicly, Splunk started copying me, which I thought was funny. But, it’s true, right? You need to have really strong data principles for security to handle the scale, but to get value out of your data as well. And that’s more of what we’re really leaning into today. So the work I did there got the attention of some investors, one in particular, actually two had emailed me. One, I just completely ignored. We talk about it, and we’re cool now. But the other one ended up incubating the company. I hired some early engineers, and then I went out and raised money, and got a bunch of “Nos” and then eventually someone was like, “Yeah, we’ll do your seed round.” We raised our A from Lightspeed and our B from Coatue and yeah, it’s been fun. It’s probably the hardest thing I’ve ever done in my life. But it’s been super rewarding, super challenging, I’ve learned a lot, I’ve grown a lot, and I continue to — it’s never dull moment.
Vivek: That is what we hear a lot from founders is — super challenging, super hard, but super rewarding and can’t do anything else. It’s always both right.
Jack: I feel like life is kind of like that in general. if you want to, learn about yourself, you have to challenge yourself. There was a phrase that I heard recently, it was if you want to reach your limit, you have to train at your limit. You gotta do the work and you gotta figure it out, and you have to push way beyond your mental limits. Obviously, there’s a balance in startups, you don’t want to just run at your limit forever, because then your performance begins to degrade, so the rest balance is hard. I’m pretty bad at it to be honest. I’m getting better. I should rephrase and say, in the past, I was pretty bad at it, but now I’m getting better.
Vivek: Well, I was gonna ask if you’ve always been that way because you were at Airbnb between 2016 and 2018 when the company was probably growing and scaling like crazy, and there’s probably all sorts of challenges associated with that, security and otherwise. So what were some of the lessons that you learned from that experience, both personally and professionally?
Jack: Yeah, Airbnb was amazing. I just love the founders and I think that they’ve done a really great job of building a great culture and really instilling their roots of design into the company in every way. I have nothing but respect for Brian, Nate, and Joe. I took a lot of lessons away from Airbnb that really allowed me to begin to understand what it means to build a startup.
So I thought about this question and I came up with three things. The first one I came up with is, don’t fear the unknown. And don’t worry if you get it wrong on the first try. When I joined as an engineer — that was actually the first security engineering job I ever got. And prior to that, I was just an analyst. Being a security analyst is very challenging for a lot of reasons, but it doesn’t really set you up to have a great career because all you’re doing is you’re looking at data all day. And at a certain point, it becomes less effective for you to look at it manually and then you have to start automating. And that’s the type of work that I was doing at Yahoo because I realized that at a certain point, I was just unable to do my job effectively. So I sat with the DevOps engineers, and I sat with the security engineers and I was just becoming a sponge. I was like, just teach me everything. That’s one example of really not fearing the unknown. You know, you have to push yourself out of your comfort zone a little if you want to grow. So that pattern continued at Airbnb, but even more so because I was hired to build a lot of security tooling. And Airbnb was a completely different environment.
But you know, the core was the same. A bunch of cloud infrastructure, a bunch of systems to secure, let’s go figure out how to do it. But this time, all in AWS. Yahoo was this massive on-prem shop as you know — they were 20 years old at that time, so diving right into AWS, I didn’t know anything about the cloud. I just kind of went in and started building, and I made mistakes and then I corrected them. So the mantra of fail fast is really important, and with fail fast, you have to learn from it, otherwise, you’re failing continuously. So that was, that was one.
The second one is, to learn to thrive in chaos. Just because something isn’t perfect doesn’t mean it’s not effective. I think as engineers, we have a tendency for perfection where we’re like, okay, it needs to be this way, it needs to be nice and neat. My classes need to be perfect, I need comments, all these things, right? But, the thing at a startup is that nothing needs to be perfect for it to be successful. When you join a startup, you have to keep in mind that things are chaotic naturally because no one has been responsible for the sliver of work that you are now responsible for. You have to train people into thinking like that. Like you were brought in to make this thing good. It is bad. That is natural. That’s how this works. You know, we are giving attention to it and we are bringing you here to make it great. So that was one thing as well.
And then the last one is don’t be afraid of taking ownership and effectively being the change that you really wanna see. In startups again, because there’s a lot of things that have never been focused on before, it’s really your job to be an owner, and that’s one of Panther Lab’s company values is being an owner. Customer love, be an owner, take care of the team — those are our three. And ownership is so important because it’s around if you see something and it’s important, just take ownership and you’re like, “Hey, this thing just had to get done, I went and did it.” And that’s exactly the type of mentality you need in a startup because again, things are very chaotic. You’re trying to figure out a bunch of things all at once. It’s very much building the airplane as you’re falling off the cliff. And the type of people who are self-starters and growth-oriented are going to allow you to both visualize what the plane needs to look like and then make it happen, just do the work and get to a very different state, and then you have new problems.
One of my favorite quotes from one of my investors is, “We only make new mistakes”. It’s the same mentality. Learn from where you’ve come from, use it as a really key source of input for your next move, and don’t make the same mistake again.
Vivek: For you, going from engineer to founder, first-time founder, from a place like that, what were the biggest challenges? What was the lightning bulb for you to decide, okay, I’ve got the product idea, now I just got to go do this.
Jack: Oh, it was total ignorance. I’ve been asked the question before, it’s knowing what you know now, would you have still done it? And the answer’s yes, but oh my God, I had no idea what I was getting into. Airbnb was the first startup experience and working in a startup as an engineer and running a startup are completely different universes. But, you get some of the same elements of urgency. Urgency and ownership are similar, just as a founder, it’s a hundred X is hard. Not to say that being an engineer is not hard in a startup, but it’s just very different.
As an engineer, I was just really excited to keep working on that problem. And engineering was one of those things I was just so continuously intrigued with. One of my biggest strengths is in orchestrating things. I’ve always found myself to be really good at, if you have a bunch of objects in a space and you need to organize them in a certain manner, how do you put them together to have a good outcome. My mind has just really excelled with those types of things. So an example of that is when I got into DevOps. DevOps is this idea of can you deploy a configuration onto a hundred thousand machines that are all different? And it’s a very hard orchestration problem, but it’s really fun because then you have to figure out, your mind has to work in very interesting ways, where you’re like, well, what is the state of this machine when I go to it? And what is the state after and how do I make sure that’s reliable? And there’s all these edge cases, and building a company’s very similar. It’s very orchestrative movement where you’re saying, okay, we need to figure out what product to build. We need to hire the right people. We need to really put them in their most powerful positions to where they’re engaged, and they’re using their strengths and their gifts to push us all forward collectively.
And you have to coach them and guide them and make sure their heads in the right place and focus them and it’s a very similar mental model. So when I decided to start the company, it was really just, I wanted to keep building because I knew that the work at Airbnb was really just the beginning. And going from being a software engineer to being a founder with zero business experience. It’s been a crazy journey. And going from being a founder to becoming a successful founder it’s like going from being the water boy on the football team to being the coach. And doing that in a year. That to me is the level of growth that you have to go through to be successful in that role. And then you have to continue to be the best. You have to continue to learn from the best and do the things that people who are the best do. And it takes a lot of growth. It takes a lot of the right contextualized knowledge, and it takes the right people around, you coaching you.
I was actually talking to another founder this morning because we were working out together. And he was just asking me about the scaling journey with being a sole founder. And I basically was just like, you have to hire around the things that you’re not competent in, and you have to really trust that those people are really great at that. And they’ve gone through that journey before. That’s really key. As a founder and CEO, I’m always told I should be the only one really learning on the job. And then everyone else should be coming in using their experience to push the whole company forward and really know the process and the technique of really scaling the one sliver of the company. And I tell that to my team all the time. I always orient them around, if you’re going to bring someone in, they have to be better than you. That’s what you look for. And the line I use all the time is from Ben Horowitz’s book that I think he took it from Colin Powell or someone, which is “Hire people for specific strength versus a lack of weakness.”
Startups are a team sport, you know, it’s not the founder that makes it great, it’s everything else around it. That’s been the transition. It’s, it’s been a massive step function every year and every year is different. I continue to learn so much about how to do this, and I’m always gonna keep learning how to do it because it is very rewarding when you get it right, but it’s super challenging along the way and, it’s very existential a lot of the times.
Vivek: I’m sure the exponential growth every year you’re always looking back and saying, you know, these were the challenges, these are the opportunities. Every founder, when you’re jumping in for the first time, you’re sort of learning as you go and you’re a different person and a different founder probably every six months.
Jack: Maybe even every three months right now.
Vivek: Well, thinking about the transition you made to being a founder, how did you think about a market like the one you were entering, which is the SIEM market? As you mentioned, there have been players like Splunk that have been around for a long time and are pretty pervasive, and are well-capitalized. How do you look at that and decide, Hey, you know what? I’m going to jump in, I think there’s a new opportunity here. Maybe just give us a sense of what that was like, taking that plunge in a landscape like that?
Jack: I’ll be really honest, going as an engineer, becoming a founder, I knew nothing about Go-To-Market. Just straight up, right? What did I know? I was a decent engineer and, I knew security really well. But when I started the company, my mind automatically went to, I know how I can build this thing better, and I know how I can continue to satisfy the problems that people were having who looked like me in other companies because I was effectively given two options. I could join another startup. I could have joined a company like Stripe, right? The ones that were just kind of peers to Airbnb at the time, but had a lot of cloud infra, had a lot of the same problems. I could join a company and keep building internally again and just do this over and over, or I could just build a company and then do it for those same types of people, but I could support multiple companies. And I could build one thing and make it really great instead of building a bunch of internal SIEMs all the time. That’s really what my target was. My target was I want to build a better version of this that allows us, as analysts, to use a UI instead of everything Command-line, because that’s what Stream Alert was. It was basically a backend service. And we really struggled with getting our analysts who were fairly new to Python, you know, didn’t know about Terraform and all these things. It’s just, it’s very engineering oriented. Didn’t know about deployments and DevOps, which was basically a required skill at that point.
So, what I knew was I wanted to build it with a stronger foundation on the backend in terms of which programming language we’re using. I want to do a compiled language on interpreted language because it’s high-skill logging and it just will perform better. And I want to have a UI. And those were the two things in my head that I was focused on. The hope was that we’d be able to support an even higher scale of logging and then companies would be able to use us either alongside their current SIEM or as an augmentation and then eventually as a replacement as we’ve caught up on parody. That’s where my head was, and I didn’t really think that anyone was really doing anything like this. Now it’s a bit different where there’s more companies in cloud-native, but just because you’re cloud-native doesn’t mean that you’re good at scaling. It’s not guaranteed. You still have to do a lot of work. And my team at Panther Labs has done a lot of really amazing stuff to get to that scale. Just for a sense, I think our biggest customer was doing a few petabytes of data per month, and that was a mind-blowing number. It just wasn’t possible. And that’s the start of what you need for SIEM. You need some way of getting to that scale because everyone is continuously growing and these big Fortune 500s just have so much data, they’re probably freaked out. They’re, I just can’t even begin to start looking at this. So let’s solve that problem. Now the next problem to solve, which is also very much a data problem, is how do we get as much security value out of that data as possible, which is very challenging just to even define. Because a lot of security teams, they’re all looking for different things in all these different ways. So finding the intersection of all that and really hinging a product around it and showing very repeatable value is very challenging. Because detection is one of those things that’s so non-binary. You look for many years for the breach and you may not ever find one depending on what’s going on. If you’re a big Fortune 500, you’re probably targeted a lot more. But if you’re a growth-stage startup, you could probably never see anything happen. But you know you need to do it. It’s like car insurance. You know you need to buy it and you know you need to drive safely, but an accident may never happen. But you do it and you pay for it because it’s important and you need to cover your risk for other people.
So in a lot of ways, this type of security is similar to that. Whereas other types of security are very defined, like cloud security. Your cloud is secure and it meets your standards or it doesn’t, it’s very binary. Same thing with application security. Like you wrote a vulnerability into your code or you didn’t, and of course, there’s gray areas with all these, but they’re much smaller gray areas than detection.
Because detection is like interpreting the law. It depends on who’s reading the law, right? It’s the same thing with analysts. I’ve worked with analysts that are incredible at what they do, and the way they work is just magical. They just know the system so intimately. To where I would look at the same logs and be like, I didn’t see it. I just didn’t know how you found it. Right? It makes it really challenging to do this. And that’s a challenge that we have now. So initially it was, can we build tech that’s going to allow us to get some early customers and solve the pains that they’re having that we were having at Airbnb and Amazon and my early team was from Amazon as well. So, they were really good at scale. They knew what scale means. Now the second layer of that is how do we make the most out of this data as possible and make it so widely applicable that it’s actually solving a lot of these detection challenges teams are having.
Vivek: It’s amazing because you, you talk about having these Amazon folks, and who knows scale better than Amazon, right? And so even just getting them on board, this is the perfect opportunity for them to show what scale really means and how do you bring scale to, a next generation of customers, that can actually start to utilize and use this. So take us to getting that first customer. What was that like? What was the journey to do that? How did you feel?
Jack: The first customer was interesting. I think that at the time, so Panther Labs was open source, and we had open sourced the platform because the thesis was, engineers wanna run open-source tooling and that’s going to allow them to trust us. In security, a new company, it’s a little bit of a chicken in the egg problem because you want people to use you, but no one trusts you until other people use you. So how do you get around that? You can do open source because engineers are tinkerers and they wanna play with stuff. So we did that and that allowed us to get our first few customers. But the story I would tell is really around one of our first big logos and that was a really transformative process because it wasn’t so much about the open-source element, it was really about are we able to hook them in and get them interested and then show them that we can evolve very rapidly and, and do the things that they want.
So, we were on sales calls with them all the time. And at the time it was me one engineer, and then my COO, my now COO. And we were sort of playing the role of SE/AE right? So what we would do is we would sit on calls with them and they would say, hey we like these things, but there’s these other two things that are just missing.
So what we would do is we would go build it and we would get maybe three-quarters of the way there. And then we’d be like, what do you think of this? We eventually did that enough times to where we got them to sign and then we got others to sign using that same technique. And in a lot of ways that’s super similar to what you just have to do after that point as well. So getting the customer is one big piece of work, but then keeping them happy and showing that you’re evolving over time is another.
Vivek: Jack, let’s talk about AI because this is the topic that is on everyone’s mind. Today, Panther Laabs does not incorporate AI into its platform at its core. How do you think about that? Is that something you even think about? Is it something that you’re thinking about for the future? Do your customers even care? We would love to get your thoughts on that.
Jack: Yeah. AI is a very complicated thing in security because of what I was mentioning before, around detection is such a gray area. It’s in a lot of ways not great for that use case because you don’t always know input versus output. Like, yes, this was truly bad or not, you don’t have enough data. And everyone is very different. Every environment’s completely different. So naturally it becomes not a great use case. However, with a lot of the advances that were made, we’re certainly investigating and seeing where’s the best mechanism of deploying machine learning and training data on things like queries is a great place for us. Like how would we translate natural language into a query? Because our effective backend is SQL. It’s a data warehouse, so there’s some cool stuff we could do there. There’s some cool stuff around just observing behaviors for people who are continuously doing certain response actions. There’s a lot of types of things we can investigate, but in security, there’s always been these systems called UEBA. user behavioral analytics. However, they’re also notoriously terrible and a lot of people just ignore them. So SIEMs in general just have a bad rap. I think most, most people just hate the SIEM. They hate the category, and there’s a reason that they hate it. And the reason that they hate it is because it was slow. They weren’t scalable. They were hard to use. They weren’t accurate, and then it just made their life a living hell every day.
And it’s because there’s core problems that were never solved in security. So, a lot of those core problems end up being data architecture problems. And if you solve that, then you’re on the way to having very repeatable ways of actually getting great value from your SIEM. But until you solve those problems, it’s very difficult. And then actually that’s also the precursor to doing things like AI because you can’t really apply machine learning on unstructured data — it just doesn’t really work. To understand what the logs are. You have to know that this is a login event across all these different log types. Then you can feed that into the model and say, Hey, from the beginning of time, this is when Jack has logged in historically. You know, model, what do you think about this log? Is this a typical IP address that he would log in from? Is this a typical whatever? And, there’s a lot of processing that we can do on top of that as well to make it very valuable, but when we ship our features that are going to do things like this, I want them to be really good. I don’t want to ship something that’s just to check the box and then it’s not helpful. I want it to be valuable. So we’re doing a lot of building and investigation right now around what that next layer of analysis is. And I’m excited to see how the team decides or doesn’t decide to use, something like an OpenAI API or, or something similar. I think for us it’s just making sure we have the right use case for value and then leaning into it heavily. So I personally pay attention to it a lot. I think it’s exciting and everyone’s trying to build as fast as possible — it’s a great Silicon Valley energy and it’s really cool being here in San Francisco, and just watching it and seeing what’s happening in the industry is really cool. But security’s been very lagging for technology for a long time.
Vivek: and for a good reason in some ways too, right? As you mentioned, just slapping in GPT, slapping in an OpenAI plugin, when you’re dealing with really sensitive and private data that your customers are entrusting you with, I imagine it’s not a chatbot or something like that where you can just sort of move quickly to incorporate AI, you have to be thoughtful about it, given the structures your customers are playing within,
Jack: A hundred percent. Yeah, those privacy concerns. And then honestly, it’s just value. I want to be able to deliver value there. It’s funny because I remember when the Web3 craze was happening a few years ago, and then now it’s like, oh, well that didn’t work out. Let’s do AI. But AI is, has always been a very enticing technology for security. Web3 obviously, in my opinion, had nothing to do with security. I always joked about doing NFTs of alerts. It’s like security alerts that you got breached on.
Vivek: Just figure out a way to combine Web3 with AI with security, and your next round will just materialize.
Jack: That’s right. GPT will generate a term sheet for me.
Vivek: I love that. Well, you know, you had a great tweet recently, analogizing GPT with autocorrect, and you basically said it’s an aid to creativity, which I really loved. Because I think there are a good amount of people out there that are a little bit spooked about GPT and what generative AI is doing. So, what are some of the ways that AI is aiding creativity within Panther Labs or within your own life?
Jack: I use it a lot. I use it for use cases that I would’ve otherwise need to just crawl the web for. A thing I do a lot is I ask a question into Google and then I search and look at everyone else, like five or six different pages and I read a few articles — I skip some of the clickbaity ones. Especially for entrepreneurial-level things. Some things seem to be just so click baity and so useless, or very surface level. And very specific questions I think are really great for something like GPT. So, the way I use it is I’ll ask very specific questions.
For example, I was building a new team, and I was asking about ratios. You know, I wanted to understand, hey, in this, for example, like in sales, you have ratios of AE, SE, and SDR, let’s just say, right? You have a certain ratio that you should maintain. So, I was asking questions like that, just trying to understand, how should I at my stage lay out my team to do this. I use it a lot for summarization as well. If I write something long, like, Hey, can you summarize this down? I’ll use it for, I’m trying to think of a word that explains this. And it gives me great suggestions. That’s perfect.
I’m not so much a fan of using it for net new things all the time. I use it when I know I have a pretty good idea of how I want it to work. And then I want to get a new iteration of that. That to me is a perfect use case for it.
Oh, actually, a really cool thing I did recently, which is more personal. So, I keep a list of questions in Notion. I have Notion in my private life as well because why not? It’s great. I love it. I’m a huge Notion fan. And I’m really big on asking good questions to people and getting to know people beyond the surface-level stuff. Because I think when you establish that level of vulnerability, you reach a new level of trust.
So I have a list of questions that are related to that. Like — what makes you trust somebody, what was the most rewarding trip that you ever took? Questions like that. And I’ve worked on them for many years. So, when GPT-3 and 4 came out, I was like, oh, what if I feed the questions and I train it on those questions that I know I really like, and then get some more questions back. So, I did that and I thought that was super cool. And you can use this for interview questions, right? I’m interviewing for X, Y, Z role. These are questions I like, generate 10 more. That works beautifully and it’s an aid of creativity because it’s inspiring. And maybe you get six back that you like and the four you don’t. That’s fine. That’s six others that you didn’t think of. And in a lot of ways this a massive shortcut to just having a ton of people around you. Because think about it. When you are building a company, you want a lot of diverse minds around who don’t have the same perspective, and that’s how you build great things. Otherwise, you are in tunnel visioned into one group of mentality. You’re in this box. And tools like language models really help you expand your mind authentically and in a way that is constructive. The one thing I will say that I thought was hilarious — I think I mentioned and brought it up as well, but I’m very big into just self-growth and those types of things. And so, I asked ChatGPT, “How do I find true love?” I was already in a relationship. I was just curious what ChatGPT thinks is the way that you find true love. And it was so on point. I was blown away. It said: Finding true love can be a complicated process, but it can be done if you take the time to focus on yourself and become the best type of person that you’d want to be with. Figure out what your values are, what are your goals? And put yourself in situations and settings where you’re more likely to meet someone who shares similar interests and values. And be open and honest in your relationships, and don’t be afraid to communicate your feelings and needs.
That’s actually pretty solid. I just got such a kick out of that one answer.
What self-love means is you have to know yourself first. You have to know what your intentions are. And that’s such an important thing for just business as well. You have to set your intention going into the year. You have to set your intention with the future you’re building. You have to set your intention with everything. How do you want to show up? Who do you want to be? What’s your identity? And then once you understand those things about yourself, then you’re like, cool, this is what I think would be ideal in a life partner. This is what I think would be ideal for having someone run this function in my company. This is what it would be ideal in this event that I want to throw. This is the outcome. This is what I want people to feel like once you get to that level of psychology, for yourself and others, then I think you’re just more effective in everything.
And a lot of the stuff that we do is all connected. Like being into fitness and health. It creates a drive and creates a consistency that applies in other parts of your life. And when you have all of those together, then you’re effective, right? But I think it’s flawed to think, “Oh, I’m just going to be great at this business thing.” Right? Because a lot of the work that you do on yourself can make you better at business and vice versa. Sorry – I could talk about self-growth stuff for hours.
Vivek: I wanted to wait until the end, but it’s too good not to ask you about the body hacking and I don’t know if that’s the right term anymore, but you know about all the things you do around, a combination of fitness with being very insightful into what’s happening at the self level — all of these things. Is that new for you as a founder? Have you always been that way? Has it changed being a founder? Would love to get your thoughts on that.
Jack: Everything I do is for the purpose of longevity. And if it doesn’t really matter what I’m doing, if I become a parent, that’s a whole new level of endurance that I need to be ready for. But even just being a founder requires a level of endurance, mental endurance, and actual physical endurance. They’re very much hand in hand. And I’ve just learned so much about my diet and my sleep and my movement, and I’m at this point now where I’ve learned so much about how my body reacts to certain stimulus, it’s just been a total game changer for me, and it’s allowed me to have better focus, it’s allowed me to learn how to just run at the right pace. I’ve had a string of health problems my whole life. I was actually never athletic as a kid, and when you’re not athletic as a kid, I think it teaches you to just not be athletic in general. But when I got to college, something really cool happened where I had an athletic roommate and he brought me to the gym, and I just kept going.
And there’s so much to being well-rounded. If you want longevity, you need to have your diet on point, because diet is actually so underrated in terms of how it affects your energy. I think it’s probably one of the most things aside from sleep, obviously. If you sleep poorly then nothing else is going to matter and you should read, ” ‘How We Sleep,” it’s a great book. So, if you’re struggling with sleep, start there. And then aside from that, learn about diet.
I wear a WHOOP religiously, this thing on my wrist, and the WHOOP taught me how to sleep right. I’d be working till 11:00 at night and then I’d go to bed, wake up at 7:00, and I’d feel horrible every day. I’d have headaches when I woke up, I would just pound coffee, and I just pushed through it. and then I learned how to sleep properly. And now I go to sleep around between 9:00 and 10:00. And then I get up at 5:00 – 5:30. I do my workout in the morning and have some time to myself. I set my intention for the day. I think another underrated part of longevity is your mental game. And just learning what your body reacts to, for example, I stopped eating meat about two years ago and I eat fish still. I’m a pescatarian, and I just find that that works for me. And some people just only eat meat and that works for them. But the way your body reacts to food can significantly affect your energy.
But all these things I’m doing are for helping my longevity and making sure that I stay strong and flexible and push, but I also recover and I take a step back and rest a little bit and getting better at that last part — that balance of activity and rest, activity and rest. If I’m constantly burning myself out, then I’m not being effective as a leader. I’m not setting the right example either for my team. And again, I’m getting better at knowing when to take time off.
It can be hard as a sole founder and a CEO. We do all these things, or I do all these things to be the best CEO I can be and to deal with the infinite stimuli that come with running a company. And if you don’t do these things and you’re constantly tired and you’re sluggish, you’re not going to show up in the right ways.
Vivek: Jack, just, just hearing even the last five minutes of what you were talking about, I realize I’m underperforming on probably 12 different things that are not even company-related between my sleep and diet and all these things, so I have a lot to learn from you.
Jack, this was fantastic. Thank you so much for joining us. Congrats to you and the team on everything that you’ve achieved, at Panther Labs and everything you’re about to achieve and really exciting to see where the company goes and where this sector goes. And this was really enjoyable. So, thank you so much.
Jack: Thanks for having me on, it was really fun.
Coral: Thank you for listening to this IA40 Spotlight episode of Founded & Funded. If you’re interested in learning more about Panther Labs, please visit www.panther.com. If you’re interested in learning more about the IA40, please visit www.IA40.com. Thanks again for listening, and tune in a couple of weeks for our next episode of Founded & Funded with Numbers Station Co-founders Chris Aberger and Ines Chami.