Why Experience Matters More Than You Think in Entrepreneurship

0:00The number one differentiator between what I call the wantropanures and the entrepreneurs is work. And I don't care how smart you are, how good your insight is or whatever. Nobody changes the world on part time. We've got Zack Staples with us. So you're former Navy officer and you spend a lot of time on the open seas. I took two days off. I finished my last day on active duty was December 31, 2017. And then I was planning to take three or four weeks off. I've been out of the Navy like a day and a half. And the phone rings. And it is a tech accelerator in Europe doing text counting for Merisk, the largest shipping company in the world. If we don't get cybersecurity right for physical AI, we are enabling humanity's worst fears about the war between humans and machines. Welcome back to another Friday habit.

1:03We're here live from somewhere in Denver, Colorado. And Austin Texas. And Austin, Texas, where all the startups are booming. And today we've got Zack Staples with us. So you're former Navy officer and you spend a lot of time on the open seas. I guess one of my questions would be is, why would anybody a young gentleman with endless possibility like decide to join the Navy? Like do you just thought like, yeah, I want to be crammed in a ship with a bunch of dudes eating, you know, crappy food for months on end. You know why? Well, first off, let's be honest. Like 18 year old boys do not make good life decisions. That's it. That's proven. I have one myself and I'm thinking to my, I'm actually saying, you know, maybe you just join the military. Right. So that says so. So why does any 18 year old man do it? Do the things that they do, right? No, you know, I think, I think people,

2:09a lot of people are looking to do the hard thing. And I think I think in a lot of, for a lot of people, you know, school maybe in socially so hard, but maybe academically wasn't a whole lot of a challenge or all sorts of reasons why people decide that I want to go do the hard thing. And I want to see if the hard thing challenges me. And we see that in music and, you know, you don't join a van because you want the easy way to spend your weekends. You have a passion about doing this hard thing with people that you respect, right? And so yeah, I had some early mentors in my life, my grandfather who I loved and respected was in the Navy in World War II. And then I had uncles who were in Vietnam. And then a guy that I just really respected when he was in high school. And I was just a kid in my church. You know, he went to the Naval Academy

3:10and everybody was like super proud of him. And so I just put it in my head as a kid. It's someday I'm gonna go to the Naval Academy. And I thought frankly, I thought frankly, I was gonna be an astronaut. That was what I was. Oh really? Where did you grow up? Here in Texas. I might be the only tech CEO in Austin from Austin. I, seriously. Yeah. Fort Worth. So you've seen it, so you've seen it blow up over the past years because it used to be the, you know, the whole like keep Austin weird thing was like, yeah, it was this little oasis in Texas that had just some strange things south by Southwest. And, you know, some weird desert parts. We're still done to keep Austin weird. It's just got to coach a lot more people now on what that means. Yeah, yeah, exactly. So that's cool. So you kind of it was like you grew up in a, and back then kind of a small town, right? And I grew up out in the world. Yeah, out in Abelene and my uncle, he had gone to law school here.

4:11And so, and then my best friend in high school who's to add lived here on the Travis. I was down here a bunch and then while I was off in the Navy for 20 something years, all of my family moved here. And then we've had generationally like, like been in central Texas for a long time. So, but I actually married a woman from Massachusetts. And so I don't want to act like I got all the agency in this decision. We were driving through the hill country right after I'd retired. Like 60 days after I'd started my first company, Foulin Five. And it was this time of the year, the blue bonnets and all the wild flowers were up. Kind of the rolling hills through the hill country, south of Boston, out into my mom's house and my wife looks at me and she goes, you know, I've been following you around for like 20 something years. I'm moving here. Are you coming? You're like, okay. And I was like, what?

5:13Yes, ma'am. I said, I can do this. I can build this company in Austin, Boston or San Francisco. If you pick coming home to Texas, you know, count me in, honey, because it's awesome. My best friend actually lives in Abelene. And I have two, yeah, Nesan F.U. who go to their wild cats over at Abelene Creek. And you see him? Okay. My best friend, we grew up and then went back to ACU to work. He's the general council there now. And it's a cool school. And you're doing amazing things in the technology space that I mean, they're actually building a molten salt test reactor and are one of the leading universities in the country now on modern safe nuclear power. Then you didn't know that's like, like, seriously, and I've been abelene a lot because my best friend lives there. And you know, you don't think about it. But in that town's been blown up too, because you got the Air Force base there

6:13and then the B2 bomber, it flies out of there, or something like that, I think. And so it seems like it's been exploding as far as that goes. Well, so for a lot of the entrepreneurs, it's worth noting that Texas is a very business-friendly climate. And so we can joke around about how all the tech guys are moving to Austin. You know what? But from Elon Musk to the founder of Uber, Travis Kalinik, and then a couple hundred thousand others. But the reason why is because Texas is supportive of small business. Which is so good. And something that's really needed, I mean, we used, Palantir used to be based out of here. But because it sucks so bad to do business in Colorado, they've moved to Florida. And so I'm like, hey, when are these people going to wake up and be like, listen, we need businesses to help the city thrive and for tax income. And all sorts of other reasons, good jobs and good people.

7:16And so it's good that Texas is still trying to hold the line on that. Yeah, try to. So many of that, I think for people who are thinking about starting a company and looking for a good ecosystem, they'll find one here. Yeah. So you got into the military right after high school then. And then you spent 20 some years there? Yeah, four years at the Academy and then almost 23 years after that. And I was a ship driver. So I was a surface warfare officer, naval officer. And then, but was really fortunate to spend the last 10 years or so of my career, mostly doing electronic warfare and cyber. So then were you a part of the Gulf War or any type of like, only by ribbon? So what I went to the Academy in 1991. And just like just like almost the end. Well, I got this little, I had my first little ribbon

8:18because I was technically in during the Cold War. But I didn't do any glass and march. So yeah. And did you, once you got into the military, did you see like a clear trajectory of like where you wanted to go? No, no, no, no. I think, you know, only in, maybe it's true for everybody. But I think the path only looks inevitable in that respect. As you're looking, I think everybody looking forward in their career doesn't understand how they're very unique experiences they've had are going to add up to their unique perspective that gives them opportunity to have a unique contribution. I love that story that Steve Jobs told about, he took a calligraphy class, just as something to do at a liberal arts college. And he ended up, you know, that was the inspiration of how the fonts had to look on the Mac and all of a sudden he created the computer that appealed to the artistic creative side of industry

9:20and you know, and made Apple. And you can't connect those dots. I don't think I'm a forward to trajectory. Yeah, yeah, no, it's so true. And it's kind of like this idea, you know, for me, I'm a man of faith. And I'm always preaching these things of like, you know, being present, not worrying how things are going to work out and expect God's blessing, you know? And you know, that's, I look back on my life and I just kind of see like the more I pushed into those values, the more I was able to be with my family and really be focused and present. And then for good, a lot of like stress and anxiety and worry, you know, because it can be hard sometimes, you know? To be company and I completely agree. Mark, it's funny how the same ideas get, maybe rebranded as the right word. Like what you're talking about, like what most, a lot of people would call mindfulness now, you know,

10:21being present, being in the moment, being accountable to the people that you're with that at that, at that, at the time, goes back to all these other ideas, you know, one of my favorite books of all time is My American Journey by Colin Powell. And in that, he talks about, you know, doing the very best you can at whatever job is the one that you've, you know, been assigned or volunteered to do. And, you know, I recall, he tells a story about mopping the floor. He's like, I don't want him off this floor, but I'm going to do a really good job. But it was that level of attention to the detail for guiding the attention of the next thing and the next thing and the next thing. Being present, being willing to put in the time to do a good job, I think is one of the, those core attributes of successful people. So to do you meet your wife on the ship, you know, was she there? Or was she to port somewhere? Or yeah, that's right.

11:21I, if I ever had a woman in every port, it's because she traveled to meet me there. I met her one after I got out of college. And wow, okay. Yeah, yeah, I got on the very first night out in my very first duty station after I got, after I was, you know, commissioned in the Navy. And we've been together 30 something years since then. Wow, that's awesome. It's been a few kids and stuff. We do, we've got, yeah, we've got three amazing kids who are as bad as far apart as three humans can be. And so given how much I was gone, I give my wife, all of the credit in the world that they all love and respect and appreciate each other, even though they are on, you know, complete polar ends of the things that American people like and believe in. So it's amazing. Yeah, what, so married for 30 years. Yeah. And I'm assuming you were gone a lot with your job. Yeah. How, how one is, I mean, how did you maintain that relationship?

12:23And, you know, again, even with the kids, like you're saying you were gone, like, what are some things you look back are the small things that maybe you say, okay, that was beneficial for my relationship with my kids or with my, you know, wife. And then maybe what are some things you would look at and say, man, I could have done better at this or been more, you know, intentional here. Yeah, for sure. I think, you know, I think this applies for so first, you know, I was gone a lot during my, you know, the first 20 something years of my career because of the military and, you know, multiple combat deployments. And then, but then as an entrepreneur and a founder, you know, you just signed it. If you're gonna be successful, you're signing up 18 hour days, right? And so being gone at the office is only slightly different from being gone on a worship. Yeah. And so, yeah, there are, there's probably a couple of things. I would say the number one thing, you know, no surprise, but the number one thing I think my wife and I have always had and still have and value

13:25is we laugh a lot like, and, and so we have our time together. There's a lot of joy in that. And the second thing is we're pretty direct about what we're thinking and have found a way over the years to be candid, but also like caring. And so I think the ability, you know, that was my grandfather gave me at our wedding, you know, but the ability to be candid and caring, candid and caring. You can tell somebody exactly what you think and say it in a way that is designed to, for them to hear it, not just for you to say it. Yeah. Yeah. And, and obviously like marrying the right person, right? Like, that, that, that always helps. I don't know that too. I'm gonna, I'm gonna, I got lucky and she's got a good picker. I don't know. Yeah. Yeah. Yeah. Well, yeah, and obviously, you know, I just celebrate 21 years of marriage. And so I understand a little bit of the sacrifice and,

14:28and just stick it to itness that it takes, you know, and because the world always wants to say the bag of goods of, oh, somebody else will make you happy or all your problems will go away. And it's just, you know, the grass is always greener on the other side, but then you get there and the weeds are magnified. And so it's like really trying to figure out, you know, like, like, all right, like, how can I be the, bring the best version of myself to this relationship? And then how can I persevere doing hard, during hard times? Because I know that somebody else isn't gonna solve my problems, you know, everywhere I go there I am. And so it's like, how do I solve this problem, you know, here and now? And so, yeah, I think that's, that's awesome. All right, so dude, you crushed it in the military. You were just getting stripes left and right and like, you know, going on deployments and, and managing people and, and, and developing yourself as a leader. And then when it was time to retire, was it something that you had this idea of like, oh, I'm, I'm gonna start a business and I'm gonna start, you know,

15:29developing tech tools and things like that. Like what, what was that transitional period for you? Yeah, again, you know, this is a story of another inspirational woman, you know, my mom and my sisters were, you know, inspirational women, we're all entrepreneurs. And, and so I grew up that way. And then I watched some of the very cool things my, my sisters did and look in the companies that they started. And I thought, and so I just, I did, that's what I wanted to do. And I kind of always had it as my plan and, you know, ultimately, I wanted to serve our country. As long as I felt like I was making a difference. And as soon as I got to the point around the 20, you know, year 22 or so and they said, maybe we want you to go do this. And like I don't, I don't think that's how I continue to serve. And so I get, I get, I get out and, and okay, okay, here's something not to do. I took two days off. I took, I took, I, I, my, my, I finished my, my last day on active duty was December 31st, 2017.

16:33Hmm. And then I was planning to take, you know, three or four weeks off. But at the time, this is about, you know, pivoting to where the market is. At the time, I thought I wanted to do a maritime cyber security company or a maritime technology company and trying to take a lot of the, the ideas that I had doing technology development for the Navy and do them from commercial maritime industry. So I built the website, you know, a couple of months before I got active duty. So I'm literally sitting at the house and I didn't have a business phone. I put my cell phone on as the phone number for the business. So I'm sitting there watching bowl games on January 2nd. I've been out of the Navy like a day and a half and the phone rings. And it is a tech accelerator in Europe doing tech scouting for Marisk, the largest shipping company in the world. And says, hey, we're listening. We're looking for like maritime digitization, specialty companies and startups to put them into this qualiator for Marisk.

17:34And I was like, oh my God. So I get up after being at a military for a day and a half. Oh my goodness. SEO is working overtime for you. And I was like, honey, remember when I said, you know, I might say, I said, well, I just got a call from the largest shipping company in the world about the website we put up. So I guess I'm going to work. Wow. If we did that, that by the way, did not pan out. You know, we got they liked the ideas and realized that I was a company of one and probably wasn't ready for scale. Right. But at least it planned the seed for you, right? To say like, oh, well, like something's possible. Like you, you stand up the storefront and then now, the sudden it's like, wow, I didn't even really try that hard and something potential came my way. So like what happens if I really dig into this? You know, and so once that, you know, once that, once that, it was, it was, you know, a full speed ahead for several years to build what we were able to accomplish in five and five, which, you know,

18:36I'm pretty proud of this. I kind of set off with it with the goal was to build a successful company that doing something that mattered. There's a book that says, you know, smart people should build things. And I got and I, you know, and I actually think if you, if you have the capacity to be a good leader and you have the capacity to attract other really intelligent people to help design product, there are so many important problems to solve in the world. That developing like some classes of products, like that might make a lot of money, but don't do anything for humanity. Seem like they're under serving the larger purpose that we could be achieving together to try and to make the world a better place. So again, I kind of a dim view of lots of financial services products,

19:39you know, yet another derivative, you know, product is probably not nearly as helpful as a desalination technique that can be used in, you know, interior countries. Yeah, the, the law, there's just a laundry list of civilizational problems. And so where we kind of took our cue was around, and in five and five was around, how do we take the emergence of AI and the industrial layer of civilization, the machines that make it possible? Yeah. I mean, what year was this? Because that, I mean, 2017, I'm thinking like, gosh, I really don't remember, you know, Chatchy Tp until like, three, you know, actually, I have a book right up there that is a DARPA study from the mid 70s, the late 70s that talks about the power of neural networks. So it is, you know, it's been known for 50 years that neural networks were

20:41going to create an amazing opportunity is the solve problems with computers that we couldn't do previously. What wasn't known was how you would train one. And so with 2012, some pioneering work by Gunn and Jeff Hinton, created mathematical techniques to actually train a computer to build with it within we were calling them a deep learning or deep. Yeah, deep learning. Yeah, yeah, Google was doing the go, you know, with training the computer, how to play the game chess and then the go game, you know, yeah, that's absolutely right. So you had deep blue that built the computer that played in beat Gary Kasperov. And then you had, and then you had Alpha Go that beat one of the world's best go players, right? And then so you saw this progression in metrics of intelligence that said, hey, the machines can do this, and solve problems. Chess, how to play chess really well as a heart is a is a is a is a problem as

21:46well as how do you play a less deterministic game? I go, well, hard problem. And so what deep learning lot is to do is just continue that, continue that thread, right? And so Jeff's work came out about 2012. And that's when the deep men and so by 2017, I'd been, you know, in that space and doing problems in that space for about five years. And so we thought we saw a lot of AI and being used for ad targeting. And and some other things that would fall into my bucket of not very helpful for society, even though they may make a lot of money. Right. Yeah. And then subsequently we would, you know, we would see when they got all revealed in the early, you know, late teens or the 20s that a lot of that social media content targeting was very helpful. And yeah, well, yeah, we, I mean, with the whole COVID misinformation,

22:50disinformation, you know, politics left right, you know, Trump, like it was wild back then, you know, vaccines, it was nuts. It was nuts, right? And then and so we had a couple of important things. I think harmed. We had, you know, the 2016 Russian election back, you know, harmed our democratic process. And then even more egregiously, you know, leadership at Facebook has been on record as knowing that their content targeting particularly towards young women had negative psychological impacts on a generation of young people and and did nothing about it, right? And so I thought, well, where is a domain that we should go this technology, we need to understand this technology as the potential to do amazing things over over the next few generations for for the world and for humanity. But we need to be careful in my opinion about where do we apply, where do we go

23:53practice? And what domains could be practiced in that are safer than the unauthorized social experiments that got right. So some of these media companies. And so we, we've really arrived at the idea that machinery has all these like AI for machines has a bunch of really good like characteristics that that that help you iterate very, very quickly on quality and advancement of the technology with harms that are manageable for the risk. So I'll give you, I'll give you a reason. All right. Just go back to that social media targeting thing. We know after a decade of research that content targeting was harmful to young women, right? Well, that's a harm that didn't really get exposed for 10 years. So you would say, hey, a better domain for AI would be somewhere where the

24:57harm is immediately observable. So we can stop doing that and figure out how to go right. But the algorithms that advances the technology. So we thought, you know what, machines are good for that. If you're not running the machine right, it breaks. And it breaks probably pretty quickly if your optimizer isn't running it correctly. And so we thought machinery AI reveals harms quickly. And then we thought, what is the, what is the scale of those harms? Right. Again, going back to damaging a generation of young women, not an okay level of harm, maybe irreparable level of, level of hard, right? Breaking a machine, you can probably claim that in your insurance. Right. Right. And so you have this. So our scale was AI, we should not cap the experimentation of the quality and size of AI models. But we should be very deliberate about the domains where we want to put that

26:01technology to work that allow us to observe harm quickly in domains where that harm is quantifiable and doesn't have civilization level impacts. Yeah. So what were those domains you were putting it in right away? Yep. Machine reproduction. So, so, phathom 5a, my first company ended up building the Navy's program of record for predictive maintenance. That bearing is going bad. That oil needs to be changed. You should change that strainer and got to work as a, a, a, a, a build a platform for third parties to develop algorithms for. Yeah. And so create an open ecosystem that, you know, help national security and, and put AI to work in a domain that was where we should be experimenting. Right. Yeah. Exactly. Where we, we can, again, like, it's not telling the, the proper machine of when the oil needs to be changed. And so we got to tweak that and fix that.

27:03And that doesn't really harm anybody, you know. So it's not getting that wrong is a, is a manageable risk. And so now you can go really fast. You can not have to worry about AI ethics and safety and all these other things. You can go, you're on early on, right? So we're only 10 years into building AI, 15 years into building AI systems. You know, think of the first 15 years of making things out of steel. Like you look back and you're like, okay, you know, you know, we're, yeah, humans playing with a new play dough here. We don't know how to make it out of this really yet. But the stuff that we're making is inspirational and cool, but, but it's nothing nearly as impressive as what we're going to do with this new, this new building material. And so the idea, right, would be how do we go super fast and learn how to use this new material? And then when we really understand it, then we start building it into systems that interact with society. Yeah. How did you overcome?

28:04I mean, starting out with the company, I'm trying to think of like, all right, it's kind of this new concept. So you're trying to say, hey, there's this thing called AI that we can install on the ship. And like, how did you get people to overcome their fear or uncertainty of, you know, using a new technology in something like a warship or something like that? Yeah. I think one of the roles of a, of a, of a, a good founder is to be a good communicator. And I was fortunate that I had the credibility of having done 20 years in the organization. So I understood all of them in that. And, and had deeply devoted myself to understanding the technology. And then, and then found a way to explain it to my mom and my sisters. And people on airplanes, right? I always said, if I, you know, Napoleon had this idea of Napoleon's corporal, if he could have, have a, have a corporal read his orders and understand it, then he knew if he sent them to another general,

29:05they should probably get what he meant. I had the same idea of if I'm sitting on an airplane and I could explain it to whoever is next to me, like, where are you going to have one at DC? What are you doing? I've got a meeting with that. I know what are you going to do? And then, you know, if I, if they could understand what we did, then I had probably like gotten it to a level where I was able to communicate it to an admiral order to anybody else who needed to understand it. And I think everybody needs to find, I think, I think even maybe it was, um, lean startup talks about this. But, you know, in the early, in the startup can, and there's that idea of, you know, the mom test, you know, can you explain? If you can't explain the idea in a simple enough way that it's accessible by everybody, then you aren't there yet. Keep, yeah, to any practice. Yeah. How, um, how quickly did that company grow? And, and then at what point did you have a new idea? It's like the classic entrepreneurial thing, right?

30:06I have a few friends that it's like, they're just ideas guys, you know, it's like they started business and then they're like, All right, they get that thing going. There's like a new idea. It's like, okay, yeah, let me, let me start something else. Like, so how long was that to you started getting some traction and, and finding a good rhythm with it and then starting something else? Yeah, we were pretty fortunate. We got, uh, we got a good, uh, amount of traction in the first year. So, uh, two types of innovators, right? There's the, the, the early young innovators who, um, have this brilliant idea, but they, they, they, they haven't let an organization. They haven't led big teams. They're learning it all as they go. And that's where the data, that's where most entrepreneurs and innovators come from. And so that that's why the data skews towards 95% small business failure because so many of the young leaders, entrepreneurial companies. Are, you know, at a point in their life when they can take a lot of risk, which usually means they're very young and they don't have debt and they may be not have a family yet.

31:13Yeah, but also is there a lot of life experience. Yeah, it's like you fake it until you make it and a lot of them never make it. Yeah, right. And so if you actually look at, and I think it was the MIT Sloan School to this data, but if you actually look at the data for entrepreneurial success for, um, founders and small business owners. That start the business over 45. The data is almost entirely inverted. There's got 50% success rate. Hmm. And I think it's because, and so I've been in Austin now doing this, been a, been a small business owner. And now another startup guy again, and just because it found the talent. But, um, so I've gotten to see tons of entrepreneurs give it a shot. I got across a whole age and demographic spectrum, but one of the things that jumps out at me about the, um, the ones that are the most successful are. There's always more things than you can get done under to do list.

32:15And there's always a top 10. Um, of what you should get done, right? And so the success metric comes down to. Of. Everything on the top 10, how many of those are repeats of decisions you've made a bunch of times before. And, and, and you know, figure, figure three of the top 10 are personnel issues, three of them are product and, you know, engineering product issues and three of them are business, like our business issues and your top nine, you throw in a couple of others in, right? Well, if you're brand new and leading people, professional engineering and starting a company, all 10 of the things on your list are brand new to you. Right. So your, your error rate just goes up, right? And the amount of time you can dedicate to the one you've never done before, like all goes down. So you have less time because on the one you know the least about, so your error rate just skyrocket.

33:17And so there's only so many mistakes you can make and, and leading a young company. Before or before you're just not going to turn it around. And so I, that's one of the reasons I believe that the small business success skews a little bit differently with experience. Now, a lot of people had that leadership experience on teams in, you know, Boyz Gouts and their church youth group in their college fraternity or whatever. And so they can, they, you know, they're, they're getting the type of leadership experience or they have great, you know, family and mentors, you know, Bill Gates mom was a board member on one or three companies. And so he had, you know, his mom was a professional. Right. So, so now you used to now you take off do I have someone I get who I entirely trust to give me good decisions on running a business, right? He was a great engineer. And so now you've got, now you've got two thirds of your risk categories, uh, minimized and Microsoft did okay, right?

34:20Yeah, exactly. Yeah. When did you start, uh, Fathom five with a partner or, or you so, oh my gosh. Yeah. Yeah. So I, it was, it was my idea and I was going to get it, uh, get it rolling. And then I invited this brilliant woman, Dr. Mara Sullivan to be my, uh, my co-founder. And, and she accepted and so we got, we got rolling with Fathom five really when I got here to Austin, June 2018. And then we got about a year and a half before COVID breaks out in December, 2020. Right. Right. And so, um, come March of 20, uh, you know, of, uh, I guess they had December 2019 and then, and then come March of 2020. Uh, yeah, at the slow pandemic, it just happens to be that my co-founder, you know, Dr. Mara Sullivan did her PhD in epidemiology, in epidemiology with our dissertation on pandemic risk management.

35:28At Emory University and like next door to the CDC, you know, we're like, so is your highest purpose in life doing our taxes? Or maybe like, you know, the next going on in the world right now. Yeah. And so, yeah, so I, I got to buy Mara out and she went off and did great things and is, uh, out there doing, you know, now back in the AI, AI space. So yeah, that's awesome. So then at what point did you have the idea or the caliber and come around as far as like, oh, another, another company or another direction you wanted to go. So this is another one of those. So when we did found five because we said, we see a change in the technology world, where the emergence of AI needs to be put to work in domains that we feel ethically, or ethically right, where we can excel with technology. That was kind of a guiding big idea behind, um, uh, Calder, I mean, behind path on five with, with caliber and it's different.

36:30It's a cooler, probably even bigger idea. And it's that, um, every time the shape of computing changes, there is an opportunity to build an operating system company that makes the new shape computer just work. So if I run through the story for you, when the shape of computers, the business computer, look was a human, you know, sitting in the background, you're probably kind of the wife, the storekeeper who's out front, right. Keep in the book. When the shape of that computer changed into a mainframe computer, that made IBM. Great. And when the shape of that computer changed again into a desktop personal computer, that changed the main apple. No, that you have that one made made Microsoft, right. Apple. Microsoft and my and and and when the MSDOS followed by windows, like was the marketer in that space. Apple really got made in its current, like it's the one of the biggest companies in the world form when the shape of the computer.

37:35Right. The computer changed to the shape of a cell phone or something that fits in your pocket that made Apple. And and so iOS became the operating system that you use to tailor your device for you. Your apps are different than mine that are different than probably despite everybody else. Everybody's a unique configuration of software that they can deploy on this little handheld computer. Because iOS or Android makes that possible. Right. That's what that's what DOS and Windows did. It's what and and so we're looking around and thinking and we years ago, I called it cyber physical conversions. And I realized that is a geeky or what everybody is calling it now is physical AI is machines and AI interacting in the world. And here's why this is so different. For the last, let's say 40 years since the mid 80s, right?

38:38If you wanted to engage with the digital world, you had to take your eyes and look at a screen. The screen couldn't make you look at it. Right. And so you you opted in to looking at a screen and then we've tried to moderate screen time. We've been we talk about measure screen time. But at the end of the day, there was some optionality in how often and when you interact with the digital world. Visible AI changes all of that. Because driverless cars can't hit you as a pedestrian on another and another car. Delivery drones are going to be flying around, you know, land and at your ring in your doorbell, making you come to the doorbell the answer. In home robotics and the list goes on and on and on about all of the ways AI and machines are going to combine and to interpose themselves on humanity. And so that is really risky.

39:43Think about well, you think about, you know, the Tom Cruise movie. Gosh, what was the name of that movie? My order, you know, he yeah, minority report and it was like, you know, he interacted in his space and it would recognize him and then show him ads based off of where he wasn't a mall and it was everything was like unique to him. He had to remove his eyeballs in order to like hide it with his body mechanism. Yeah. So I mean, I'll give you a really practical example, right? Like late life healthcare, the, you know, the checking the bed pans and doing kind of some of the very personal things that the people need late in life. You know, there's a probably more than a possibility that there's strong probability within the next 10, 20 years at the outside, that's going to be done by a robot. We're going to have, we're going to have physical AI in our homes on our streets and our offices and one of the, and I can tell you two things definitively about that.

40:51So what I want to do is, if the cyber security for physical AI is as bad as the cyber security has been for our email and the spam text messages we get on our phones. Right. Like we're not going to be with the world we built for ourselves. Yeah. Because now it now something that doesn't get hacked and it, you know, and it steals your identity. Now it gets hacked and it robs your house. Right. Right. So, and so we have to get cyber security right for physical AI. We just have to. We be, if we don't and, and Mark, I'm not, I'm not, I'm an optimist, right. But it is worth saying that if we don't get cyber security right for physical AI, we are enabling humanity's worst fears about the war between humans and machines. Yes, cyber nine. So I would do judge by day. I hear an often when I explain what we're doing with caliber and he's like, so basically you're preventing SkyNet. And I'm like pretty much she did.

41:55That's it. You've nailed you've hit the nail and that dude. So, so caliber and bills and operating system for autonomous machines. And if you think of iOS is the operating system for mobile telephones. And, and then there are AI applications that you can run on them like chat GPT or call on. Yeah. We, the operating system for physical AI. And, and we have a mission bay of applications that we have verified to be safe on the plan. And then the second thing we do is. And you hard code Isaac Asmob's law robotics like inside of them. I'm so telling to so so blessed to work with brilliant people. I've got a, I've got a, a colleague with me on this project. She advises or a doctor care, a little point. She actually led the Institute for a sure autonomy at Johns Hopkins at the applied physics lab there and a couple other people.

42:59Some brilliant people and the day I figured out how to code those three laws brother who go in it calling. But now we're kind of focused on, you know, performance corner cases and and just adoption, right? I mean, trying to get people to adopt it because that's the biggest thing right is. Is getting open AI and and theropic and everybody else to like use your system as the standard right. Like Microsoft with DOS it was like, okay, they created the foundation that everyone then coded on to deliver their apps to society. So yeah, it sounds not, it sounds like a uphill battle, you know, so what are some of the problems that you try to solve? Or like what are some of the things that you're trying to do to, you know, educate people on adopting, you know, your platform. Yeah, so Caliburn's platform is called tempest OS. So the first thing I'm doing is shameless plugs of the name everywhere I go. Nice. Okay. The SEO going right.

43:59You know, all the learning algorithms and large language models to kind of hear the name tempest OS. There you go. No, I did and then and then much more fundamentally. We're starting with the things that we know need to be done. So for the last, you know, 20 years, we've been using Linux operating systems in military hardware. And that has been an uphill battle to configure an open, you know, a normal general purpose Linux for use in military systems and weapons. And there's a, there's a list of a thousand plus things you have to do to, to a Linux operating system to make it to make it more secure and less hackable in a military system. And so we looked around and we're like, why isn't there an operating system that already has all these things done? Like out of the mountains. Why do you have to hire four very expensive cyber engineers for a year to go do this list of a thousand things anytime you want to build a new system for the US Department of war.

45:10And so we started off by saying, okay, if all of these really talented people have already made a list of things that, you know, that make it safer or let's just do those out of the box. The next thing is, I'm going to think about, you know, buying a suit off the rack at Walmart or Tari. Right. It's a suit, but it doesn't fit you great. You know, you can show up at a party with that suit on people, yeah, you know, you're not going to get thrown out of a nice restaurant because you are wearing a suit, but nobody's going to put you on the runway. And so the difference between, you know, off the rack general purpose and tailored people get that right. And so we should have tailored operating systems. We have the intelligence now to build a factory for operating systems that builds one specific for a use case. And why this is important is, if I have 10 million lines of code that support everything from a, you know, a media player to a TV to a toaster to a nest on the wall, because general purpose Linux can be used to make any one of those things.

46:32Well, maybe I shouldn't leave all of that stuff in there. If I'm building a robot. So let's take a very practical example. If I'm building a robot to clean your floor in your house, should I leave all of this sound and microphone driver stuff in the operating system so I can convert your robot to a listening device in your house. Or the ethical thing be to take all of that out. So it's just auto vacuum just the vacuum. Yeah, I heard I heard there was like some, it was some vacuum. It was like a vacuum. I think it was like Chinese made vacuum. And it was able to get on to the local network of the house or whatever. And then, you know, kind of hack, hack the, you know, users all through the vacuum because it was like an open, you know, it was like an open source or whatever. Yeah, so, so this is a really good example of, of making good choices, right. And so there's two ways to navigate around and close space.

47:35One is you use a non vision technology like, like LIDAR, which is laser radar or radar. Another way technology is to use pictures vision processing, right. And so, you know, it was an opinion is that a robot in your house, I would prefer it not use pictures. Yeah, ten, ten, they paid around my house, especially if your robot is going to be communicated to the internet so you can deploy updates to it. That's one hack away from learning that robot into a surveillance device that has all the pictures of the inside of my house. Right. And so, and so we believe that, you know, operate the operating that the, how you can connect the intelligence of the system to the networking stack is something that is governed at the operating system layer of any of any, you know, technology product.

48:39And so the operating system layer of the stack is the right place to deploy safeguards. And so, yeah, and how is taking, you know, when you started fathom five, like, how do you take in things you've learned there and maybe tried to speed up or shortcut. What are some of the things you learned in building your first company and now, you know, Calibur and, and like, what are some of the, the, like, go to things of it. All right, starting this new company, I need to do X, Y and Z first. Yeah, let me give you, let me give it to one is kind of like culture and one is like how to how to lead technology teams. So culture, I, you know, again, being in a kind of a hot startup town in Austin, but having previously been, but I end up in San Francisco in Boston and all these other places on a pre regular basis, right. So I see a lot of this.

49:39And number one differentiator between what I call the wantra panoers and the entrepreneurs is work. And there are, there are people who want to go to the free tequila and chicken night and all of the entrepreneurial startup stuff. And there are people who want to go with their team and grind. Yeah, I don't care how smart you are, how good your inside is or whatever, like nobody changes the world on part time, but. And so if you know, so your pitch deck, whatever it is, talked about how you were going to go change the world, you've been the world to your, or to your view, right. And then there are an overwhelming number of wantra panoers that will try and do that on part time. And so, so I was blessed to have a work ethic, you know, built into me, starting my grandfather with him on his ranch, all the way through the military to get out.

50:40So I only knew one way of work and that was way to work hard, right. And that turned out to be the cultural thing that I see missing in so many different places. And then I think and and and not willing to tell other people the work hard, the ability to be there and be the example of how hard we're going to work, right. That's so important. And then I think the other thing I took with me was, how to build good technology. And if you don't mind, I'll tell one more story as we round out and now, right. I think you can't have been in the technology space and not heard of agile. Right. It's just a thing of a talk. Lean six sigma agile. All right. All of all the buzz, right. And so what I love is, is like stories about human connection. And so there is, you know, the web, the original agile manifesto is still on the internet and it's original form.

51:44It looks like an awful website from the like from the early 1990s. It's like agile manifesto. And so what I love about that group of people that is kind of fuzzy in that, you know, in that in that old picture is that human beings. Took up the idea that you could build meaningful things out of code in the mid 60s. Right. And by the, and in 30 years later, 25, you know, in there in the early 60s, you know, approximately 30 years later, early 90s, the people who were the first generation of humans to ever try and build something useful out of code instead of aluminum or wood metal or silicon or something else. Got together and said, what have we learned to pass on to the next generation? And they wrote this and they wrote the agile manifesto. And what they talked about, it was a craftsman's movement of this is how you, this is what we've learned about how to build thing quality things that of code.

52:48It was important because code is a different building material than silicon or aluminum or steel. Right. And so every building material has the engineering principles you should adopt that that maximize the usefulness of the thing you're building with that material. And so I joke around like the good of the counterpoint is if I try to weld wood, it's not going to go well. If I get, if I get up my welder and I try and I take do it and I do two oak boards, like I'm about to start a fiber. It's not going to go the way I think it is. And so, and so what the agile manifesto did was it laid out the engineering principles from the first generation of humans that tried to start building things out of code. And, and so, and then McKinsey and Bane and Deloitte and everybody else thought, ooh, here's an opportunity for me to sell consulting hours.

53:48So they became the religious practitioners of method and process that a certain set of meetings and all of this stuff right in order to implement this agile process. And they lost sight of the of the human connection, the real story there about about about what kind of what's in sconce and that and the azure manifesto. As I, I built projects, you know, my whole life. And then in the latter part of my time in the military, I got to lead graduate students building projects and start to work with them and how to implement these ideas. And then in fathom five, we got to ask the question, how do I go from a requirement driven world that's not going to change in the department of defense. And actual implement these concepts about how human teams should work together to deliver quality with code. And we developed some, I think, very useful practices for how to how to deliver quality. And as a result, fathom five was the first, you know, the first company to build a program of record.

54:58So not a demo or product expert experiment, but a national program of record AI deployment inside the inside the Navy and put on ships. And so we now in caliber, and we get to say, OK, now we want to go do something else really hard. We want to be that trust and security layer that allows the rapid composition and. And a bit of physical AI, but we get to inherit like how to do something that big and that hard from having done it before fathom five. Yeah, yeah, and it's always that I feel, especially and this is, I think, the scary part. And I think that we're starting to see some of this right is this idea of Congress or, you know, government really was clueless about AI and putting in the right types of laws or restrictions. And it's almost like are we too late like the cats out of the bag, Pandora's box has been open. And now, you know, we're barreling down this hill. And then you have these big companies that are too afraid, you know, to fail. So they don't want to move quickly.

56:01And so it's like, you know, trying to turn the Titanic. And then you have, you know, these small startups who aren't really caring or thinking about like, OK, how do we do this in an ethical way that's not going to destroy humanity. It's like they're just like, oh, like, let me try to get some VC money and like prove the concept on this thing and put it loose on the internet, you know, to get a bunch of users. And so, yeah. So where do you find that balance of, of, of moving fast, but then doing it in a safe way. Yeah, that's a great point. So I think that it is about picking the domain to go fast in. Right. AI is not the appropriate solution for every problem. And there are, there are some problems that we probably shouldn't go after first. And so, and then there are other domains where there's a lot of guardrails already built in. Right. And so, you know, off the top of my head, domains we shouldn't go first.

57:13Online, like suicide crisis interventions. Right. Like when we have a human being that is, is decided to call a suicide crisis line, we could scale that by having them talk to a chatbot. Right. But, but that's probably a horrible idea, even though it's technically do up. Right. And so we need to, we need to define domains. And so that's an extreme case. But we need to define domains where we say, hey, listen, we're not going to regulate the technology because it's inherently, it's inherently dual use that it's inherently appropriate for many different things. But there are some things where we're going to say, hey, you can't apply it in this domain yet. And then there are other places where there's lots of safeguards built in and people. And people, I thought, by the way, I thought the debate about anthropic and their use of, you know, the recent debate with anthropic and open up.

58:14Yeah. How they pulled out said, hey, we don't want our, you know, technology to use autonomously to drop bonds on people. Yeah, I think, I think there was a much better debate that absorbed all of, you know, those were, there were some important questions being asked, but it absorbed all of the energy in the ecosystem to talk about other better questions. And so I, this is one that I, it's kind of a, it's a thought experiment I've been running with people lately is since the, you know, let's say it's since since 1941. Since we enter World War II. The most dangerous technologies in the world have been prototype to experiments and experiment with and reduced practice by the United States Department of Defense Department of War now Department of Defense now Department of War again, right? Yeah, with probably with one of the best accident safety records of any organization anywhere.

59:14So think about all of the horribly dangerous things that we've never had an accident with nuclear weapons. We've never, there has been zero accidental nuclear weapons. No Americans have been accidentally killed, but we haven't had a trinol. Right, we haven't and chemical weapons like we haven't had a chemical weapons release or a use of chemical weapons against America and ever. And though this goes on and on of the dangerous technologies that the US Department of War has successfully transitioned into safe and ethical use in armed combat with allow it while restricting their use in other domains. So although it's counter-intuitive, there are a couple of things about the Department of War that are unique that don't exist in commercial organizations, the first of which is it's full of skeptics who think the whole AI thing is BS.

1:00:16And there are empowered skeptics to say no, you can't do that. And so there is that there is an empowered testing evaluation organization that can say no, there is nothing like that in entropic or open air or or the corporate that are adopting them, right? Because everything is is market driven. And so you have people in those in the US Department of War who aren't financial driven, who are ethics and policy driven. And so that's one thing. The other thing is there's a fully funded testing evaluation organization that isn't competing for budget from the product team. And so and so structurally we get into it more and more in another call, but structurally, although counter-intuitive, there are a lot of reasons to say that we should let the military have an unregulated experimentation with this to get as far as head as possible because they've got the best safety track record, a clear,

1:01:28right? Like in all these other reasons, right? Yeah, yeah, that totally makes sense. Well, listen, man, I have thoroughly enjoyed hanging out with you and just learning from you and hearing your experiences. And so thank you so much for for joining us and and sharing your story. Mark, the pleasure is all mine. Well, happy to come back any time. Yeah, I'd love to. I'm there's a lot more that we can talk about that I'm interested about, but if you know, if people wanted to connect with you, what's the best place to connect? Absolutely, you know, just connect to connect with us on LinkedIn and and and we'll get you connected up with our feed. We try and we try and send out kind of a monthly kind of observation of what we see going on an R ecosystem and and love to comment and interact with folks on that. Caliburn.us is the website. Sign up and join the voice and join to kind of let us hear you and tell us what you think about what we're saying.

1:02:29Yeah, nice, awesome. And then I always love to leave people with, you know, one word of advice or one takeaway to say, hey, starting next week, you should do this to grow yourself or grow your business. Focus on this thing. What would that advice be that you would give to somebody for Monday morning? It is spring. You turn off the digital and grow something. Grow a vegetable, grow a tree, go to home, like, like, like, take care in something that takes a long time to develop. All right, get out there and grow a vegetable and maybe two, if you grow a tomato and jalapeno, you can make some salsa. So, there we go. It means go do something in the real world. Yeah, girl, girl, I love it. It's spring. That's right. Hey, thanks so much for hanging out with us. Hey, if you go to the FridayHabit.com, you can find channels for this episode. You can also find links to our websites and ways to get in touch.

1:03:29And at the bottom of the page, you can download our guide to the Friday Habit System that will show you how to set aside one full day each week dedicated working on your business instead of always in your business. You can hit us up at hello with the Friday Habit.com. And until next time, remember go outside and live every day like it's Friday.