From Navy Ops to AI Solutions: Modernizing Federal Service | The Pair Program Ep68

Speaker A: Welcome to the PEAR program from Hatchpad, the podcast that gives you a front row seat to candid conversations with tech leaders from the startup world. I'm your host, Tim Winkler, the creator of Hatchpad.

Speaker B: And I'm your other host, Mike Gruen.

Speaker A: Join us each episode as we bring together two guests to dissect topics at the intersection of technology, startups and career growth. Welcome back to the PEAR program. I'm your host, Tim Winkler, joined, uh, as always by, uh, my co host, Mike Gruen. Mike, uh, today is Cinco de Mayo, uh, which, believe it or not, is one of the top five drinking holidays in the US Right up there with New Year's Eve and the Super Bowl. Souls researching that. They said $600 million is going to be spent on alcohol today. Um, will you be partaking in, in any of, uh, these Cinco de Mayo festivities?

Speaker B: Probably not. Uh, I do find it funny that we make such a big deal about Cinco, uh, de Mayo here in the US I think. But anyway, um, also I'm trying to figure out what the other five holidays are. So St. Patrick's Day is obviously one. I'm just gotta be one struggling with the fifth. Uh, but anyway, Fourth of July maybe. Oh, probably good call. Um, yeah, no, probably not. Uh, I have a lot to do. I assume, uh, will you be partaking?

Speaker A: Yeah, I'm going to open a Corona app right after this recording.

Speaker C: It's too early now.

Speaker A: Yeah, for our listeners, it's 11 o' clock on AM on the east Coast. Um, no, I think we're actually going to host like some neighbors for dinner and my wife, uh, makes this like key lime pie margarita. It's pretty good.

Speaker B: Nice. That sounds good.

Speaker A: Um, all right, well, yeah, just a quick preview for our listeners today. Um, we are not going to be discussing. Discussing, yeah, uh, pairing the best beer with tacos. Uh, we're going to be diving into a topic that sits at the intersection of public service, national security and artificial intelligence. Um, and we're asking how can we reframe Federal Service as a compelling career path and how can tools like AI make that path even more impactful? And, uh, so to do so, we've got two great guests, uh, to tackle the topic. First off, we've got Mike Frank, uh, Deputy Secretary, CTO the U.S. navy. Uh, Mike brings, uh, a blend of experience from the Marine Corps to Federal innovation leadership, to working with some of the world's largest consulting firms like Accenture and Boston Consulting Group, uh, to help drive transformation across one of the largest institutions in the country. With the Department of Defense. Uh, Mike, thanks for joining us on the pod.

Speaker D: Yeah, thanks so much for having me.

Speaker A: All right, and then joining, uh, Alongside Mike is Dr. Jim Liu, uh, founder of an AI consulting firm, Socat. Uh, Jim's also an associate professor of finance at Johns Hopkins Carey Business School. Jim's, uh, work at the intersection of AI, blockchain, and finance has not only shaped academic research, but has also informed how government agencies can adopt these tools with purpose. So, Jim, thank you for also joining us on the podcast.

Speaker C: Absolutely. It's an honor to be here.

Speaker A: Awesome. All right, now, before we dive into the thick of the, uh, discussion, we kick things off with a fun segment called Pair Me Up. Uh, here's where we all kind of go around the room and just rattle off two things that just belong together. So, Mike Gruen, you're. You're always leading us off. Well, what do you got for us today?

Speaker B: So today we're just going to go with, uh, Thursdays and poker. Uh, I don't know what it is, but, like, Thursday night poker has just been a thing for all the way back to college. Um, I currently play in a group. It's funny because, uh, with Jim on the call, uh, I play up in Hampden with a bunch of degenerates and a coup, uh, professors, uh, from Hopkins.

Speaker C: Uh, so wait, wait, I might know these guys. Let's say their names.

Speaker A: Let's call them out. Let's call these degenerates out.

Speaker B: That's the name of the club. It's actually. Yeah.

Speaker A: Anyway, I like that. I like. I'm still waiting on my invite, by the way.

Speaker B: Yeah, I know.

Speaker D: Yeah.

Speaker A: Like, you know, whenever you're ready to cross the state lines, you let me know. Um, I dig it. Are you, uh, do you find yourself in the winner circle often? Or what's. How's your win rate?

Speaker B: I do okay. I mean, it's home poker. The, uh, money, it's most. A lot of games of luck, and it's sort of where the money ends at the end of the night. But, yeah, I do okay.

Speaker A: Cool. Yeah, I've, you know, living in Leesburg, It's a quick 30 minutes to get to Charlestown Casino. Ah. So I'll go up there every once in a while and do a cash game with, um, a neighbor of mine.

Speaker B: So.

Speaker A: I love it, man. It's a good, good time. Um, cool. And Thursday, huh? Huh? Just kind of like, something to look forward to.

Speaker B: Yeah, definitely. I don't know, it's just, um. There's even a Book called Thursday Night Poker that I read a long time ago. But there's just something about poker and Thursday nights that go together because it's.

Speaker D: Yeah.

Speaker A: Anyway, yeah, good pairing. All right, I'll jump in. I'm going to stick with the Cinco de Mayo theme. I'm going to go with a timeless classic, which is tequila and lime. Uh, I just feel like you can't really have one without the other. It's a perfect compliment. Kind of cuts the burn of the tequila if it's, you know, throwing back a shot or just kind of sipping on. I love, like, Classe Azul. Um, so kind of need to have that. That lime compliment, uh, by its side. So I'll go with tequila and lime for the pairing. Um, and let's pass it around. So, uh, Mike. Yeah, quick intro. And. And your pairing.

Speaker D: Yeah, absolutely. So, uh, Mike Frank. I'm the Deputy CTO for the Department of the Navy. I'm also the, uh, cyber portfolio lead for the Marine Innovation Unit in my reserve career pairing. Uh, I'll say Memorial Day weekend and the NCAA Lacrosse tournament, that has been one that is always going back for me, and, uh, they got to go together.

Speaker A: That's awesome. Yeah. Any, um, any teams you're shouting out?

Speaker D: Um, I actually, I think selection Selection Sunday was yesterday, and I don't know the results. I don't even know who's in right now. Um, but, you know, it's. It's been a good season. West Point's been having a good season, and then they. They dropped one. So I don't know if they. If they made it. I gotta. I gotta check that after this.

Speaker A: Nice. Yeah, I know it's, uh, it's big in Maryland, so, um. Yeah, got. Got it quite a bit. Um, cool. Uh, yeah, thanks again for. For joining us. And, Jim, quick, uh, intro and your pairing.

Speaker C: Yeah, absolutely. Um, hi, guys. My name is Jim Liu, and I'm the founder of SoCat, named after my two daughters, Sophie and Catherine. And my pairing is, um, Vibe coding and the mba. That's a, you know, for coming from the business school MBAs, I think, um, all MBA students. These are business school students. Masters and business administrations are going to be Vibe coding. The better term is, uh, using the prompt and coding with a prompt. And I think that's going to be a trend that we'll see in the business school, and I'm hoping that it's going to be a trend that we see across the DoD, because I have about 114 students, and they all can do it. It's very accessible and I think this is uh, part of a trend that hopefully we'll discuss a little bit later. But as um, AI is already cooked into everything, it's becoming easier and easier and uh, more accessible to just, you know, the non programmers, the business school students and business professionals.

Speaker A: Yeah, it's cool. It's been taking off. Uh, you hear a lot about it and it's a great way to get folks into tech and uh, make it a little bit more accessible. Have you done uh, any projects yourself that you're proud of?

Speaker C: Oh no, I give these projects. It's a lot of fun. The first project is always the Snake game. Uh, do you remember the Snake game? What is it? Could you code the Snake game if I asked you to?

Speaker B: I couldn't. I could, I did

Speaker C: try to code the Snake game. I guess that's a better question.

Speaker A: I haven't though.

Speaker C: I'm not a, I'm not a game programming expert at all. Right. I'm like a Python hack. But um, with Vive coding and you know, any of these platforms, you know, we use Windserve, but there's Cursor, there's many of them. You can basically type in a prompt, I need a Snake game. You know, I want to play it. And you can. That's the prompt and you push enter.

Speaker A: Yeah.

Speaker C: And then it starts coding it up for you. And it's really interesting because, um, you know, once we get the students to do that, we give them a couple of other projects. One of the projects that's more difficult is uh, flying blind. I basically give them a zip folder and I tell them nothing about what's inside there and they have to figure it out. And the only requirement is add value. And so what I do is week by week we, you know, build their skills. Um, and a lot of it is confidence, to be honest with you guys, um, you know, giving them stuff and you know, working with them. Uh, their submission on their homework assignments is a three minute video and explain what they did. And you know, we posted up in the discussions and you know, people like the ones that they like and they're also learning from each other and I'm also learning from them. And then you know, we go on to stuff like um, analyzing um, you know, earnings reports from three companies like Amazon and um, Meta, Facebook and Nvidia. And then you know, take the point of view that you're a uh, value investor. You know, Warren Buffett's retiring, so you're a value investor. Choose the one stock that you know and make a case for that value. And then, you know, now you moved on the team with Cathie woods and now you're a growth investor. Right? So now make a case and, you know, create a website to explain what you're doing. And they can all do it with a vibe coding. So it's, it's, it's a lot of fun.

Speaker A: Cool. Yeah. Vibe coding MBAs. I like that. Um, yeah, we'll probably lean into some of that on today's discussion. But yeah, let's, let's, uh, let's, let's wrap up the, uh, the Pair Me up segment. Dive into today's episode. So, like I mentioned earlier, uh, today's conversation is all about making federal service more appealing and impactful in the modern era. Ah. So we'll explore how advanced tools like AI can empower public servants, uh, help close some of these skills gaps, uh, spark a culture shift across government. Um, a couple of those themes is how AI access can be used to attract and retain top tech talent. Uh, why public service, even if it's for a short period, can be a very fulfilling, uh, opportunity. Uh, the culture and operational barriers to innovation in government and how cross agency collaboration can help accelerate this type of transformation. So lots of unpack. Uh, let's jump in. Mike, I'd like to start with you. You know, you've worn many hats. Marine consultant, now a senior tech leader in the Navy. What drew you back into government service? And how do you think we can make this path more attractive for the next wave of technologists?

Speaker D: Absolutely. Yeah. I mean, the simple and quick answer is mission. Right? Um, you know, I've always been, uh, kind of mission driven, mission focused. You know, obviously in the Marine Corps, that's, that's super easy. It's super clear. Um, after getting off active duty, you know, going to business school, that's where I really had the decision of, like, all right, what do I, you know, what do I want to go do next? Right? Like, what do I want to be when I grow up? And you know, business school is a, is a really interesting, uh, time. I mean, it was incredibly valuable for me. And I know a lot of peers who have come off, you know, active duty, gone to business school. It's been valuable for them too. But I mean, when you walk in the door, you're immediately getting recruited. You know, day one, like, there are companies there, there are different industries. You know, consulting, finance are the big ones, you know, investment banking, um, but there are, there are all kinds of companies come in, pitching you and you know, you barely even have time to catch your breath, let alone, you know, know exactly what it is that you want to do. And, and, you know, for folks coming out of government service or military, because we had folks that were coming, you know, directly from either, you know, Peace Corps or Teach for America or, you know, prior government service, you know, everyone in that capacity is kind of like, all right, what, you know, what the hell is going on, right? And you're trying to figure out what exactly you want to do, what you want to go be. And you know, for me, consulting was a great opportunity, was a really. Was a really great way to, um, get a lot of different kind of experiences, work with a lot of different companies. Um, but for me personally, where I spend my time was consulting for the federal government, right? So I was a contractor. I worked with Department of Energy, I worked part in the state, worked with, um, you know, a lot of. A lot of my time was with Department of Defense, um, but kind of all over the place. And, you know, that for me was. Was giving me the ability to scratch the mission itch, uh, while still being in the private sector and still kind of experiencing what I needed to on that side and, you know, kind of gain that. But to answer your question of like, why did I come back? Why did I join federal service as a, you know, as a GS employee? Um, you know, that really, again, came down to mission and timing. Um, so, you know, as. As anyone who's been a contractor or anyone who's been a federal employee has seen, you know, we need both, absolutely both play a critical point, uh, you know, part in the. In the mission. Um, but there are differences. You know, there is only. There is a limit to what you can affect as a contractor, um, and, you know, a limit to kind of what you're able to accomplish as a federal employee. So, like I said, it's symbiotic. We do need both. But for me, after spending so long as a federal contractor supporting the federal government from the private sector side, I did want to step onto the other side and have more of a chance to impact directly. The other piece of it is timing. I mean, right now we are in a. I'll call it a little bit of a renaissance in kind of defense, um, you know, Defense acquisition defense, um, you know, the defense industrial base expansion, um, and so there's. There's a lot of private capital rolling into the defense industry right now, which is spurring a lot of innovation, um, which, like I said, is a really critical time given what we're seeing on the geopolitical landscape. Um, so as we shift to the Pacific, we've got various folks who have predictions on when things may happen, um, in the indopacom aor. But really what we all agree on is that the next couple of years are very important, regardless of what happens the next couple of years. And our buildup is very, very important. Which again, you know, was, was the main driver behind my timing on why I came in now.

Speaker A: Yeah, yeah, I think it's interesting too. It's like, um, you know, kind of grow up and growing up in D.C. um, you know, and having a lot of friends or family that have, you know, worked in federal services, you know, oftentimes it's kind of looked at as like, you know, that's it, you know, you're going to be in the service for you know, 30, 40 years. Um, but there's, you know, there's another angle here of looking at it even if it's just as a rotational kind of opportunity to where you can kind of get some of that experience sitting in a seat of uh, somebody that's in customer, end user, um, and then taking that over to industry, uh, and using that to your advantage. And I think you're right in the sense of timing. We talk about it all the time on the podcast. Is this kind of renaissance and very easy to point out from the global politics, uh, you know, happening today of like defense tech and a push for modernization and, and doing it in a more rapid and agile uh, fashion. Uh, so we're seeing you know, a new peaked interest in getting involved and getting behind like that mission. Uh, so I'm glad that you kind of pointed it out and it's cool to get that perspective of somebody who's jumped from consulting, you know, to work directly with federal services. Uh, Jim, I'd love your perspective on this topic. Given you're a professor, you know, you work closely with students and early career professionals. Are you seeing a shift in you know, either how they view federal service, um, in mission aligned roles like national security or defense tech?

Speaker C: Yeah. You know, first off, Mike, you know, thank you for your service and I think you have an amazing background, um, coming from some of these elite consulting firms and then also going, and then you know, working inside the government so you know, all the angles. So these consultants, these guys come up to you, you've been in their role. Right. And you know, you know what they're, what they're all about. Right. And I think that's just gives you such a great perspective for the role that you're trying to do, which ultimately you have to kind of make some changes there. Right? Um, you know, people, um, in Johns Hopkins, you know, we see a lot of people transitioning in, um, from one side to the other side. And a lot of times they're trying to reinvent themselves. Um, some people will go to, um, you know, the public services, some people go to healthcare. Some, uh, people want to go to Wall street and so forth. But it feels like most of them want a bigger challenge. So they may be mid office, back office, you know, earlier in their career. Now they want to get out, you know, to the front office. Um, so, um, we see that. Um, I think what's important is that, um, because we're located sort of in the D.C. area, we get a lot of, um, you know, people, um, some military, some not. I mean, I've had, I've taught students in most of the different agencies.

Speaker A: Right.

Speaker C: And whether they're working part time or full time or they get a job and they move on. Um, so, yeah, I think it's, it's, it's great. Our location, um, is, is wonderful, um, too. And then, you know, when I go out there and talk to people in D.C. i meet a lot of people are alarms, right, From Johns Hopkins, and they talk about their time here, which, which is great. Um, on the DOD side and the intelligence side. Um, you know, I know a few, right. And um, I think there's a lot of guys, some of them who start cyber companies and you know, government contracting companies, very successful in, um. So, um, I think all the universities have their, um, kind of star, uh, entrepreneurs coming out that do, um, government, um, contracting work very successfully and they, and what's really nice is they go back and they support their university. Right. Um, so it's a very good ecosystem and there's a lot of real great opportunities just around the beltway.

Speaker A: Yeah, I'm glad you point out, like the location thing, it's uh, something that I've seen are, you know, locale or ecosystem kind of suffer from over the years is breeding great talent, but then losing those folks to that want to go to Silicon Valley. They want to go, you know, different parts of the country. Um, but making more of an intentional push to keep that talent here and encourage them to get involved, uh, you know, with federal services or even local, you know, startups that might be innovating, you know, uh, on behalf of or building products that will eventually, you know, be acquired by the, the defense ecosystem, um, trying to encourage more folks to be more in this setting. And I think that is part of this push of return to office too. You're seeing a little bit less fully remote, uh, and looking for folks to come back into a setting to innovate and be a part of that, um, ecosystem. So, um, I wanted to, uh, also make this analogy because I'm curious on how you. How you kind of vocalize, um, this Mike. Uh, you know, this working. You know, most folks that have worked with. In a very large organization, they kind of. They know what it can feel like to not know, like, how your efforts are making an impact. Uh, it's kind of like this small fish in a. In a big pond scenario. Um, you know, how can, like, personal satisfaction impact be better communicated across, like, the federal government?

Speaker D: Yeah, I mean, it's a. It's a great point. Right. I mean, I think anybody coming from a smaller organization or a startup, you know, you get used to this kind of, like, immediate feedback loop where, you know, you take an action and you see results. And that can come in the form of, you know, personnel, uh, and how your team is operating, or it can come in the form of, you know, just revenue, whatever that is. Yeah. To your point, in larger organizations, that is much less the case. Uh, you know, I, I usually liken it to, uh, a carrier. Right. You know, an aircraft carrier. To turn an aircraft carrier, it takes a lot of effort. Um, and usually you're only turning it, you know, a couple degrees at a time. You know, these aren't. These aren't major turns. So when we talk about, you know, making change or, or even, you know, influencing change in the federal government, we're talking about really small things, um, which, you know, zoomed out. You may say, well, what's the point? Or kind of like, what impact has that actually had? But I think the longer that you're there or the closer that you are to it, uh, you kind of understand that, you know, you can achieve change. You can achieve, you know, positive improvement or excellence or whatever you're. You're striving for in pockets that will then, you know, if you start to. To stack those, if you start to just like, keep putting those in the hopper, you know, it. It expands. Right. You know, I think about culture as, uh, kind of the last, you know, the average of your last thousand experiences. And that can be on an individual basis or an organizational basis. And so in order to kind of change that average, you need a lot of new experiences coming in.

Speaker C: Right?

Speaker D: Like, you need a lot of wins, you need to put a Lot of things on the board. And that's, that's how I think about it for, you know, for large organizations, you know, whether that be giant companies that you're working for, um, or more specifically the federal government, um, because, you know, there, there are a lot of wins. We experience wins all the time. And it, that's, that's, you know, by attaching yourselves to those and, and you know, hopefully, you know, publicizing those as much as possible, you know, you keep the motivation up. Um, and then the more of those that happen, you know, it's, it's this kind of virtuous cycle where the more of those that happen, you know, ultimate, ultimately, you know, culture does start to shift very slightly, even if it is just a couple degrees at a time.

Speaker A: Yeah, it's a good take. Appreciate that perspective. Um, like the thousand things combined, uh, get that cumulative, um, uh, point of view. Jim, uh, during our discovery call, you were very passionate about using AI as a tool to empower public servants. What's your take on how AI can practically support federal employees and how you envision AI serving as an outlet to help attract and recruit a new wave of, of talent to, to join federal services?

Speaker C: Yeah, well, you know, earlier we had this conversation. I think, um, the US is ahead, but not that far ahead according to Jensen Huang. Right. And, um, what my idea was, um, you know, we have all these wonderful technology companies in Silicon Valley with the most cutting edge, uh, technology, including xai. We should ask Elon, hey, give a copy of, you know, your strongest GROK model to every Fed who's serving you across all the agencies. And you know, not just ham, but we ask OpenAI, and we ask anthropic, we ask all of them, let's put this in the fingertips of the people who are using it to solve problems for, you know, the American taxpayer and keeping us safe. And what I, what I think would happen, at least this is what happens in the classroom, is people start to see where the edge is, how far you can push this technology, uh, how valuable is it really? And then it's not, you know, obviously you can't do everything with AI, right? And there's a lot of hype. But what's really fascinating and interesting is that as you keep using this technology to try to solve real world problems, the, uh, technology, the AI only gets better. So last year you may be struggling with this, right? Hey, I want to pick stocks with AI, but it's not very good at, you know, reading an earnings announcements or parsing to a 10k. But then you just wait like nine months and then all of a sudden, you know, it compare, compare, like three different, different stocks together. Whereas, like six months ago, a year ago, we couldn't do that. Right? It would hallucinate. And what's important is that, um, a lot of people sort of miss this point. The whole AI thing, it's kind of like tinkering, so whoever tinkers the most and shares that moves ahead. So I think that's kind of lost. And people are like, oh, AI, I'll never understand AI. I'll never understand AI. And that's exactly the experience in the first class. I say, hey, we're going to vibe code. And they're like, oh, no, no, Professor, I can't, I can't code. I'm not a Python coder. I can't do that. I'm like, okay. You know, there's a new coding language, it's called English. Can you speak English? I can do that, Professor. And then so you start building some confidence. You put these tools in their hands and then they get excited. They're like, oh, do I only have to use Windsurf? I'm like, no, use cursor. Here's Google, you know, uh, LM use that, it's free. And so then they start searching around and they say, wow, this is really interesting. But I think what's important is to support their development, right? So empower them. Challenge our Silicon Valley friends, right? And then, you know, challenge Ivory Tower as well. But put it in their hands and let them, because they're on the front lines, right? They know what the problem is. And if they start, you know, breaking through and getting their wins, as sort of Mike said, right? Getting a bunch of wins, have them share that, share it across, you know, DOD shared across government and say, I was doing XYZ and I just did this and it opened this up. And look at this. This is my fee performance indicator. It used to take me months and, you know, weeks or whatever. Now I can do it in days or minutes or seconds. Right, and so how did you get there? Well, here are some of the prompts I use. So highlight that across government and share that, you know, openly to the extent that you could share that. But I definitely think in empowering everybody with these wonderful tools. And the other thing is, these tools are only going to get better. So when you couldn't do three months ago, you absolutely can do after, um, the next innovation, the next wave, right? And I think that's what's important to realize. And it's Very challenging, right? I'm trying to teach this stuff, I'm trying to stay ahead of it and learn as much as I can and then go in the classroom and regurgitate it and provide resources. But it is really exciting and fun and if you want to be challenged, oh my goodness, right? There's so many problems in the government that you could solve with this stuff. Um, so I think empowering our workforce. I'll give you one anecdotal example. I had a friend of mine, uh, visit me from, um, Oklahoma.

Speaker B: Oklahoma.

Speaker C: We grew up together in Oklahoma. He had a job site in Maine. He was driving through and I said, hey, Shane, come hang out with me. And so he, he sat into my class. You know, he didn't go to college, he graduated from high school. And you know, he works sort of blue collar jobs. And um, I said, hey, Shane, come over here, I'm going to teach you how to vibe code. And he's like, oh, I don't know how to. Same exact response, right? I'm like, shane, come on, just sit here, you know, create the Snake game. And he did. He was so excited about it. He started, you know, putting different faces on the snakes and, and then he did Pong. And I said, cross the two. And then he did. Okay, so what's interesting, the Snake game code is there. Pong's code is out there on the Internet. But crossing the two is not there. So that's where the AI is getting creative. But what I was thinking while he was doing this, uh, is, oh my goodness, you know, this American dream that we all are, you know, it's usually immigrants like my parents immigrated over here and everybody comes to the United States to sort of live the American dream. But what if we took the people in America, like my friend Shane, right? Um, you know, he's a really smart guy, but he's not in such smart places, right? His talent is not really being used. But you start giving them these AI tools. Everybody, every one of us knows one friend who's like super smart, who's in somewhere, you know, probably not utilizing their potential, right? But imagine you brought like one in. Come solve this problem for the DOD or solve this problem for HHS or whatever it is. Here's some tools. And if everybody did that with one of their friends that they know are talented, you know, we could have The American Dream 2.0, which is the, you know, taking an American in America, you know, a really smart guy, not in a smart place, and empower them, encourage them to come in. I think that could be, you know, really interesting. And, you, uh, know, I'm kind of calling it The American Dream 2.0. And I think this is what a lot of, you know, people felt like they, they got left out on. Right. Um, but, you know, I don't know, what do you guys.

Speaker A: Well, you know, Mike, I'm curious to hear it from, you know, from the inside. Right? You know, you're, You've, you're a big advocate for, you know, agile, you know, tech adoption by the dod. And, and, and it's apparent, too, like, the Navy is, we would say, at the forefront driving a lot of this change. We actually hosted Justin Finnelli on a. On a topic not long ago, uh, about driving more tech modernization and doing it through different creative outlets, like structured piloting. How do you kind of see AI playing a role in empowering your teams within the Navy? And what are some of those hurdles to getting this AI access into the hands of the public servants?

Speaker D: Yeah, I love what Jim is doing. Um, I love the way he was talking about, you know, there is this just hesitation, uh, intimidation, you can say, even for folks who, you know, haven't really delved into kind of what the capabilities are yet. And, you know, that barrier is high. That barrier to entry is seemingly high, I should say, because it's actually not right. And Jim, I think you've probably seen this with your students and, you know, everybody that you've kind of brought into the fold to say, look, it's not as hard as you may think. I mean, we are in a unprecedented time in the federal government right now in terms of kind of shifting numbers of personnel budgets, kind of uncertainty, uh, for the federal workforce. And so what I'd say is that there has never been a more kind of important time where we're going to need to upskill folks really quickly. Um, and it just happens to be at the time where AI is making legendary strides kind of every couple months here. So I think we're seeing kind of this convergence that, you know, wasn't maybe wasn't intentionally planned out. But we are here now, and we've got an opportunity. So, you know, for us in the Department of the Navy, what we're really focused on is, um, one, piloting a bunch of different tools, so looking at different models that we can use, different ways that we can get them into the department. Two, pushing out policy on, um, you know, from the departmental level on, you know, what models can be used, uh, for what types of use cases, in what scenarios, how we deal with the classification Issues how we deal with the classification by aggregation, issues that arise when you start pulling all this data together. Um, but outside of that, there are tons of use cases where we see this being an immediate, um, increase to our ability to execute the mission, both back office, front office, um, edge use cases. There are a lot of ways where we're going to need to, like I said, upskill our workforce. Because, as you know, as we're looking to decrease the population of federal employees BY Anywhere from 8 to 10%, you know, we've got folks that are leaving through the, um, deferred resignation program, taking, you know, voluntary early retirement, things like that, um, where, you know, we are dealing with a reduced workforce. On top of that, you know, business services contracts are getting cut. So essentially, you know, we have fewer resources. Both internal federal employees and external contractors do the things that we need to do. So what's the answer? Right? We need to turn to technology. We need to turn to the tools that, you know, Jim is, is teaching to his students now. Um, and getting a generation of folks more familiar with how to use them, uh, to do more with less is really what it comes down to.

Speaker B: And Mike, I think one thing I wanted to touch on that I, um, or rather you touched on a little bit, is with those people leaving, I think AI is a great opportunity for that institutional knowledge, that tribal knowledge, right? Like, that's a good place for this stuff to reside and be, you know, as people transition out, that's always the hardest part, is that knowledge transition. Um, and then one thing both of you were sort of talking about in terms of, like, there's this intimidation factor, right? Like, hey, I don't want to use it. I'm not that person. Whatever. One of the things I've seen, and I'm curious how you do, how you deal with it, is the, oh, uh, the AI gave me the wrong answer. It doesn't know what it's talking about or, oh, it gave me this thing. And it's going to be more work for me to fix it than to just do it myself. I'm curious how you guys tackle that, because I think it's the other side of the coin of the people who are like, oh, I don't want to do this, because it seems like it's more work. And I'm just curious how you guys tackle sort of helping people through that over that hurdle.

Speaker D: Yeah, absolutely. I'd love to hear Jim's answer, but, I mean, I'll just touch on it real quick. From the DoD point of view, I Think, like, if you think about the normal technology adoption scale, you know, the government's always kind of a little bit behind, right? So if the. The general population is maybe in the early adopters, you know, we're still in the kind of visionaries or, um, you know, that far left piece. And I think we are going to, um, continue to see kind of pushback if there is no traceability. So traceability is huge in terms of the models that we're using. Um, we're going to see pushback in terms of any kind of operational use cases. But those business use cases, those back office use cases, I think are areas where we can really start to build trust and confidence in the models to the point where senior leaders are more comfortable using it in, um, let's say, expanded use cases.

Speaker C: Yeah, that's. That's a great point. You know, just to push that further, Mike. Um, I think that's a right way to do it, right? So, for example, like, most agencies has an HR department, they have travel, right? I'm sure when you. You go off and travel, you have to get your receipts and so forth, but you go after these, uh, things that most businesses struggle with. At Johns Hopkins, we have the same thing. We have a horrible. I don't even want to go anywhere and try to hit into that system. I'd rather get my phone and take a couple pictures of our streets and be done with it, right? Like, you know, these simple things that everyone's struggling with. Like, you know, in Johns Hopkins, if we're hiring, then, you know, you have to look at the resume and see if there's a fit. But that's something that happens, I guess, you know, in every agency, right? You know, is this candidate fit for this? How do these people sort of have a career and how do they project? How do they, um, sort of get career advice in a nice way, right? So, um, you know, in school, in a typical way, we manually look through these resumes, right? And, you know, we read the job description, we read the resume, right? But how, how can you use an AI to help you further match that? But you can do even more than that. You know, how can the AI say, hey, you're liking one or two of these skills. If you got that, you could probably have a good chance of hitting this job with some probability right? Now, if you want to hit that other job with a higher salary, you can do X, Y, Z, right? And the other thing that I think is also very interesting, and, um, I was playing around with, um, the AI on the way to, ah, school down in D.C. and I have to go sit and moderate this panel discussion. And I just hit the chatgpt and the Voice and I said, hey, I gotta do this panel discussion. This is my intro. How am I doing? And they gave me really good suggestions. They're like, oh, you're talking too fast before an important word, stop and pause, you know. And I was like, whoa, this is great. I just have, uh, this Voice coach now. I was going to hire one. I don't. So what's happening is as we're, as I'm interacting with it, I'm also testing what can I get out of it, right? And it would be, it's so much easier. I don't know any voice coaches. You know, I don't have that network. Um, so, you know, I ask it a lot of different things just to test it out. But the other thing is, I think, uh, career advice. So imagine if I, you know, I'm not going to join the Navy, but suppose I was really young and I joined the Navy and I'm butting heads with everybody and I want some career advice. What am I doing right? What am I doing wrong? I mean, I'm thinking about my career in Wall street, right? When I first got there, I didn't know what was going on. I didn't know how to behave. I wish I had an AI to sort of say, hey, don't go bother your boss about xyz. You should talk to HR or whatever it is just so that, you know, you have another voice there to help you along, right? And maybe you're, uh, a colonel and you want to become a general, right? How do you become a general or whatever? How do you take your career to that next stage? Well, you know, what, what's going to happen? Maybe it's telling you, um, some organizations to join, and it's probably telling you to expand your network at a certain level. I think the, uh, skills that took you to a particular level in your career, the skills change to the next level, right? And so just to understand that whole path and, you know, get some advice. But I, I, maybe I'm embarrassed. I don't want to go tell everybody, all my colleagues, I'm trying to improve my, you know, these different types of skills, right? And I think that, you know, I think there's some advantages to that. Um, my, my wife, who's the CEO of socat, she says, before you do any business, go interact with AI and see if you're wasting your time, right? It's, it's it's interesting because, you know, you, you can sort of, um. It's a really great sounding board because I think one of the things that is in there that we really don't really, uh, we haven't really pushed hard enough is all the best practices. Now we know coding best practices are in there, right? So we know the AI can code better than the majority of coders, you know, probably in the top three, 5%.

Speaker D: Right?

Speaker C: So we know that. But I also think like in terms of running businesses, it gives us pretty good ideas on their operational side in terms of our careers, right? In terms of some relationships now, you can't go there and blindly believe everything it tells you, right? And you have to use your own judgment and say, hey, does this make sense? Does it not make sense? And then talk to people about it. But it has a lot of really good best practices. And I think that's what's uh, really interesting about this. Not only encoding, but, you know, how do you run an organization? How do you think about even the cybersecurity? One project I'll tell you guys a little bit about is we're trying to modernize COBOL code, modern day languages, right? And um, the AI does a really good job of translating the code. But the more we think about it, COBOL is basically written for business school people who are not coders to move some kind of business process along. The reason why it gets all messed up is contractors get in there generations after generations after generations and they make it more difficult because it's easy to make code more difficult. You just don't comment it or you use terms that are not consistent. You, the coder knows it, but maybe somebody who's doing the process. And down the line they don't. But that kind of gives you, um, it justifies your job. Defendable, good for you, but not good for the agency. Right? And so how do you think about that? How do you use AI to understand the business logic first? And do you have to go through and convert all this code or can you create it very elegantly this way? And those are the things I think are really interesting. And um, because at the end of the day I get a sense, you know, this sort of, um, goes back to what Mike was saying, you know, what's the mission? The M mission is usually pretty simple. So how do we do this to the mission? Right? And we need to kind of unravel this complexity that we've sort of put in there as consultants over generations, right? To defend our existence and our Jobs. We got to kind of rethink that. And, um, you know, I think, um, unfortunately, that type of stuff not only exists in government agencies, but it exists in financial institutions and exists, you know, quite pretty much everywhere where, um, you know, people over time have been worried about their job and their job safety and so forth.

Speaker D: Right.

Speaker C: So they're insulating themselves in a way that is not productive, you know, for the, the organization, you know, ultimately. So, um,

Speaker B: I think there's another, uh, reason for that as well, which is usually speed, right? Like the. Whenever you're, uh, trying to get something done, the first thing you jettison is the documentation. The second thing and is the testing. Uh, so as you know, which. Then you're just hurting future version of yourself or whoever's going to have to inherit the code or whatever. But yeah, it's the same problems. And I think that's another area where AI can really also help is just sort of maintaining that documentation, maintaining that testing and then stuff like that. But, yeah, yeah.

Speaker C: I'm sorry, what do you guys think of. I'll just throw this out there. What do you think about this whole digital twin? So I was at the, um, you know, Nvidia conference, and digital twins for manufacturing and, you know, creating stuff is all over there. It's Nvidia. Everything that they do is first a digital twin. I mean, imagine we had a digital twin of all the government, and so then basically we can go in there and change and see if it works, right? And if it works, then we're like, hey, uh, we'll test it a lot. And if it works, then we try to push it across government. But setting up a digital twin, we're not really going to hurt anything, right? Arguably. But we can play around with simulations and say, okay, what if we did this, this and this? What have we converted cobalt this way? Or what if we try that and had lots of, you know, simulations there? And then we say, hey, this really works. Um, all we have to do is X, Y, Z. So now let's go implement that. Right. You know, I'm just curious, what are your thoughts on that?

Speaker A: Yeah, I mean, we see it quite, uh, a bit. It's actually a topic that we're crafting around is digital twins. But if you put it into the scenario of defense, I think it's super relevant and apparent to have modeling and simulation done on behalf of the warfighter, right. So that we can try to understand, you know, what, you know, what are the impacts before, you know, just putting it directly into their hands and Hoping for the best. So we see it as a huge use case across defense. Mike, are you have any, um, you know, vision into, you know, modeling simulation digital twins and how that's impacting some of your all's projects?

Speaker D: Yeah, 100%. Um, you know, modeling in sim is a huge part of what we're doing right now. Um, and a huge use case for kind of different companies that are coming at us with emerging models and capabilities. But, uh, from a digital twin perspective, I mean, we've been doing this for some time now just around our major platforms. So you think an F35. Right. And a digital twin of an F35 or any of our major ships or any of our airframe platforms. The ability to do predictive maintenance on kind of what we're seeing and what we're pulling from the telemetry data from the platforms themselves is huge. And so that's another kind of definition of a digital twin. But it's something that we have been, um, trying to really get in place now for a while. Um, but now with the increases in just computational capabilities, um, and models, we are able to do a lot more, um, which has been fantastic.

Speaker A: Yeah. I wanted to ask one more question. Just, um, bringing it back into, you know, some of the appeal of working in federal services before we kind of wrap. Uh, Mike, I'm curious if there is. Have you picked up on any sort of shift around, like, interagency collaboration, um, where you're maybe, you know, because we need to kind of, like, pull on what's working and kind of apply that to, you know, across the board. Are you seeing more openness to this? And I don't know if there was like this preconceived, like, uh, you know, the army's doing this one thing. They don't want to expand on it because it's kind of their thing. Is there any shift in that and more of, like, this encouragement across the board of, like, we're in this together and, you know, the mission is to kind of, you know, uh, if it's a race against China, you know, if the army is figuring something out, it needs to be shared over here.

Speaker B: Yeah.

Speaker A: Maybe a little insight onto that.

Speaker D: Yeah, yeah, definitely. I mean, you know, you used to always see the signs, you know, go army, beat Navy or go Navy beat Army. Now it's all, go Navy beat China, Go Army Beach. Yeah. Or as that goes. Yeah, for sure. Um, no, but I mean, you know, I think it's always been kind of tongue in cheek competition. Um, a lot of times, uh, I think everyone in the building gets it right? We're all on the same team. Everybody wants to work together. But to your point, I would say now more than ever, there is a necessity for us to work together and for us to, uh, you know, copy from each other. Right. We don't have the same resources that we did before for everyone to go off and build things on their own. Um, you know, we need to, we need to replicate as much as possible. We need to have joint programs. We need to, you know, in order to save resources. So we, so we need to, you know, copy and copy and paste wherever possible. But the other aspect of that is, you know, when I say joint programs, I don't just mean from a funding perspective, but I mean from an interoperability perspective. You know, when we talk about a, uh, fight in the indopacom or just great power competition in general, these, these new capabilities that we are trying to bring into the department, they are at the joint level. They need to operate at a joint level. And when we think about a kill web, it is no one specific service, it is no one specific domain that is going to have an entire kind of decision cycle across the kill web. It is going to be all domain, all services, all departments that have components and have pieces of it. And so the only way you can build solutions like that is by working together. So, you know, for us at the Department of the Navy, I mean, you know, we are working super close with, with the Department of the Army, Department of the Air Force to make sure that we are tied in lockstep with what they're building out. When we think about space capabilities, when we think about cyber capabilities, you know, all of this, it needs to work together and we need to be talking. Um, so, yeah, definitely. I think there's been kind of an increase in that.

Speaker A: Cool. Yeah, I think it's a good point to kind of wrap on. Um, we're gonna, you know, kind of put a bow on this conversation and transition to a final segment. This is going to be, uh, just a, uh, you know, fun, fast answers. Try not to overthink it. Uh, we call it the five second scramble. Um, Mike, you, you could lead things off with Jim and then I'll kind of close with, uh, rapid with Mike.

Speaker B: Sounds good. All right. Uh, if Socat were an animal, what animal would it be?

Speaker C: Oh, my goodness. You know, have you ever seen that, like, lion where he's just sitting there and all these hyenas are trying to bite his butt, you know? Yes, that's us.

Speaker D: Horrible.

Speaker C: In Marketing. But we can, you know, eat one of those hyenas in two seconds, and everyone's like. Like, bullshitting A.I. you know, they're about or waiting, and then, you know, and then we turn our head right now. You know, I'm just kind of half joking. But, um, you know, we. We think we're pretty darn good at AI and, you know, we. We want to go in there and do that really challenging stuff. Right? Um, you know, my team, it's interesting.

Speaker A: We.

Speaker C: We didn't cover this too much. I mean, how do you attract the most talented people? You go after the hardest problem. And so, you know, we are. We. We say we want to look at the hardest problems across any agency, and then we want to figure it out, because we think we can rally the talent. A lot of them come from Hopkins. They graduate, and they're coming from different places. But, you know, we're always trying to go after that because it's fun and interesting and it's challenging. And, uh, sometimes when we start the engagement, we're not quite sure we can do it. But most of the things. The more you sit there and talk about it and you talk with the customer, the client, right? You start to unravel what's happening, and the solutions are right there. But you need to work. You need to kind of, you know, work together. So we think of ourselves as, you know, um, uh, we want to go after those. Those challenging things. So it's that lion sitting there getting attacked by the hyena.

Speaker B: Cool. All right, um, what's your favorite, uh, part of the culture?

Speaker C: So, Cat, Um, we barbell this. Okay? So we get a very senior person like myself. I'm old, right? And we surround ourselves with really junior young people, uber talented. I mean, way smarter than I was when I was that age. Right? And then we mentor them, and we try to, um, show them, you know, how to present, how to communicate. And we always push them a little bit further than we think they should be. So, for example, they'll. They'll be in there presenting to very senior. You know, Maybe there's an SES in there. Maybe there's GS14, 15 in there, right? And so we want to. We want to give them a little bit of a challenge for themselves to present. If you're very technical, you probably didn't have a lot of time presenting, right? And so, um, and also we have a culture of, um, really encouraging people to build their skill set. So if they don't know anything about the cloud, we'll give them, you Know, some, some videos to watch, and we'll give them time to develop that skill set. And we really want to invest in our, um, engineers. And most of the times, I mean, uh, you know, knock on wood. But all our engineers who've left SOCAT have always left for much higher pay, which is, uh, totally okay with us, right? We're like, hey, there's no way we can match that. Amazon is giving you three times. This is government contracting. Go, let's stay in touch, right? And I think that's part of the fun because, you know, you get in, you train up, some people, they go off. But also, you know, AI is hot. So, um, if they can, they can get in, a couple gets a couple reps on these things, right? I mean, then everybody is poaching them away, which, you know, that makes me happy. I'm like, the part of being the professor, I'm like, all right. And then we all hire some more, you know, young people to train them up. So that's. That's our culture.

Speaker B: Cool. Um, what's the most common advice you give to students?

Speaker C: Oh, that's easy. The most common advice is that you can do this. They're like, I don't think I can do this, Professor. I'm like, you're way smart. You can do this. But you need to encourage them. Right? And a lot of people, they, uh, have a lot of doubt. I think people, human beings have a lot of self doubt. I'm there to, like, preach to them, yes, you can do this. Just give it a shot. And, you know, by and large, you just have to put in the work and they can do it.

Speaker B: Cool. What was, uh, what was your first car?

Speaker C: Oh, um, no, my cars. Now is so embarrassing. It was a Chevy Chevat.

Speaker A: Nice, nice.

Speaker C: Like professors, come on, guys.

Speaker A: Love it.

Speaker B: What's a surprising hobby of yours?

Speaker C: What's a surprising hobby? I think I play way too much chess. Like, you know, by my, you know, on your mobile phone. Against human beings? Of course not. Not against AI that would crush me. But it's fun.

Speaker B: What's a charity or, uh, corporate cause or. Sorry, charity or cause that is near, uh, and dear to you?

Speaker C: Um, because I'm Korean. Korean American. And, um, both my parents were professors. They both passed. But there's this Korean, ah, American storybook collection, which is kind of cool. They just go around and they interview Korean, Korean, you know, Korean Americans who came over here and just hearing their life story, it's. It's a lot of fun. And I'm. I'm surprised that the Korean culture is so mainstream. You know, I have friends who tell me about kimchi, and they speak Korean better than me.

Speaker B: Nice. Uh, what was your favorite toy growing up?

Speaker C: My favorite toy, uh, probably my BB gun until I almost shot my eye out.

Speaker A: Nice. That's a great. It's a great answer.

Speaker B: Great one. Uh, and, uh, last one. What's, uh, something you enjoy doing but are very bad at?

Speaker C: Something I enjoy doing, but I'm very bad at. Um, I'm trying to keep up with my kids. My daughter was so much more athletic than me. It's sad. I used to be able to run, and she's a sophomore in high school, and then she plays, like, you know, field hockey. And now I try to trace her. I can't keep up. It's like, I mean, what happened?

Speaker B: I remember when my youngest started beating me in races and I was like, ah, what happened?

Speaker A: Yeah, you win. Good stuff. Awesome.

Speaker B: All right.

Speaker A: Well done.

Speaker D: All right.

Speaker A: Mike, you up?

Speaker D: Yeah.

Speaker A: What is one leadership trait you think is underrated in federal service?

Speaker D: I don't know if it's underrated, but authenticity, um, I would say, and just the ability to not try to project or not try to be a, uh, leader that you think people, you know, want to hear from, but just be yourself because that ultimately shines through and, you know, people respond.

Speaker A: Yeah. Well said. If you could instantly fix one government tech challenge, what would it be?

Speaker D: Oh, man.

Speaker A: How much time do you have?

Speaker D: Yeah.

Speaker C: Yeah. How much time do you have?

Speaker D: Um, one government tech challenge, uh, instantly fixed, let's say ATOs. So, uh, authority to operate. So the ability for companies to, uh, get approval to operate on government systems and networks. We're making a lot of progress there, and it's improving, but if we could just get that solved right away, that would be awesome.

Speaker A: That's huge. Uh, what's the most impactful tech trend that you're tracking right now? M.

Speaker D: Tech trend, I'd say in the defense space, um, probably around, uh, sensing and kind of alt. Pnt. So when we think about, um, you know, ways, alternative ways that we can navigate without using, you know, GPS and others, um, and coming up with new technology around that, we're seeing a lot of companies that are coming to us with capabilities that are just. I mean, they're mind blowing. It's awesome, and we need it.

Speaker A: That's cool. What's one thing you wish more people understood about working in the Navy?

Speaker D: I'd say, um, probably your ability to impact things. You know, we, we alluded to this earlier, uh, but I feel like people, you know, have, with large organizations in the Navy in particular, you have this perception that you can't really impact things. Um, but, but, you know, if you focus on your sphere of influence and the pockets, um, of people that you're around, you can see positive change and you can, you can impact change. Cool.

Speaker A: What's a charity or corporate philanthropy that's near and dear to you?

Speaker D: Yeah, so I'm on the board of the Hearing Loss association of America. And, you know, it, it does what it sounds like. It provides support and services to people with hearing loss. Um, you know, I'm an artillery Marine. I've got a lot of folks that I work with that have hearing loss. I've got hearing loss. I've got hearing loss in my, um. And so, you know, to be able to provide, uh, and give back a little bit there is great.

Speaker A: Cool. What's your go to road trip snack?

Speaker D: Oh, uh, the Fiery Cheetos.

Speaker A: Solid. Yeah. Yeah. What's, uh, the best, uh, concert you've ever attended?

Speaker D: Ever attended? Um, Billy Joel in the Philippines. Wow. And I was stationed out in, Stationed, uh, out in Okinawa, and me and a couple other lieutenants, uh, went over to Manila and saw Billy Joel concert there. Pretty awesome.

Speaker A: It's a flex. That's a great answer. Uh, what's the, the first job that you ever had?

Speaker D: Uh, construction. So it was, we were a subcontractor, but it was a shelving, uh, company. We would go on to, uh, commercial construction sites and install, you know, industrial shelves. Um, that was awesome. Loved it.

Speaker A: Cool. What's a hobby or pastime that you've picked up in the last five years?

Speaker D: Oh, um, so my wife got real into needle pointing during the pandemic. And, uh, I tried getting into that a little bit. It, um, hasn't fully stuck, but really, I mean, my hobby of the last, you know, couple years has been, uh, babies, so that I don't have to.

Speaker A: But yeah, it's a full, full time hob. Um, last one. What was your, your dream job as a kid?

Speaker D: Oh, um, you know, like, like Jim, you know, had the. Had the BB gun was running around the backyard. Nerf guns, little knives and stuff. So, um, yeah, I mean, I was always wearing camo and stuff like that, so probably marine

Speaker A: living it out. So. Good for you. Awesome. Well, I wanted to thank you both for, for sharing your insights on, uh, you know, this idea of building a stronger and smaller, smarter public sector. Uh, you know, if you've ever considered a role in Federal service or wondered how AI might change how our government operates. You kind of got a front row seat to it here on this episode. So thank you both for your time and your service. And then, uh, thanks for joining us on the podcast.

Speaker C: Thank you very much.

Speaker D: This is awesome. Thank you very much,

Speaker C: Sam.