Speaker 1 (0:15) Hey there, and welcome to the IT guy show. (0:17) My name is Eric, the IT guy Hendrix. (0:18) I'll be your host today. (0:19) This is episode 12. (0:21) I'm really excited. Speaker 1 (0:22) We've we've gotten a ton of feedback. (0:24) A lot of viewers have found their way back to the to the stream, so really excited that you all have tuned in. (0:29) And if you haven't, make sure to hit that subscribe button. (0:32) That way that way you get notified anytime we we go live. (0:35) I'm trying to do some bonus episodes, and I've got a ton of guests lined up through the end of the year. Speaker 1 (0:39) Really excited about it. (0:42) In fact, I'm really glad that I got this recording today because, well, this week, I'm starting teaching a class. (0:49) So that'll be a new experience, and I'm sure I'm I'm sure I'll I'll talk a little bit about that. (0:53) Maybe even interview one of my fellow professors talking about teaching Linux in college today, but that's not what we're talk what we're talking about. (1:01) My guest today is the former CTO of of GovTech and GitLab. Speaker 1 (1:07) He had, a 15 word title, so I'll I'll I'll let my guest introduce himself here in a second. (1:13) But today, we're gonna talk about what it's like working in the public sector versus working in government. (1:18) I know a lot of people talk about what it's like working for government. (1:22) I've done it as a contractor before. (1:24) I have my opinions. Speaker 1 (1:26) But as as someone who's recently been in that space, I want to bring in Joel. (1:32) So bring in my guest today, Joel Kruswick, was actually my manager at GitLab. (1:38) I owe this guy a lot. (1:40) He doesn't sign my paycheck anymore, so, you know, it's okay. (1:43) This is just me being honest. Speaker 1 (1:45) But, Joel, welcome to the IT guy show. Speaker 2 (1:48) Well, thanks for having me, Eric. (1:49) It's good to to be back on with you. Speaker 1 (1:53) Yeah. (1:53) We we were talking during the the preshow that it's probably been at least a year since you and I talked, like, face to face. (2:00) And then it's it's been, my gosh, like, six years since since we worked together back at back at the lab. Speaker 2 (2:05) Wow. (2:06) That long already. (2:07) Wow. Speaker 1 (2:09) So, Joel, why don't you tell us a little bit about yourself, what you do, what you do for fun? (2:14) It's always a crowd favorite. Speaker 2 (2:17) Well, as you stated, I'm the former federal CTO at GitLab, so I kinda live where policy and technology meet. (2:25) That's kinda my thing of of monitoring policy, keeping up with technology, trying to make sure that everything gels together well. (2:33) And when it comes to fun, I live here at a lake. (2:37) We were very intentional about our investments and our our real estate work back before all of the pandemic stuff hit. (2:46) And so we moved here in 2021, and so one of my favorite things is just having a boat in the backyard that we can go get out on, out here in Indiana. Speaker 1 (2:58) That's awesome. (3:00) So one one of the goals that I have when I do these podcasts is does dead gum marketing people yes. (3:08) I I am. (3:09) I work in marketing. (3:10) Love to coin terms and throw terminology around and don't always define it. Speaker 1 (3:16) So one of the things that I wanna start off with is what are we talking about public sector versus government? (3:20) Let's let's define our terms to begin with. Speaker 2 (3:24) Well, I think it's interesting because the first thing I wanna do is throw out TLAs. (3:27) Right? (3:27) The whole three letter acronym thing is what government's all about, isn't it? (3:32) So, you know, when we talk about it, sometimes we see public sector and government as similar. (3:37) And the public sector in general typically encompasses everything from the Department of Defense and the intelligence community and all their their contractor base, their subcontractor base. Speaker 2 (3:49) So you're thinking like the big Lockheed Martin type folks of the world through all the civilian agencies and in all the way down to state, local, college, like university education levels of government. (4:02) Like so so the public sector, when I think of it is that way, the private industry side or the the public, publicly known company side of things, of course, then takes us into all of our enterprise side, you know, corporations and all the the stuff that you find on the stock market all the way down to small companies. (4:23) And so it's interesting because there's a lot of talk about public private partnerships and things. (4:27) And a lot of times when you see it broken out, the word government is just kinda thrown around loosely. (4:33) It's missing the label. Speaker 2 (4:35) Right? (4:35) It's the federal government or the local government or the state government. (4:40) And so public sector is that encompassing term. (4:42) And if I hear government, I really think federal agencies more than anything, and that includes Department of Defense. (4:50) That Speaker 1 (4:51) that helps a lot. (4:53) Most of my career was spent more on the commercial side, so working in private sector, dealing with b to b relationships or maybe once is is b to c. (5:03) Sorry. (5:04) Now now I'm using terms that I'm not defining. (5:06) So that's business to business versus business to consumer, b to b versus b to c. Speaker 1 (5:11) And then like you said, you kinda have the this relationship between government and and public sector. (5:16) So when I I think most people are comfortable and familiar with the the paradigm of I'm I own a business. (5:26) I make a product. (5:27) You you, the customer, pay me for that product. (5:29) How does that shift? Speaker 1 (5:30) What what are what are some of the goal differences between a for profit company like that and someone in the public sector? Speaker 2 (5:39) You know, it's interesting because the similarities in workflows and the similarities in the needs are the same, but the incentive for them is often different. (5:49) So when we look at private industry, a lot of times, it's about the productivity. (5:52) How much can we get done? (5:53) How fast can we get to market? (5:55) The innovation pace. Speaker 2 (5:56) Right? (5:56) Those are expensive things that we wanna tackle. (6:00) Make sure we're out in front of our competition. (6:02) It's very competitive space. (6:05) Once you enter the public sector, that shifts. Speaker 2 (6:08) And so you don't have a competition necessarily that you're up against. (6:13) It now becomes, can we make sure that the experience here is okay for our civilian base? (6:21) Is it something that we can scale? (6:23) And that has become far more a concern, over the last five years or so. (6:28) But I think it's it's different from the perspective of making sure that certain things get to market, not necessarily that we're to market first, not necessarily the best product to market. Speaker 2 (6:40) And so that changes things. (6:41) Right? (6:42) It changes how you work, and it changes the pace of work, and it changes the reasons behind things. (6:48) And so what we were starting to see is as some of the new government regulations come out and they go, hey. (6:53) By the way, in the next six months, this will come to market. Speaker 2 (6:56) It's coming to market, but is it an optimal solution? (7:01) Probably not. (7:02) Probably not. Speaker 1 (7:04) I I I was laughing periodically through your explanation because I I worked as a government contractor at one point. (7:11) I was my the company I worked for was attached via contract to gosh. (7:19) Now I can't even remember. (7:22) Had to do with government owned property, so government real estate. (7:26) And so I'd I worked as a systems administrator. Speaker 1 (7:29) That was probably the second or third job I had since making the shift strictly to Linux. (7:35) And so I had a batch of servers on this side of a firewall that were more public facing, so the the government entity's website, and it'll come to me as soon as we stop recording, which which organization I work for. (7:48) But then on the other side, I had servers that I was responsible for that were more for the department of the gosh, I'm completely blanking on the term. (8:01) But they they handled the financial aspect of government real estate. (8:06) So, you know, you you build a courthouse or something and and and this was this entity was responsible for for owning, managing, upkeeping, and and ultimately paying for that. Speaker 1 (8:17) So I had I had systems on two sides of two different firewalls, and both of them used completely different sets of tools. (8:24) Mhmm. (8:25) So for instance, one side was Red Hat satellite. (8:28) This was back during the satellite five days when it wasn't as great as it is now. (8:34) And so it was brutal, and we had patch managements and and that kind of thing. Speaker 1 (8:38) And the other side was more Wild West. (8:40) Just and and so the interesting thing with with that history was that they had different contracting agencies that managed different types. (8:49) So as as happens, and maybe you can speak to this a little bit, government contractors have to basically reapply, rebid every few years to keep their contract. (9:00) So, eventually, the company I worked for ended up winning out on both contracts. (9:04) And so a lot of my responsibility for that, for those several years were were kinda trying to we we couldn't we couldn't bridge them together, but at least make both sides of that firewall look the same. Speaker 2 (9:17) Yeah. (9:18) It once you get into that space, things get really interesting, don't they? (9:22) And and I'm really happy that the this work that you did made such an incredible impression on you that you can't remember who else put it. (9:31) Let me put that out there. (9:32) But, yeah. Speaker 2 (9:33) It's fascinating. (9:34) Right? (9:34) Because you work with all these different agencies, and they go, well, here's how we do it, or or here's the way that we'd like to do it. (9:41) And it doesn't matter how related to other things it is. (9:44) It's just here's how we'd like to do it, and this is our way of doing it. Speaker 2 (9:49) So I love seeing some of the things that are happening right now. (9:51) Right? (9:52) Things like the DOD is doing a swift initiative right now. (9:55) And so that should be something that standardizes how they buy software for a while. (10:02) Right? Speaker 2 (10:02) That would be great because then we don't have to answer all these different inquiries around, well, what's your spot chain look like? (10:08) Do you have an SBOM? (10:10) And, know, there's all these different questions that are coming up. (10:13) Well, the implementation of that, the standardization of things is something that's been lacking for a long time. (10:21) And because of that, I can go to some websites that require me to use, like, login.gov. Speaker 2 (10:26) I still have to authenticate with my old login and some weird bin. (10:32) So, like, it it wasn't like you replaced it and standardized it. (10:36) You just added a layer. (10:37) Right? (10:38) And so things like that are too commonplace. Speaker 2 (10:40) I love the idea that there's some standardization happening within the GSA, the services administration. Speaker 1 (10:46) They're Which was who I work for, by way. (10:49) Yeah. (10:49) I was gonna I was gonna poke that in there somewhere. (10:52) Yes. (10:52) It was it was the GSA that I was attached to. Speaker 1 (10:55) Right. (10:55) So Speaker 2 (10:56) Yeah. (10:56) Yeah. (10:57) And they're I mean, they're one of the ones that that really is helping try to standardize some things and say, here's a platform. (11:02) Everybody get on this, and we'll we'll do things together. (11:05) That's great. Speaker 2 (11:07) But the number of different solutions that are out there today, not only per agency, but also, like, what are you using that self hosted? (11:15) What did you do that was your own GovTech versus something that was off the shelf someplace? (11:19) It just has led us to this place where maintainability is a real problem. (11:25) So we don't think about productivity. (11:26) We just think about how do we keep this stuff online. Speaker 2 (11:29) Hopefully, AI, hopefully, is gonna help us standardize a few more of those things over time. Speaker 1 (11:34) Oh, you went there. Speaker 2 (11:36) I have to. (11:37) I mean, I don't know how many minutes we're in, but I didn't say the words AI yet, and it just has to be said. Speaker 1 (11:42) Well, we're we're about ten minutes into to your ears and my conversation. (11:46) So that's that's that's a good pace. (11:49) It it was an interesting dichotomy working for the GSA. (11:53) And I I I don't know if the GSA called us their chief financial officer or if that's more of a private sector term, but but I I I kinda worked both sides. (12:03) It was an interesting dichotomy because on the one side, they self they they manually built, Apache web server packages. Speaker 1 (12:13) They didn't use the the precompiled RPM. (12:17) They built their own. Speaker 2 (12:18) Yeah. Speaker 1 (12:18) But then on on the flip side, they were also the ones who introduced me to and I helped with a proof of concept for using, keep in mind, this is, a decade ago, so this was all new, their first DevOps pipeline. (12:34) So Jenkins, Jira, GitLab, it was either I I think they were evaluating GitLab and Bitbucket at the time. (12:42) Or, actually, this may have been pre GitLab. (12:44) So it may have just been Bitbucket. (12:46) But I helped them build their first DevOps pipeline there. Speaker 1 (12:50) So thank you to the GSA for helping helping my career forward. (12:55) Because with that experience, I eventually started working for GitLab and yeah. (12:58) Anyway but so so getting back on track, we we've I I threw out the term DevOps. (13:04) You threw out AI. (13:05) So let let's let's go down that that, that path. Speaker 1 (13:09) Starting with with sort of pipelines and and the the continuous release methodology, what is it like using something like DevSecOps, which is developers security operations type development workflows in those regulated environments? Speaker 2 (13:29) Honestly, it's not a whole lot different than what it would be anywhere else. (13:34) Right? (13:34) We still have the same goals. (13:35) We have to still test the code. (13:37) We still have to secure the code. Speaker 2 (13:39) It can't go out with with any less security than anything else. (13:45) And so speed to mission is still important, especially now. (13:49) We've seen, you know, a downsizing of the government. (13:52) So doing more with less is a term I keep hearing. (13:55) I don't love it, but it is, you know, in its, intent is the right concept. Speaker 2 (14:02) Right? (14:02) And more with less means more automation, means more DevSecOps. (14:05) It means more pulling AI into workflows. (14:09) And so as we look at what they're doing here, we see a lot of similarities between the private sector and the public sector. (14:17) And so the government space in particular, as the emerging threats continue to grow, right, the the threats of malware and ransomware and and all these malicious attacks that are out there, you have to keep up. Speaker 2 (14:30) There's no exception to that based on your label. (14:33) And so from a usage perspective, it looks pretty consistent across the board right now, and I'm pretty happy to be able to say that because for a while, there was a significant lag we were seeing as it relates to pipeline adoption and some of those capabilities. (14:48) A lot of that's caught up, and it it's, brought me a lot of joy to see that over the last couple of years. Speaker 1 (14:54) So you you, you used this distinction, during your introduction, but you kinda sat at at kind of a t junction between technology and government from a vendor. (15:03) So I I wanna specifically ask, so internally, you're saying it looks very much like a like a standard business nowadays. (15:12) But what about vendor relations? (15:14) Like, you work between GitLab and and the government. (15:16) What what do those relationships look like compared to, say, just regular for profit company and and a software vendor? Speaker 2 (15:23) Well, it's a longer term process, I guess, a lot of times to to get from the point of interest to a point of procurement. (15:33) That said, I think even that is streamlining a lot right now. (15:37) So if you look at a lot of the policy, what's happening in DC, what you're seeing is a real focus on making sure that technology can be procured more quickly. (15:47) And I think a lot of that's being driven by the concept of, malicious attacks coming in from AI. (15:55) You almost have to go, like, the singularity route here of having an AI to battle an AI. Speaker 2 (15:59) So you have to have your good AI that can help re reflect the bad AI out of your system. (16:05) And, like, I feel like that's one of the core drivers that's saying, look. (16:08) We can't wait anymore. (16:09) We we can't have these legacy environments that, well, I'm gonna procure this at some point. (16:14) It has to be now. Speaker 2 (16:16) And so there's a lot of current initiatives. (16:19) The DOD is working on one called the SWIFT initiative. (16:22) That's great. (16:22) There's a a number of other things. (16:24) The GSA has got a program for for trying to accelerate this. Speaker 2 (16:27) Right? (16:28) We're we're seeing it across the board. (16:30) I need to be able to get my technology quickly when I need the technology. (16:34) And so I think we're in a period of change where this is rapidly becoming a far easier cycle for the government to get what it needs. (16:44) Mhmm. Speaker 2 (16:44) And, I'm excited to see that happening. (16:46) It's been a long time in coming. Speaker 1 (16:50) So we we've we've hinted at it. (16:52) What what do you think AI's role is going to be in this moving forward? Speaker 2 (16:57) That is a really tough call. (17:00) AI unto itself is such an interesting thing. (17:03) Right? (17:04) Because it's affecting everything. Speaker 1 (17:06) Mhmm. Speaker 2 (17:06) And there's all this faith being put in it. (17:09) So what do we do with it? (17:10) What do we do with AI? (17:11) Where do we apply it? (17:13) Where is it augmenting people? Speaker 2 (17:15) Where are we are they trying to replace people with it? (17:18) Like, what what is this thing? (17:20) In the world of software development, here's where things get interesting because what it's doing right now is it's creating new workflows. (17:26) So the whole idea that today, it is this it's just a a push button exercise. (17:33) You want an you want AI, you talk to it. Speaker 2 (17:36) You push the button, it gives you a response. (17:37) It's reactive. (17:39) Mhmm. (17:39) The whole agentic revolution is in play right now. (17:42) You're seeing it roll out everywhere. Speaker 2 (17:44) These agents are far higher capability. (17:46) When you group them together, think of it as multiple subject matter experts that come together and solve a problem really well. (17:53) That's the direction we're going. (17:55) So you're gonna see streamlined workflows. (17:57) You're gonna see that a lot more time spent in the IDE if you're a developer, and then a briefer middle section where the code is being developed and a lot more emphasis on the back end. Speaker 2 (18:09) And so what that might look like is is instead of today of of being a problem statement, say say you're gonna work on something, you create an issue in a system someplace or a task of some kind, That now is gonna become an AI prompt. (18:20) It's gonna become Mhmm. (18:21) A system, a solution architecture kind of approach to things with a historical reusable prompt. (18:29) AI will go off and do the work. (18:31) All the agents will. Speaker 2 (18:32) Right? (18:32) And then it comes back and says, well, I did this work. (18:34) What do you think? (18:35) And by the way, it wants to test the work for you, and it's gonna have a seat at the code review table with you. (18:40) Right? Speaker 2 (18:40) Like, all these different pieces you go, oh, woah, woah. (18:42) Hold on. (18:43) Let me be part of this. (18:45) So you keep yourself involved, but you can see the workflow has changed. (18:48) And what's really important here, and this is the thing that can't be overstated, is historically, when you commit code, you write code, you commit code, it has your name on it. Speaker 1 (18:58) Mhmm. Speaker 2 (18:58) Well, now you're the author of the prompt and of the problem. (19:02) You're the solution architect over here. (19:05) The coder will actually register as one of the AI engines. (19:10) Right? (19:11) So this is a dramatic shift where now well, who wrote the code? Speaker 2 (19:14) Oh, well, Claude did or or Duo did or Copilot did or, you know, whatever that looks like. (19:20) Right? (19:20) Cursor kicked out this code for me. (19:23) Okay. (19:26) What is our role? Speaker 2 (19:26) What does it look like we're doing? (19:28) Right? (19:28) And so it it's shifting substantially what the role of developers looks like, what the role of architects looks like, what the role of of AI prompt engineers looks like. (19:40) Like, that is now becoming kind of a compressed space. (19:43) And, I have some predictions that it's gonna change what teams look like going forward. Speaker 2 (19:49) It's gonna change not only workflows, but what whole teams look like in the years ahead. Speaker 1 (19:55) Mhmm. (19:56) Yeah. (19:56) And I've I've never I mean, I'm coming up on twenty years in IT professionally. (20:03) Goes far beyond that if you go all the way back to the days when I figured out how to change my dad's Mac two's, like, desktop wallpaper. (20:11) But, professionally, I'm coming up on twenty years, and I've never seen a technology sweep the industry like AI has. Speaker 1 (20:19) I and I've lived through the consumer hardware to virtualization move. (20:26) I saw the move from from from, you know, monolith to to more of a containerized workflow. (20:33) I'm I've seen the move to cloud, and now we're seeing a move away from cloud or at least Repeat creation. Speaker 2 (20:41) Right? (20:41) Yeah. Speaker 1 (20:41) Right. (20:42) And then, then then there was that year where every technology had to be green. (20:46) That that was fun. (20:48) It's like, not sure how Dell PowerEdge could be considered green, but, you know, we went through a year where that was the thing. (20:54) Few years after that, it was, like, blockchain and and, you know, then DevOps, then DevSecOps, then DevXOps, and just, like, all these other things. Speaker 1 (21:02) But in all of that time, I have never seen a technology or or a mentality just sweep the entire industry. (21:11) It's changed everything. (21:12) I I don't think I've used ChatGPT for more than a year, and it's already changed how I do all of my workflows. (21:19) Now content on this show, I I am real. (21:22) I you know, I'm I'm me. Speaker 1 (21:23) This is an an AI rendering of me. (21:27) It is supplemented by AI. (21:30) I will I I'm still very much like, this is this is my passion project, so it's going to be me. (21:36) I come up with the topics. (21:38) I'd I talk to people who might be great guests, and then, you know, we we kinda figure out what we're talking about. Speaker 1 (21:44) And then I will throw it to ChatGPT and say, okay. (21:47) What what am I missing? (21:48) Am I forgetting anything? (21:49) Or when I write a blog post, you know, it's ChatGPT makes a great editor. (21:55) But that's that's the the conversational piece of AI. Speaker 1 (21:58) That's kind of the I'm in the driver's seat. (22:01) You're just here to help me or to catch a blind spot or something. (22:05) But, I mean, in just the last few years, we've seen the shift to agentic AI. (22:10) We've we've seen was it m m m d MDC? (22:14) Is that the the it's basically like a marketplace for AI that isn't just a chatbot that actually goes out and does things. Speaker 1 (22:24) And now there's companies that I mean, I'm a former sysadmin. (22:27) There's companies out there that are building these tools that'll go out and manage your infrastructure for you. (22:34) And it's like, do we I don't know. (22:37) This thing can't spell strawberry, but we're going to give it root access to a thousand cloud based servers, and we're going to trust that it's not going to spin up 10,000 more, and all of a sudden we get a $100,000 cloud bill. Speaker 2 (22:50) Yeah. (22:50) We we have plenty of questions yet. (22:53) We're we're not there yet. (22:54) It's making huge differences, but we're not there yet. (22:57) And so I think what you're gonna see I mean, you know, we kinda peaked the hype cycle, right, over the last two and a half. Speaker 1 (23:02) I'm so glad we're coming down on Speaker 2 (23:04) that. (23:04) Yeah. (23:07) We'll see where it goes. (23:08) We got we have a ways to go yet before this thing can be fully trusted. (23:11) There's there's a lot of complex problems. Speaker 2 (23:13) The thing about it that's interesting is when you think about, you know, whether you're talking agents or MCP, model context protocol servers Speaker 1 (23:22) There it is. (23:22) MCP. Speaker 2 (23:22) Yep. (23:23) If you're talking about those kind of things, you can be very intelligent on a specific thing, like, on a specific way of working. (23:30) And so that is a new twist on what AI is, and and and I kinda like it from the perspective of trustworthiness. (23:37) So if I've got specific agents that do specific functions and they know those functions really, really well, they can repeat those at scale. (23:44) And having that agent go out and deploy the architecture in a specific environment may become a far more reliable thing. Speaker 2 (23:52) Right? (23:52) So this is kinda where the corner is being turned. (23:54) Are we there yet? (23:55) No. (23:56) But there's a lot of companies that are out there trying to solve that specific problem. Speaker 2 (24:00) I just looked at one yesterday. (24:01) It was kinda interesting. (24:03) So they're using AI to do cloud deployments, to do things at scale. (24:08) And I think in the near term, we'll see at least from the developer side that that gets relieved from their plate as one of the things that they need to deal with too much. (24:19) Right? Speaker 2 (24:19) AI should help with that. (24:20) I still see it as a core problem for the architecture of the systems, though. (24:24) AI is not good at that yet. (24:26) So Right. (24:26) We still need people who are architecting these systems well that are auditing all this work that are saying, yeah. Speaker 2 (24:32) That's great. (24:32) I I love what you're doing here, but that doesn't scale to the realm that we need it to. (24:37) What are you thinking? (24:38) Right? (24:38) So, yeah, there's a lot of work to still be done for sure. Speaker 1 (24:42) Well and and one of my growing concerns is we're trying to automate away a lot of the work of some of the junior developers, junior sys admins. (24:53) I mean, one of the reasons why I fell in love with technologies like pipelines or like Ansible playbooks was because I'd done all that by hand for years. (25:03) Yeah. (25:04) Manage hundreds of servers where you had to use TMUX and SSH tunnels to go and manually manage a 100 servers in production. (25:12) And so you'd use TMux, and you'd you'd have all these different panes open on all these different servers. Speaker 1 (25:17) And you go and you make the change to the SSH config file, and then across the board restart that service. (25:23) And I I did all that. (25:25) I did it manually. (25:26) So I'm glad that I did that. (25:27) I'm glad that I have those scars and that experience because now I can say, you know, I could do that, or I could write this six lines of YAML and automate the whole thing. Speaker 1 (25:39) I mean, you take your pick. (25:40) I know which one I'd choose, but I've I've done both sides. (25:43) But now we're talking about taking that away and throwing it into a black box and then giving it root access. (25:49) It's like, I don't know yet. Speaker 2 (25:52) There's a concern I have there about the layer of abstraction. (25:55) Right? (25:55) So you you and I, we've been there. (25:57) We've done that. (25:57) Right? Speaker 2 (25:58) I've had plenty of terminal time over the years. (26:01) I've rebuilt Linux kernels, you know, to integrate drivers and whatever else way way back in the day. (26:06) Right? (26:07) So the general understanding is up there, understanding how this should work. (26:11) Once we start abstracting that away, think about the next generation coming into the workforce now that Speaker 1 (26:16) Mhmm. Speaker 2 (26:16) That may not have that. (26:17) They'll just rely on AI for it going forward. (26:19) Maybe that's fine. (26:21) Maybe AI is good enough at it that that's something that we don't have to think about anymore. (26:25) But maybe there's also a place for that to be learned yet because it'll still be learning from us and the things we've done in the past. Speaker 2 (26:35) And let's be honest, you know, if it's learning from any of my old code, it's probably learned how to be unproductive and or and have something that's wildly inefficient. (26:44) So, you know, what does it really know? (26:47) And this is where some of those specific functions that companies are working for could be really good for us. (26:55) We have to get to the point where that layer of abstraction is not important. (26:58) Today, to your point, highly important. Speaker 2 (27:01) Mhmm. Speaker 1 (27:04) I mean, it's it's almost like we've iterated on the conversation between Linux system versus Kubernetes cluster because Kubernetes abstracts a lot of that away. (27:14) And I know sysadmins to this day, you know, what, Kubernetes is what? (27:17) 15 plus years old now? (27:19) And there's still sysadmins that are like, I I don't know what it's doing. (27:22) I don't know how it's determining what schedules to to keep. Speaker 1 (27:26) I'm not sure when it decides that it needs to scale horizontally, and and they just they sworn it all off. (27:33) And yet here we are now taking a computer system to do that. (27:36) But on the flip side, if I have this AI system that goes out and can deal with 99% of the calls that would come in at 2AM or on my weekend and I don't have to be responsible for that anymore, It's it's an interesting it's it's an interesting split brain problem of do I trust it? (27:58) But I really, really, really wanna trust it. Speaker 2 (28:01) Yeah. (28:01) Yeah. (28:02) If it can save us time, if it can save us energy, if it can save us money, I you know, there the other side of this when if this all hits the promises that have been brought before us, it changes what we do and how we do it, and it changes it substantially. (28:17) And there should be increasingly worthwhile life benefits from it. (28:23) And I think that's the you know, you talked a little bit about the the human side of all this. Speaker 2 (28:27) I think that's where the rubber really meets the road because, okay, what are we doing? (28:31) What is our role in this new space? (28:34) You know, what happens when we hit AGI maybe a year and a half out or something? (28:38) I I don't know when that comes exactly, but that's my projection, sometime twenty twenty seven ish. (28:44) Okay. Speaker 2 (28:44) What does that do to this? (28:46) How much more do we trust it or not trust it then? (28:48) Can it solve these problems real time so that we don't have to think about those? (28:53) We can think about other things, and we can advance technology in new ways. (28:58) You know, the there's a whole door that's opening here, but at the same time, it's gonna take a toll on us as as just people. Speaker 2 (29:05) Right? (29:05) The the World Economic Forum came out the other day and said by 2030, something like 40% of all jobs are gonna need a retool for skill sets. Speaker 1 (29:14) Again? Speaker 2 (29:17) Like, I was I went through the Internet revolution. (29:20) I went through the mobile revolution. (29:21) I went through the cloud revolution. (29:22) Now I'm here. (29:22) Like, you know, okay. Speaker 2 (29:24) That that may be fine because that new workflow may be beneficial for me. (29:29) But I keep hearing over and over, well, we're gonna be more creative. (29:32) We're gonna be more innovative. (29:34) We're gonna be more fill in the blank. (29:36) Right? Speaker 2 (29:36) Which is gonna make us able to tackle more difficult things. Speaker 1 (29:41) But as as a as someone who works in marketing, my position is one of those being targeted to be replaced by these AI things, and I think that really takes something away. (29:51) Yeah. (29:51) Because one of the reasons why I work in product marketing is because I have a particular voice, a particular style, a particular set of lived experiences. (30:00) That's why I'm in podcasting and not in systems administration anymore. (30:04) And there's a lot of value to that voice, to that experience as as jaded and scarred as it might be. Speaker 1 (30:13) But, I mean, I I don't I don't fear the retooling like public media has been. (30:20) Because, I mean, if you think about it two hundred and twenty five years ago, how much of the population was geared towards food production? (30:28) Farmers, tractors, horse trainers, that kind of thing. (30:32) And yet we survived all that, and we've iterated on that from man pulls plow to horse pulls plow to now tractor. (30:40) And then now we've got these giant combines that do it, and some of them are like self driving combines nowadays. Speaker 1 (30:46) I mean, it's we've we've gone through that, and there's not you know, to use your number, 40% of the population isn't unemployed because we don't need that many farmers anymore. (30:57) So I know humanity will will be resilient. (31:01) I know we'll find new things to do. (31:03) Maybe maybe AI is the answer to some of these four day work weeks or or at least, you know, reduced work hours. (31:11) You know, you you may still work a full time job, but maybe a full time job's twenty five hours ten years from now. Speaker 1 (31:17) So that part doesn't worry me so much as how painful is it going to be. (31:23) And is the economy are people's budgets? (31:25) Are people's incomes going to be able to to be able to kind of bridge that that transition? Speaker 2 (31:34) So, yeah, near term, we're going to have some pain. (31:37) I don't see any way around it. (31:39) Right? (31:39) There there is just gonna have to be some pain in there. (31:44) There's a guy, and I am trying to remember his name, but there's a guy on YouTube who talks about the post AI economy. Speaker 2 (31:54) Like, he he talks about, like, on the other edge of this side, or other side of this this AI hill, what's there? (32:01) What does it look like? (32:02) And and Mhmm. (32:03) It's basically a post income driven economy kinda thing, and it's fascinating to hear him talk about his theories and and, hey. (32:12) Do we need, you know, universal basic income at some point? Speaker 2 (32:16) Can we get to the three day work week? (32:17) What what's the goal? (32:19) Now, I mean, look. (32:20) We've had the promise of this for a long time, and it's been possible for a long time. (32:24) And all we do is we push productivity up a little bit more and try to ring more out and go faster. Speaker 2 (32:29) So I don't know if we as people can get there from here, right, just because of who we are. (32:35) But the promise is there if we continue down this road, and I'm excited to see it. (32:42) So I've been kinda watching some of those videos going, wow, man. (32:45) If I could if I could get in, you know, into some of these flows and we can trust AI enough, maybe we get someplace from here. (32:54) Right? Speaker 1 (32:56) Well, I I'm I'm hoping for that, but science fiction does does not agree. (33:04) We'll we'll have to see how that plays out. (33:06) But I I do Speaker 2 (33:06) dystopian on me, man? (33:08) What Speaker 1 (33:09) I I don't know. (33:10) As you were kind of explaining things, you know, Skynets and Terminators were kind of playing around at the back of my mind. (33:16) But Speaker 2 (33:16) Oh, no. (33:17) But but, Speaker 1 (33:20) I mean, I I think it's going to happen a lot quicker than anyone ever projected. (33:24) Yeah. (33:25) Things are moving so fast, and it's it's too late. (33:27) Pandora's box has already been opened. (33:30) We're this is the new world that we live in, and it'll be interesting to look a year from now, two years from now, and see just how much things have changed. Speaker 2 (33:39) Yeah. (33:40) And we're forks down this road. (33:41) Like, let's be honest. (33:42) Right? (33:42) We we were talking about the government side of things. Speaker 2 (33:44) You know, what happened if you look at Google's data, you look back five or six years, right, back about the time that we were together at GitLab, the threat of an emergent bug in one of the systems, right, something that needs to be patched, You have, like, sixty days before somebody tried to exploit it. (34:03) Right? (34:04) And a couple years later, it dropped to thirty days. (34:06) And did you see where we're at now? (34:08) We're we're at, like, four days before typical exploitation. Speaker 2 (34:13) That's on a zero day vulnerability, on an end day vulnerability. (34:16) Some as soon as the patch is published, there will be attacks on one on every six servers within, like, four hours. (34:24) That's crazy. (34:25) That is AI driven because the it spins up the bots and out they go, and and it can do so very, very quickly. (34:31) Now we're being forced to do something because we all have to respond to what the malicious side looks like. Speaker 2 (34:38) So Yep. (34:38) I think it's gonna be fascinating to see where we land in all this and and see if there is a tug, one direction or another as the malicious use ramps up. (34:49) Will it drive new things on the other side? (34:52) And then what's the economic impact of all of it? (34:54) Huge, huge question. Speaker 1 (34:56) Well, I mean, my day job, I'm working on tooling that helps automate patching of vulnerabilities Oh, really? (35:03) Which cracks me up because I was the guy who begged companies that I worked for as a sysadmin that we have to patch these systems every quarter. (35:12) Like, it it's government regulation now. (35:16) You can't ignore that. (35:17) Oh, can't we just do this once a year? Speaker 1 (35:19) And now it's like, if if you patch every quarter, you're screwed. (35:23) You might as well just close your doors now and avoid all the pain because it like you said, four days before most attacks begin. (35:32) And, you know, you you listen to these these security podcasters, and they talk about how out on on certain forums that people are selling vulnerabilities for more than I've made in my entire career for one vulnerability. (35:46) And and they're they're selling it. (35:49) They're selling this information not to exploit themselves, but to sell to to a malicious user. Speaker 1 (35:53) Yeah. (35:53) And, I mean, it's just it's it's kinda terrifying. (35:57) It it's it's hard not to become paranoid. Speaker 2 (36:01) Aware. (36:02) Let's use the word aware. (36:04) We're highly aware of what's going on around us. Speaker 1 (36:09) So we we kinda took a deep tangent down down the AI path. (36:13) But is is that kind of the the most top of mind issue facing public sector entities nowadays? Speaker 2 (36:20) I think there's two. (36:21) I I maybe three. (36:23) AI is definitely number one, doing more with less, being able to respond in kind and in time. (36:28) You know, those kind of things are really important. (36:31) Second thing is just supply chain security, the whole idea of cybersecurity and positioning and making sure that we're all doing the same things. Speaker 2 (36:37) We're doing it well. (36:39) We're able to, secure code that we're putting out so we don't hole have holes in it. (36:44) I mean, let's face it. (36:45) The number of attacks and hacks lately, the amount of data floating around, the number of passwords, the public sector, the government, they cannot afford for that data to be out there. (36:55) They've got the stuff that really matters. Speaker 2 (36:58) They cannot be the next Experian or, you know, whoever leaks all really important data out. (37:04) So I think that's another one that's really, really important is that supply chain security piece. (37:09) And then the third one's something we already mentioned, and that's just the procurement side. (37:13) Right? (37:13) Can we buy a commercial off the shelf solution? Speaker 2 (37:16) How fast can we get it in place so that we can be building things that matter, not keeping the lights on with a Cobalt app that was written in the sixties? Speaker 1 (37:25) Right. (37:26) That mainframe's still running. (37:29) So we we didn't talk about this beforehand. (37:30) So if the answer is no, then then don't don't hesitate. (37:33) But has has quantum commute computing come up in any of your conversations? Speaker 2 (37:39) It it does come up. (37:40) I think the promise of quantum is there. (37:43) The scalability of it's been a problem until recently. (37:46) I'm just now starting to see some breakthroughs that may speed it up. (37:50) Most things with quantum have been planning 2028 to 30 before we really see an emergence. Speaker 2 (37:56) I feel like that's been pulled up to the shorter end of that time frame now, with some of the breakthroughs we have. (38:02) But, you know, look. (38:04) A lot of that stuff's gotta run at such cold temperatures and whatever else that it's just hard to sustain. (38:09) And one tweak, minor variation on that temperature, and all of a sudden, your ones and zeros, which are not really ones and zeros, to start to actually become malformed. (38:20) So there's such a sensitivity there that we have this optimism around I put quantum computing and humanoid robots in the same thing. Speaker 2 (38:29) Like, we have this optimism around both, but we've had optimism around both. (38:34) I need to see that scalable, repeatable, you know, situation where things are really trustworthy, and and then we'll go that direction. (38:43) But there's a lot of evaluation right now because that's a that's another coming game changer. (38:49) Right? (38:49) Once AI can move at the speed of quantum, all bets are off. Speaker 2 (38:53) What does that look like from a scaled attack perspective? Speaker 1 (38:57) Well, I've I've kind of thrown all three of those, and a bucket isn't the right imagery. (39:01) But all three of those, I've kind of put almost soft link to one another. (39:06) I I think improvements in AI will help improve quantum, which will help improve robotics, which we'll then circle back to. (39:13) Now we've got smarter AIs running smarter robots. (39:16) And, I mean, if you can throw quantum into it, it it's a supercharger on all of this. Speaker 1 (39:22) And it's just it it is a fascinating time to be in technology. (39:25) That's for sure. Speaker 2 (39:26) Yeah. (39:26) It is. (39:27) Yeah. (39:27) It's moving really fast. (39:28) And and between now and 2030, I have my eyes wide open for what comes next. Speaker 1 (39:34) But if some company called Skynet shows up, I'm I'm out. (39:37) I'm done. (39:38) I'm Speaker 2 (39:38) I'm out. Speaker 1 (39:38) Buying a buying a missile silo somewhere and turning it into a home. (39:44) So speaking of, big changes, I'm I'm given to understand that you've recently went through, just a few weeks ago, a huge change. (39:54) You wanna talk about that? Speaker 2 (39:55) Well, yeah. (39:56) I mean, right at the eight year mark, I I stepped away from GitLab, and that that was a pretty tough thing to do because I'm kinda at the top of my game, really, really enjoying the ride. (40:08) Still love the company dramatically, but decided that it was time to step away for a little r and r. (40:14) I I have to recharge. (40:15) I mean, an eight year run going from 150 people to 2,500 people and from a small VC funded company to a public one, a lot changes. Speaker 2 (40:24) Right? (40:24) And so it it was a challenging run. (40:28) And so this is the season of recharge from here forward for a while. (40:33) Get get some some months of, of rest and and restoration of health and that kind of thing, some pet projects. (40:39) Believe me, there's plenty to do around here. Speaker 2 (40:43) But once those once those projects are done, then, we'll take another look at what's going on in the industry and and where I might be interested in, applying myself. (40:52) In the meantime, there's a good chance that, you know, my wife and I, we've done real estate projects for years here around the lake, and we just, we're in motion to to buy another one. (41:03) And so I'm hoping that there's gonna be some sort of a YouTube channel where y'all can follow along as we do some restoration stuff. (41:09) So that'll be fun. (41:10) That'll be new for me. Speaker 1 (41:12) Love it. (41:13) Yeah. (41:13) I I I remember you working on on various houses when we're working together. (41:18) You'd you'd show up for one on one meetings and be in a completely different space from time to time. (41:23) It's like, that's not your house. Speaker 2 (41:25) Yeah. (41:26) But Speaker 1 (41:28) so I I bring that up particularly thinking about my audience. (41:33) A lot of lot of people that I talk to, some of them in college, some of them are just starting their career path. (41:39) And I know you and I both had hard learned lessons, things that have taken a literal physical toll on what we do. (41:47) Yes. (41:48) So what advice would you give to someone who's getting started in the industry, someone who is is attracted to that? Speaker 1 (41:56) How much just how much more of myself can I ring out? (42:00) What what would you tell someone in that situation? Speaker 2 (42:03) Okay. (42:03) I've got a couple key thoughts here. (42:05) And and part of this is driven by the fact that my son is getting his information systems degree, and he'll be done. (42:10) This is this will be his finest final semester coming up. (42:13) No sooner did we get to this point that I just saw a report from CNBC a little bit ago that said that, you know, one of the the higher unemployment rates for, new graduates is anything that has computer in the title or information in the title. Speaker 2 (42:31) Right? (42:31) Computer engineering, computer science, information systems. (42:35) Those kind of things are seeing a dramatic uptick. (42:38) So we've been told forever that STEM, you know, the whole science and technology, engineering, math world is something that we can count on. (42:47) That's where the money is. Speaker 2 (42:49) Well, turns out the money is there, but the jobs, we're at you know, one out of every 10 or 12 people is currently unemployed coming out of school with these degrees, which means you're smart. (42:59) You could think. (43:01) The paper says you could think, but there may or may not be a spot. (43:06) Now this feels like a tech recession. (43:09) Typically, that changes. Speaker 2 (43:11) Right? (43:11) And I I expect that that could change again. (43:13) But will AI be something that shifts us? (43:17) The top performing majors right now are humanity based. (43:21) They're all nursing and and humanities focused. Speaker 2 (43:25) They just don't necessarily all pay as well as the tech space. (43:29) So my encouragement is if you are going out into the tech space right now, learn what you need to learn, stay on top of AI no matter what's going on around you because colleges are behind on AI. (43:43) For the most part, they're not gonna tell you that. (43:45) They're not gonna tell you about, you know, how things are working, what does a workflow look like today. (43:50) They're gonna give you what it was five years ago, ten years ago. Speaker 2 (43:54) That hasn't changed since I was in school, by the way. Speaker 1 (43:57) Oh, trust me. (43:57) I'm I'm doing course prep on on on screen, and I think some of my examples are built on, like, Ubuntu 18 o four. (44:06) Yeah. (44:07) And it's like, can I use something a little bit more recent? Speaker 2 (44:12) Right. (44:12) Right. (44:13) Well and that's just it. (44:14) So I think getting an education is great, but think about the application of technology, not the technology itself. (44:22) It doesn't matter. Speaker 2 (44:23) Oh, I'm gonna learn how to code. (44:24) I'm gonna learn how to how to, you know, how to be an admin. (44:28) I I'm gonna learn all the networking technologies. (44:31) Okay. (44:31) Great. Speaker 2 (44:32) What are you gonna do when you get to the workforce? (44:35) What's the application? (44:37) And so if you think about adding value to technology, what does that look like? (44:42) Does it look like a podcast? (44:43) Does it look like teaching? Speaker 2 (44:45) Does it look like possibly selling the technology? (44:50) Right? (44:50) Helping people solve real world problems. (44:52) That's a great application of it. (44:54) You what where is your application application of of the the technology? Speaker 2 (44:56) Technology? (44:57) Because that's really gonna matter. (44:58) Only a subset of people are gonna be the ones who are architecting the solutions. (45:03) AI is gonna be doing a lot of the grunt work now. (45:06) You need to find a way to be uniquely human in an AI based world, and that's gonna be the key going forward. Speaker 2 (45:13) That is not something that's easy to solve for, but it is what you need to do. Speaker 1 (45:19) That's that's great. (45:20) In fact, the next couple of episodes we have coming up on this show are going to talk about, I wanna do I wanna try my hand at a solo episode, see how that goes, talk about my own career, progression. (45:31) Yeah. (45:32) One one of the reasons why I wanted to talk to Joel around this time was because, you had a profound impact on my career and on my life and on my family, because I had been a sysadmin for years, and there's only a couple of career paths that you could go. (45:51) You could go deeper into tech, systems engineering, systems architecture, systems design, or you go into people management. Speaker 1 (45:58) That was kind of it or so I thought. (46:01) And I I used to tell people, I not going to be a people manager. (46:07) I don't wanna deal with people. (46:08) I'm I'm a tech guy. (46:10) So that that meant, you know, I'd have six monitors, and, you know, I'd I wanted to be able to read the matrix, basically, and that was what I thought I was going to do. Speaker 1 (46:19) Until one of one of our mutual friends ran into me at at a conference here in Kansas City. (46:26) And DevOps days, KC, 2017, something like that, 2018. (46:32) And he's like, he got a lot of personality for for an engineer. (46:36) Have you ever thought of sales? (46:38) And I literally laughed out loud. Speaker 1 (46:39) Like, I'm not a seller. (46:42) I'm not gonna sell anything. (46:44) And and you were you were gracious enough to see the potential and helped me get out of IT ops. (46:52) And my career and my my view of the world exploded during that year at at GitLab. (46:59) That's great. Speaker 1 (47:00) I ended up getting a job at Red Hat, and I worked there for five and a half years. (47:04) I did sales for a little bit, and then I found what I really love is, like, teaching, engaging with people. (47:10) You know, that whole I don't I'll never be involved with people thing kind of blew up. (47:14) And and it's just I mean, over the last seven years, it's been amazing, the journey that I've gotten to to I'm I'm not driving. (47:22) Somebody else is driving because every step of the way, I'll never be in sales. Speaker 1 (47:29) I did it for two and a half years. (47:30) Oh, I'll I'll never be in marketing. (47:33) That's such a fluff job. (47:35) I've been in marketing for, like, six now. (47:37) I'll I'll never teach. Speaker 1 (47:38) I'm teaching a class starting this week. (47:40) I mean, it's just like every time I say no, that's the next barrier to to be knocked down. (47:47) And so one of the things I wanna capture is there's so much more to to to technology than to being the guy that writes the code. (47:53) Because here in a few years, it may not be people writing code. (47:57) It may be AI, and then we're I don't know what we're doing. Speaker 1 (48:00) Hopefully hopefully, I can, you know, dive deeper into my my bourbon hobby or, you know, something. Speaker 2 (48:07) I don't know if you can get paid for that, but it is good to have an alternative interest. (48:13) I will say this. (48:13) You know, one of the interesting things about this is a lot of times we're so focused on the technology, and we think we're just gonna you know, we're gonna stay in that place. (48:20) Like you, my career storied. (48:22) I went from being on call and fixing things at a command line all the time to to coding at the command line to to to now, you know, moving into an IDE and and then moving into product management and then accidentally falling into the world of sales because somebody wasn't there to pitch something. Speaker 2 (48:39) But I was the windowless lab behind the sees scenes kinda guy. (48:43) Right? (48:43) Like, there were no there I didn't know if it was day or night when I was working. (48:46) I was in the back room. (48:47) I was setting up databases and launching servers. Speaker 2 (48:49) Like Same. (48:50) That's just what I was doing. (48:52) And the reality is that was great until it wasn't. (48:57) It's great from an experience perspective, but applying that knowledge and that experience is where the rubber meets the road. (49:04) And the sooner you can get there, the better for career trajectory, for satisfaction, and and, you know, unless you're somebody who just plain can't do those kind of things, and that's fine because we still need people who love the windows windowless lab that do that better than I do. Speaker 2 (49:20) Right? (49:20) Okay. (49:21) There there's a place for that. (49:23) But the reality is there is so much more out there. (49:26) And so when you open the aperture a little bit and just don't put the box around the technology, think about it from what value I add. Speaker 2 (49:33) All of a sudden, there's all these interesting conversations you can have with people. (49:37) Like, I got the introduction to people through product management. (49:40) Just checking with customers. (49:41) Hey. (49:41) What do you need? Speaker 2 (49:42) How do we prioritize that fix in the system or that new feature and and start rolling that out? (49:48) I think that role grows under in the era of AI. (49:52) Mhmm. (49:52) AI helps us fix things, but we have to know what people want first. (49:55) Right. Speaker 2 (49:55) Right? (49:56) So, like, there's there's things like that that I think are gonna be emphasized, and and that's the way I look at the next level of of career trajectories. Speaker 1 (50:06) I love that. (50:09) Well, I picked this up from from a from another podcaster. (50:14) So I'll I'll I stole this question. (50:17) I'll have to remember who I stole it from. (50:19) But was there anything that you wanted to talk about that that we didn't cover? Speaker 2 (50:27) So I think one of the things to think about is piggybacking off the career thing, but adding the government back in. (50:35) So a lot of times when we thought about what the government job looks like historically, it hasn't been a glamorous thing. (50:41) Right? (50:42) And and I'm seeing that change. (50:44) I think from the perspective of what's happening today in that space, what the jobs are, what the opportunities are, and what the benefits and perks are, ten years ago, I'd have been like, I don't know about government work. Speaker 2 (50:58) Now what I'm seeing is, wait a minute. (51:00) That looks like a great job with great benefits. (51:05) Did you say the word pension? (51:06) Because that's something I don't hear anymore. (51:08) Right? Speaker 2 (51:08) Like, there's things there that weren't thought about before, and so I'm starting to see more young people trend that direction. (51:14) Right? (51:15) Coming out of school, like, there's a good opportunity for me to grow with the armed forces or to grow with the civilian agencies in a way that just wasn't possible a couple short years ago. (51:26) So I think that's something to keep in mind, that we didn't talk about. (51:31) The other thing that I think is is important to keep in mind is just on the technology side. Speaker 2 (51:36) Things are changing so fast. (51:38) You don't have to know it all, but you have to have a general idea of how it's gonna affect what you do and how you're gonna work. (51:44) And so from that perspective, nobody's gonna tell you. (51:47) Right? (51:48) I'm noticing nobody in corporate America saying, and here's how you use AI in your job. Speaker 2 (51:53) It's just here it is. (51:55) Go figure it out, which is creating a chasm. (51:57) Right? (51:57) But you have to at least be aware of what's out there and what's coming and how it's gonna impact your job and adopt the pieces that are most critical to keep you most relevant. (52:09) So I think those are the two top of mind things that we didn't go over. Speaker 1 (52:13) Awesome. (52:14) Well, I'm going I'm going to permanently steal that because that that was incredibly helpful. (52:19) Like, I I worked as a contractor for the government a little over a decade ago, and I'm really, really glad I had that experience. (52:28) But it was it was kind of the cliche, like, I got paid more to not touch production than I did actually touching production. (52:36) So stereotypes are are dangerous, but they also exist for a reason. Speaker 2 (52:44) Times are changing. Speaker 1 (52:45) Yeah. (52:46) That's that's really awesome to hear. (52:47) And and I have seen a trend of more younger folks going into government work. (52:54) So that's awesome to see that that's that in that not industry, but that that side of technology is changing. (53:01) And maybe even maybe even taking the lead in some areas as as we move forward. Speaker 1 (53:05) I believe so. (53:08) So is is there anywhere you'd like to send folks to to follow along with you? Speaker 2 (53:14) You know, I'm still really active on LinkedIn. (53:17) So if you just follow me on LinkedIn, you'll find, the latest content I have. (53:21) I'm talking there not only about the technology yet. (53:25) Like, I just had a post, that I put up about AI again. (53:27) I'll I'll be doing that pretty regularly trying to follow along with things, but also just about the the human side of things. Speaker 2 (53:33) Right? (53:33) Not only the human side of technology, but when you burn yourself out on technology, what does it look like on the recovery mechanism that you're gonna gonna learn from, unfortunately? (53:44) And so if you wanna keep up with me there, that would be your best bet. Speaker 1 (53:49) Awesome. (53:50) Yeah. (53:50) I'll make sure to have links to some recent talks and articles that Joel's published as well as his LinkedIn profile in the show notes. (53:56) As I teased a minute ago, we are going to be doing a couple of episodes back to back on actually, like, three episodes or so back to back on technology careers. (54:08) A few folks that I trust very deeply are gonna come on, and we're gonna talk about careers and progression and some of the different avenues you might be able to take. Speaker 1 (54:16) So if you know some younger people that are interested in technology or if you're kind of at a crossroads in your career like like I I was when when Joel picked me up off the street, Definitely encourage you to tune in. (54:28) Make sure to share with a friend. (54:29) Of course, all all the usual things, hit the like button. (54:32) We all have to deal with it, and AI is not making this any less necessary. (54:37) Please just it takes you three seconds. Speaker 1 (54:39) Click click the like button. (54:40) Hit subscribe. (54:41) That way you get notified anytime, I produce new content. (54:44) Trying to do that more often, really leaning into this sort of teacher, mentor period of my life. (54:51) Although I'm still, you know, 13 year old stuck in a 30 year old body. Speaker 1 (54:56) So my my kids are in Legos right now, like, deep into Legos, and they're starting to fall in love with d and d. (55:02) So I'm doing my job as a nerd dad or just refusing to let go of my childhood. (55:07) I'm not sure which. (55:09) So definitely tune in for that. (55:11) Joel, thank you so much for for what you've meant to me, my career, my family. Speaker 1 (55:15) I really, truly, honestly appreciate it. (55:18) And, I love that we've we've maintained this relationship over the years. (55:22) And thank you for coming on and talking about government and AI. (55:25) I told you we'd we'd be off topic in minutes, and we were. (55:28) So not a problem. Speaker 1 (55:29) That just means that, you've gotta come on the show again, in the future. Speaker 2 (55:33) Oh, okay. (55:35) Thanks, Eric. Speaker 1 (55:36) Glad I had to twist your arm there. (55:38) So thank you all for tuning in. (55:40) Really appreciate it. (55:40) On behalf of Joel, my, my guest today, I've been Eric, the IT guy, Hendrix, and look forward to talking to you all again real soon.