340: Hire AI in Enterprises with Charles Fry

Speaker A: Foreign. Here. And I'm talking with Charles Fry, the founder and CEO of codexvitos, building cyber physical systems for mid market and enterprise companies, as well as full stack Web Mobile and SaaS Development. Charles, welcome back to the show.

Speaker B: Hey, I'm um, happy to be here. It's always great to see you and I'm looking forward to our chat.

Speaker A: Yeah. So it's so interesting to talk to you because the last time we had you on the show, three or four years ago, it was still before the AI age was fully upon us. Your business was kind of a different business. And um, I've been following you on LinkedIn and I see that you have evolved your approach and now you're an AI first company. So tell me a little bit about how that came down, this whole evolution and how do you find your new, uh, focus?

Speaker B: Wow, it's been that long since we were, uh, on the show. It was a lot of fun, but here we are. You're right. Really sort of came out of left field. I'll, um, skip all the technical things that suddenly made AI an achievable thing, but really in 2024, the beginning of 2024, somebody can fact check my timeline, but ChatGPT, if you were aware of it, was kind of passing the Turing test, you know, it was giving you pretty reasonable answers to natural language questions. And we're like, wow, this is interesting. At first we were helping our clients think about how to build those capabilities into their products, something we still do. But by mid 24, late 24 became pretty obvious that one of the best applications of large language models and expert systems, they used to call them, I.e. writing software. And so by mid-2025, early to mid-25, the systems were suddenly not novelties. They were credible at what they were doing and they were gaining momentum in the quality and credibility of the software coding they did. Now, codexos was started largely to create an opportunity for entrepreneurs and enterprises that needed, let's call it garden variety, well done software built to do that through the Americas, to arbitrage the labor race in Latin America and to leverage the time zones. So it was essentially an offshore BL hybrid team effect. Honestly, by the middle of 2025, the AI tools for software engineering were as good or better than 50% of the human developers that we employed. And at some point, as a business owner, when you're out there representing yourself and your, your product is yourself and you're representing that to clients, you have a moral and ethical obligation to say, hey, I think I can still give you the best product that you're looking for. But I'm going to do it in a different way. So beginning in uh, late 2025 we were hard in the pivot of um, all of our software development. Now today is done agentically. There's still people. It's not a complete dark factory, but our mid level performers and below we exited them from the business, which is a lot of human turmoil. I mean we were at a hundred people or so, a lot of human turmoil. Our clients were going through the same thing and we were watching what was happening in their organizations and what the leadership demands were and we just made the decision to lean into it. And here we are in almost mid 26 now and it's actually going really well now. AI. And there of course anyone that opens up an Internet Browser anymore sees AI is everywhere. You read the newspaper. AI is going to change everything.

Speaker A: Every application is an AI layer. Proof. Yeah, SaaS application has a button, you know, use AI here.

Speaker B: Yeah. My view, at least the things that people should probably give me some credibility about. I'm going to keep my views more to how AI applies in the software industry, in my industry and a direct impact we see and we have clients working on things like AI and customer service or the legal department or the finance department. We do all of those things internally. Uh, AI agentic first, AI first. But those really aren't my industry and I'm not ready to make that sweeping prognosis about how it's going to change capitalism in the United States. But in the software industry it's a fundamental change and it's not done yet.

Speaker A: So what's your vision? Where is everything going, what it's going to look like three years from now?

Speaker B: Well, I'm not smart enough to know that, but I think that the patterns that we've seen and again within the world of writing software and kind of make that a broader category of activities. It's going to continue to consolidate and converge to where humans are important. But they might be the 10 or 20% input of the process. I really do think that we're going to see a day sometime in the um, call it the three to five year time horizon where a large amount of software will be software that's written and managed by software, other software systems. There's no technical reason to prevent that. So for example, I was talking to one of our clients, a CIO today, great company, couple hundred million dollars in revenue, really well run business, sizable internal IT team. But there's a lot of ongoing Maintenance and attention. That building the software is just the beginning of a five to ten year life cycle. So I think after the near term we're going to see that building the software becomes like, okay, we got that figured out. That's a largely solved problem. We'll then progress to the problem of, hey, this software has been in production for five years and it needs updates, it needs attention, it needs maintenance, it needs to scale. More software systems will take care of that. Fewer and fewer humans will be involved in that kind of stuff. And so I think that's where the software industry gets. I think it's 60 to 80% smaller in human capital than it is today, sometime soon. Yeah, I really do think it's, it's pretty close to, it's as close as I want to get to an extinction event, let's put it that way.

Speaker A: Some people say that they're, you know, SaaS companies, uh, go out of business and it's all going to be agents running around and doing things for us. But other people say that the SaaS companies are actually the SOP for whatever activity there is out there. And you need the structure. You know, the SaaS application is the structure for it. And you don't want agents to run, um, in an unstructured way. So you'd rather have these SaaS applications. What's your view?

Speaker B: I think, and that's a good way of looking at it, if you're a dinosaur like I am way back in the late 1980s or the early 1990s, when you wrote software for a company, everything was custom software because there were no packaged, no SaaS platforms. But over the last 20 years, I think SaaS companies have become, for a lot of businesses, exactly what you said. They're the embodiment of best practices. So if you take something like HubSpot, which I'm sure you and many of your audience are familiar with, you really don't need to customize it. You just need to do what its baseline processes are because they have thousands of people who've perfected what the sales motions are that work. So I think there's some truth to that. The problem with software, the problem that SaaS systems face, is that the barrier to competitive entry is much, much lower. So if you look at a company like Salesforce, and I've done, I think I've actually led three different Salesforce deployments back when I was a CIO cto, three different times, you know, that software really kind of shows its age and it's layers and layers and layers of complexity that have been built to serve um, a wide audience. It's great, it's expensive. Emerging companies don't need that. They can effectively vicode their own CRM system and it works. I think the threat for big SaaS companies is twofold. One is that the next generation of customers are going to onboard very, very differently into those systems than the previous generation of customers. I don't know what that onboarding on ramp is going to look like. The second problem they have is there's very little defensibility for having a pure software product. And the other part in our intro you talked about cyber physical systems. We're spending more and more of our product development cycles in hardware related objects, things that have a nexus in the physical world. Here's a good example. I am wearing one of these health, you know, rings, this Oura ring. There's a, you know, there's a lot of amazing hardware in here that justifies my monthly subscription for the app. The app we could recreate pretty easily. But the development and the manufacturing and the distribution of this physical item, much higher barrier for a competitor to take on. And so we have more and more of our clients are companies who have a physical thing that they either want to make it smarter and make it more connected. That's really what it comes down to. And that's a pretty exciting space. But a pure play SaaS company. I think it's going to get tough, the competitive pressure is going to be tough and the barrier to entry is going to be really low. And it's not even engineering cost anymore because the cost of engineering's drops so much in AI.

Speaker A: Uh, it's almost like it went full circle. You had all these product businesses that wanted to become service businesses to create recurrent revenue and now the service businesses, the class business, want to become product businesses to create a barrier to entry or retention or non disruptibility essentially. Isn't that interesting?

Speaker B: Yeah, I haven't thought about it exactly that way. Maybe the pushback would be professional services, business services that wanted to have a technological play or platform. That's interesting but I think we're going to see AI, at least in technology, we're going to see AI continue to lower the barrier to entry, allow a lot faster experiments with pure software ideas. And we're just focused on those things where the robots, the AI robots can't play. You know, they're not going to cut your grass. They might guide the machine that cuts your grass, but they're not going to cut your grass. And so I think that while the turmoil is still sorting out in the pure software world, we're going to see a whole big uh, set of opportunities open up where we say now we can really have smart devices. We can have devices that think about them, you know, they're aware of the world around them. They can participate with us, uh, in the day to day work. That'll be a lot of fun. I think we still have some more rough sailing ahead of us. And uh, as AI sorts itself out,

Speaker A: isn't it true that people prefer to interact with a purpose design device than a software product? And maybe an app is kind of a device that needs a software or maybe that's the overlap there. But I know that I love uh, something, it may come on my phone, but it's complicated because there's so many other stuff on there. But if I have a single purpose device like you had your oring, uh, it's easier to interact with. There's no complexity and then it lowers the exploitability.

Speaker B: Yeah, an area, an area of active study is uh, something called HMI or human machine interface. And again back in the 80s and 90s it meant, you know, are the buttons big enough for someone to push? Does a red light always mean a bad thing and a green light always means a good thing. But now that's expanded into the kind of research and psychology and sociology that you're talking about, Steve. And some of that is really amazing. I mean we have, I mean I'm sure you've seen them and your users have seen them. You can find these videos on YouTube. There's humanoid form robots and it took a while for researchers to figure out that. So like a robot doesn't need a head.

Speaker A: Okay.

Speaker B: It can have what a functionally looks like a torso with legs and arms on it. The head doesn't really need to be there. But uh, a robot with no head freaks people out. They don't like it. So the robot guys put heads on them and then they thought, well if we got a head here, we'll just

Speaker A: put a face on it.

Speaker B: But if the face is too realistic, that gave people the creeps.

Speaker A: Yeah.

Speaker B: So people didn't like faces on them. So now if you look at the current generation of humanoid, uh, autonomous, uh, robots, they have these, I don't know, sort of like pseudo faces. They sort of look like Halloween Jack O' Lanterns or something. Not scary, but they're more in the middle of. Anyhow, the things you're talking about are really fascinating. And those are the.

Speaker A: Yeah, I mean Isaac Asimov wrote about human aided robots and all the challenges that come with it. And when they have a human type scheme and what happens when they become, you know, people think that they are people and they just don't age. So all that things have been explored. But listen, I would like to, I'd like to switch gears here and ask you that. So right now, in this AI age, what drives your business? What drives growth in your business?

Speaker B: This part is truly fascinating to me. Everyone is working off of the same timeline now, which isn't a very long timeline. We don't have a lot of experience to draw on much more quickly than when the Internet became commercially available. I was there when that happened too. The acceptance of AI as a fundamental change happened in a matter of months compared to several years for the Internet as an example. And then some, you'll see some people talk about the mobile adoption. You mentioned your phone mobile phone adoption. But this has been very, very fast. And a year ago we talked to sophisticated technical buyers who said, yeah, I'm still on the fence about whether or not uh, I like agentic software development. That doesn't happen now. Everybody's like, yeah, we're using it too. What we're seeing now is it's evolved so quickly and it's had such fundamental impact that people don't know how to not only manage it inside of their business, but to deploy it inside of their business. It's really disruptive. And this is where you know, you're a pro. It's really disruptive in the organizations. And so in less than a year we've gone from hey, should I let my developers use AI to now everybody's using AI and the leading people, including our teams, can actually produce high quality commercial code faster than organizations can absorb that and faster than the org charts can adapt to the change. Our engineering teams have to adapt to the pace of the business, not the other way around. Because we get clients saying hey you guys are, you're producing too much. We can't check everything. You know, we, we haven't gone through last week's new features and capabilities to fully test those yet. We, we can't take another know load of features and capabilities this week. So we're seeing a lot of organizational behavior change that's starting to come out of this. And that's, you know, when we're talking to C level people, senior leaders, that's where most of the conversations are today. How do I retool my organization to capture the benefits?

Speaker A: Yeah, because uh, what I see is that the more AI you apply the decision velocity increases and the complexity of understanding the whole picture, the big connecting the dots, the need for that increases. So you need different kind of people who can work at that higher level of on contextualization.

Speaker B: Do you see the same thing we do? Software engineering or product development had matured into a pretty predictable cast of job descriptions, capabilities. Uh, the business processes were really well worn. We knew what the product owner did, we knew what a project manager did, we knew what a tech lead did, et cetera, et cetera. And a lot of these frankly became trade skills. Hey, I'm, I'm really good at writing code or I'm really good at doing qa. But I'm not really a systems thinker, I'm not an entrepreneur, I'm not a creator. Pick your fuzzy lens of choice. That's really what AI displaces right now. AI displaces those trade skills and frankly does them better and cheaper. There's no way to dispute that. What we look for now, and I think where the trend is going in our clients is you want systems thinkers. We have enough agentic tooling built on our own internal platform that the people operating and building product for our clients, we refer to our team as digital creators and they come from a variety of backgrounds. You don't have to be a computer science major, you do have to have some domain experience. You do have to be a, uh, systems thinker. You do have to understand what's the business value you're trying to create. But as far as actually writing really good code, nobody's doing that now. It's being done automatically. You have a couple gray hairs like I do. If you remember back, I don't know, 20 years ago, we talked about it was a war for talent. That's what everybody was looking for. And they wanted people with these highly specialized engineering skills. I think there's a new war for talent and it's going to be harder to pin down because we're going to be looking for these whole systems thinkers as opposed to technical specialists. Because AI will be the technical specialists that we need in insert business topic here.

Speaker A: Mhm. So what do you do to infuse systems thinking in your business?

Speaker B: Wow, I wish I had a good answer for that. I don't even know how to recruit for these kind of people right now.

Speaker A: Uh-huh.

Speaker B: I'll be that candid with you and your listeners. I was talking to a couple of my senior people and I said, you know, maybe we should go look for failed entrepreneurs, which is kind of A heretical thing to say, but as an entrepreneur, I know firsthand that, you know, it doesn't always work. And the fact that the business fails doesn't necessarily mean you, as an entrepreneur, are a personal failure. But entrepreneurs are about the only, I don't know, prime source I could think of for people who I've done a little bit of everything and I'm a systems thinker and you know, maybe I didn't get it right, but I could. So, you know, we talked about that, we talked about, I don't know if Disney still does it, but you know, Disney was phenomenal at producing these kind of people through their internal training programs. We're not big enough to compete with Disney. But right now, to answer your question though, how do we teach it? I, uh, can't honestly say that we do because we're still figuring out what it is that we would even teach.

Speaker A: So it's kind of a type of SOP is needed in the business. So, you know, what are the best practices to build an AI? That workforce? Um, which needs to be defined.

Speaker B: Yeah. And for larger organizations, for our clients that are running larger organizations, they have the same problem and all of a sudden their org chart is broken. And what I mean by that is if you look at the way we've traditionally built and scaled businesses, you have this pretty large cadre of managers who, you know, give you what Lightning Maester called the span of control. You know, your degree of lever. You know, when you're younger, you hear they're like, uh, ah, my manager doesn't even, they don't, they don't even do anything. Well, you've probably heard that before. Uh, my manager doesn't really do any work. It just comes in and bugs me. It's not all wrong because we rely on that manager's experience to then be sort of sliced across 6, 8, 10 other people and supervise that work. So the managers suddenly don't really do a whole lot of, they don't do a whole lot of delivering work. And I think AI is going to change that. I know that AI is changing that inside of technical teams. And so all of a sudden we have clients saying, my org chart structure doesn't translate to the way my business operates under this new agentic model. That's problem number one. And problem number two is I have people on my team that are good people and good contributors, but there's no box for them in the new org chart that I think works with an agentic workflow, if you will. Mhm. Does that make sense?

Speaker A: Yeah.

Speaker B: So two things have happened suddenly where we see a lot of press. Although I think it's maybe it's moderating a little bit about how, you know, kids coming out of university are having trouble getting entry level jobs. True enough. I think the other big collapse area on org charts is the managers who don't actually produce any output, supervising other managers and compiling the weekly report of reports. It just isn't a valuable job function at the best of times. And now it's uh, I hate to say this but it's, it's useless. And so I think there's a lot more work that we're going to have to do with our clients and ourselves on what does an org chart look like and what are the expectations of people doing work inside of a company that's moving aggressively along the lines of leveraging AI capabilities in white collar, what we would normally call white collar job functions.

Speaker A: Yeah, some years ago I uh, I thought about the org chart being broken. This top down hierarchical org chart. I think it's completely broken in my head. The org chart is more of like an amuba where you have, you know, the entrepreneur and the manager in the middle, uh, as a yin and yang and different departments report to uh, different people and there is, you got these pizza themes all over actually delivering teamwork. But that's fascinating, fascinating topic. So who are the ideal customers for you that you would like to work with? If they have the right kind of projects. So what are the right kind of customers and right kind of projects for code exitus that would be interesting uh, to look at.

Speaker B: There are two types of clients that we focus on and that we can help out quite a bit. The first type of client is one where they have a large established internal software development, product development process and they're trying to figure out how to adapt and how to modernize it and harness AI. And we can come in and we have a very opinionated point of view. We can have a couple conversations and, and they either like the direction that our telescope is pointed in and they want us to help or they say no, we think we're going to do it a different way. And that's okay too because right now nobody really knows the final answer. So we would call those engineering transformation projects. Somebody says, hey, we have a team, can you help us get better? The second type of client that we like are clients that have this physical connection issue. Uh, I'll give you an example. We have a client that principally they make pumps and motors and they put these pumps and motors out into very specific industrial applications spread all over the North America. You know, they wanted those pumps and motors to be connected to a uh, network and they wanted to collect data off of those pumps and motors to help their customers. And then when we got the data, we got the connection built, we got the electronics built for that, then we got the connectivity done for that. And now that the data is coming in, now there are a lot of AI related things that we can do with that data. So we're beginning to work on. You think about them as like supervisory agents that just sort of watch what's going on. Much more robust than the old, um, sort of filters, look for exceptions and red lights. But those are the kind, those are the kind of clients we really help on the product side. Sometimes they just come with a uh, you know, scribbled out on a napkin and it's like, hey, we have this system or this process that we envision and we need somebody to help us build it and we'll do the electronics, the AI, the software engineering and that, that does become a system. So more systems thinking.

Speaker A: Yeah. And then you combine software with hardware and then you have a, agents to, to do much of the coding and the managing or maintaining of these systems.

Speaker B: Yeah, that's right. And it's not a client of ours by the way, what the story I'm going to tell, but it's a fascinating story is uh, second degree connection and chatted with. But he runs a hundred million dollar a year manufacturing company and the second or third generation, I can't remember which, knows it. He grew up in the industry and he's in the process of building the company so that he basically can run the whole company himself from his phone. I mean he's, he's applying AI and internal business functions like finance and accounting and it's, he's done some really amazing stuff. He's automating the, the manufacturing process and the machines and the feedback. It's just stunning what this guy's able to do already. And he just picks up his phone and he's like yeah, I want to run my company from here. And I think he's going to be able to do it and I think we're going to see more of that emerging.

Speaker A: Yeah, that's fascinating. The race is going for the first one person unicorn. Right.

Speaker B: I think that's already done. I don't know if you've seen this, I can send it to you. But in New York Times there was an article a couple months ago, uh, a guy Not a tech guy, marketing guy. He and his brother run a company, an online company that generates $1.8 billion a year in sales. And it's the two of them.

Speaker A: Wow.

Speaker B: Just the spoiler alert is, I remember they sell, uh, these weight loss drugs. And he's a marketing guy with a tech flare. And so he figured out all of these marketing channels where if you order, I don't know what they are, um, Ozempic or whatever, you, if you order it online, it basically drop ships from the pharmaceutical company to you and he gets a cut. But he said in the article, he said at one point they were doing $300 million a year in sales or a month in sales. He, uh, goes, well, technically I'm not a one man company because I had to hire my brother to help me out. So.

Speaker A: But.

Speaker B: So it's two of them.

Speaker A: That's pretty crazy. Yeah, uh, that's definitely a unicorn. So if you're listening to this and you have an enterprise company and you want to harness AI in the business, and you want to create agent agentic systems to streamline the business and make it more efficient and more, uh, productive, then reach out to Charles Fry at codexitas. Any last thoughts for the listener who are thinking about building a business in the AI age that you would give as an advice?

Speaker B: I don't know that it's changed a whole lot. Um, building a business is always hard work. Um, for any listener that wants to chat about any of these topics or see if we're the right fit, they can always reach out and contact me and conversation's free and I usually learn something out of it. But no, it's. I would say that things are different. It doesn't mean that they're wrong or better. I think they're just different. And it'll be interesting to see how this all unfolds over the next few years. Yeah, I'm in it for the journey.

Speaker A: We're living in interesting times. So, Charles Fry, founder and CEO of Codex Citos, thanks for coming on the show and if you enjoyed this show, make sure you follow us on YouTube, Apple podcast, uh, give us a review and stay tuned because every week I get amazing entrepreneur on the show with us. Thanks for coming. Thanks for listening.

Speaker B: Thanks, Steve.