From Network Engineer to Applied AI: Ryan Booth on the Career Path Nobody Maps Out

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All right, you're listening to or watching, because we'll publish this to the YouTubes as well, another episode of the CTO Advisor Podcast. I have with me Ryan Booth, Principal Owner and Consultant with Blue Ridge Consulting. Ryan, welcome to the show. Well, thanks Keith, I appreciate it. Thanks for having me on. Thanks for the chat. So this has been a year in the making. I reached out to you back in, I think, June of 2025 and said, hey Ryan, we should get on the podcast and talk about kind of the journey of going from a infrastructure engineer architect to AI.

I don't know, what do you want to call it, AI developer? What are you? Yeah, it's the term that I'm starting to see come up in the industry right now is an applied AI engineer or applied AI director. Those types of roles, people are recognizing that you're not necessarily building the AI, but you're figuring out how to apply it in the real world or out there for people to utilize. And I don't think there's any shame in being an AI rapper.

I think, what is it, Cursor just signed a $60 billion deal as a result of being an AI rapper. So making it practical, both of us are users and soon customers of Cursor, and we find it a tremendously valuable tool. We'll get to that in a second, but I'm really curious because a lot of CTOs, CIOs that listen to this show are kind of watching their existing human resources and figuring now, how do I build Ryan's? How do I get from a network engineer, a systems engineer, architect, into AI applied design engineer or whatever the title is, but how do I transfer the skillset, which is valuable to this new domain?

So let's first start with background. How did you start the first part of your career? Walk us through that. Yeah, yeah. I grew up here in Amarillo, Texas, kind of middle of nowhere, but we're big enough to be on the map. And I kind of fell in love with technology and especially networking in college, classical networking person going through an associate's degree. I went through the Cisco Networking Academy and those first few classes that just absolutely beat the hell out of me in terms of learning and knowledge and all of that, I fell in love with it.

And that kind of started and pushed my career up through networking and networking infrastructure for about 10, 12 years. But then as SDN started coming in and network automation and DevOps started picking up, that was when I was kind of hunkering in and getting my CCIE. And so I kind of had to sit back and just observe a lot of that. And then towards the end of it, 2015, 2016 is when I transitioned into network automation. And it started out as kind of a gateway and that's kind of the way I recommend it for everybody that's in a current skill set now is use it as a gateway.

And I started out providing network expertise while software developers helped me learn my software development shops. And that got accelerated when I moved into the startup that did network automation, Apsara. And I spent the most of my time there just getting clobbered by the engineering teams out of Silicon Valley that I worked with. Basically them teaching me the ropes of software development, how to write real code, how to build enterprise grade solutions, how to maintain them. It's not just about making it done right the first time, but you got to iterate on that hundreds and hundreds and hundreds of times.

And I think that's what makes a true professional in the space. Pause there at the Apstra part of this. I've worked with you when you were at Apstra, the CTO advisor, before Juniper was acquired by HPE, Apstra and the Juniper folks were customers of ours. We did a really interesting project in which we brought the solution into the CTO by the hybrid infrastructure, deployed it and said, hey, this is how you operationalize network automation and intent-based networking, which has obviously a bunch of parallels to AI.

The challenges are the same. So I want to make sure we don't leave this part of your career without sticking a pin in it. Yeah. There is a awful lot of parallelism between, I want to identify this like transferable skill in people. Let's jump ahead really far and just oppose that more traditional vendor side and practitioner side career to what you're doing today. Because what you do today on surface looks very different than what you did two, three years ago.

How are you using and working with AI today? Yeah, so I've basically AI has replaced my software developer skillset. I very rarely manually write code anymore. For the most part, I have that process and what I'm working on nailed down to build out applications or test stuff or explore different areas. And so it is more of a, less of a software engineer typing on the keyboard and more of changing hats all the time, trying to get the best performance out of my AIs and my workflows and of course building on them.

But with all that background, I come from the infrastructure side. I come from the customer side. It gives me a real deep understanding of what the customers are wanting, what they face in the trenches. And a lot of times that doesn't make the transition into the vendor space to understand how do we improve these things? And so that's what I'm trying to do is all of those lessons learned and all of those deep fights that I went through in the network automation and the DevOps days, teaching executives what matters, teaching teams how to dig into the problems and solve them, how to build trust in the system and in your colleagues and learn in a very vulnerable environment.

Those were what I just basically took and put right into place with AI and just started running full force. Well, there's kind of this, I know executives are looking and they're asking the question they were asking me in this. And if we were live in front of them, they'd stop us and say, wait, what the hell? We just jumped from like a network automation expert to AI expert and before we hit record, you building a virtual advisor for your wife's business. Like, how do we get there?

Where's the in between? So let's put some meat on the bone. There's no question to me, I've seen like your software development skill, like when you were developing software. So you understand, I think, a couple of different things. Obviously, you understand development workflows. That's a given. What you also understood, had to understand was this integration point between the two products or the two disciplines. The network, you were a network expert, one. CCIE level, if not equivalent, CC, well, if not a CCIE, equivalent level of expertise.

But also you have this soft business skill that I think executives need to identify. Let's drill into that. Talk to me about the combination of skills of being kind of the architect that understands both products and the architect that needs to integrate the product to solve what problem? Like what problem were you solving when you integrated Apstra and Terraform? Yeah, yeah. No, and that's a great point to bring up. And I'm going to come from the reverse side of this.

I'm going to come from the trenches and I'm going to come from that guy whose first tech job was level one support. Scratch that, not even level one support. I got to answer voicemails for level one support and translate them into tickets. From this side, you grow and you learn to build the tools that you're learning. You learn how to configure a router or switch or you learn how to set up a Kubernetes infrastructure or whatever it may be, write an application.

But as you grow into a mid and senior level, you command that area and your work pretty confidently, but you don't do well working across teams. And when you move more from the senior level into a more staff level, which is you see that more common in the vendor side than I do see staff level engineers. Anyways, but once you get there, the key step for your staff engineers is being able to dynamically control a project and a set of goals across all parts of the infrastructure.

And not just the software team, but the app team, the business team, and all those people. You got to pull it together. Even though there might be a product manager there, you have to give technical direction as a staff engineer. That's kind of what's expected of you. And so I think that's where a lot of value comes is because I've usually stepped into organizations, especially from my early days, that needed that leadership, that needed that guidance. It wasn't the technology that failed them.

It was the lack of skillset and knowledge and direction of how to use the technology that failed them. And so I'd have to come in and clean that up. And so when you do that, you learned that you spent more meetings with business people discussing business things than you do clickety-clack at a keyboard configuring something. And so I've kind of built those two skillsets up side by side because I know I can build whatever I want to build, but I eventually have to either sell it or market it.

And so I need those others with me. So we've established the archetype. The archetype is the curious engineer who is willing to put in the work, become CCNA, start down the CCNE, CCNE, I'm sorry, CCIE route. Doesn't matter if you achieve it or not, but this is the person that goes down that route. They establish the pattern of being the one that gets stuff done. You're the physical management station of a genetic AI process. I give it a problem, it's going to solve the problem.

This is the archetype of people that's on my staff. This is who you are as a engineer. Now let's talk about the evolution because that's the part that I think we sometimes get stuck on. Yes, you've proved in your career over and over again that you can reinvent yourself, going from a network engineer to network automation, from network automation to business process, from business process, now AI. Let's talk about in some level of detail of that AI transformation. What did it take for you technically to go from someone who knew how to develop software to somebody who understood a genetic AI?

I've read some of your stuff. You absolutely understand a genetic AI. Because for me, looking on the outside in, it was Ryan Booth, the network automation specialist who transferred into DevOps to somebody who would now, wait, this guy's building a genetic AI workflows. What the hell, man? How did that happen? Yeah, I have to start with where it failed to cover this one. And I'm gonna go all the way back to when we first met. And that was network field day 12.

And we went to, and if you weren't in this one, I apologize, I should have looked this up first. But we went to listen to a machine learning presentation that was in private held by, it was Extreme Networks at the time. Yes, a few known faces were at Extreme and we went to a network field day there. And they just layered on the machine learning discussion to the whole delegate panel. And all the normal actors back then were in that panel and we were all just equally mind mush on what they were discussing.

And if you go back and listen to that presentation right now, it's pretty much the same stuff we were talking about two or three years ago, but more in general. And back then it clicked and it was like, I need to get into this. I need to pay attention to it, but I never really sucked my teeth into it. Come 2015, 2016, I'm really deep in network automation. I'm really trying to push a number of different areas. And I had people at startups be like, hey, we're checking out this network automation stuff.

You should come jump in and play with it with us. And I was like, I mean, not network automation, but machine learning. And I was like, it's too abstract for me. I've tried to learn it two or three times. I can't get into it. I can't find a practical use for it in my job. And I skipped out on those few startups then, but it wasn't until the first thing that landed was the art generation stuff. And I saw it and was like, whoa, this is cool.

And I've been painting, I've been doing art my entire life. It's always kind of been a side hobby, but that was my in. I can go on Saturday mornings when everybody's asleep, I can pull up Google CoLab notebooks and learn how to generate AI art. That is what allowed me to sink my teeth into it. I played around with it for six, seven months and then ChatGTP landed, and then it just became a whirlwind. But I just kind of kept that momentum of curiosity.

And once we crossed the bridge with ChatGTP we could see that it could make intelligent decisions and it could actually put code together and router configs together. It was like, oh yeah, this is it. And so that's five years, five years in the making. I wanna consider myself a professional. I wouldn't even consider myself a machine learning engineer because those guys are way, way better at that job than I am. But you put all the same smart people in a room from all these different areas and I'm gonna connect the dots for them.

So I think that's the key pattern to recognize here is that you have to give your team something that they're curious about. Yes. For you, it was AI art that led into you to eventually take your genetic AI capabilities and marry them to application development. You've built some really cool stuff. I'll put some links to some of the things that you've built to now advising organizations on their AI strategy. I want to bring you in and you were to help assess me on my staffing needs.

What do you think the top two or three priorities when it comes to helping build this muscle internally, what do you think that will look like? Yeah, I think that you come into any process like this, I think you really gotta sit back on and look at the workflows, look at how the normal business or how the normal teams work through their operations. Coming in and just saying, all right, let's rip everything out and let's chase this down or make everything AI or stuff like that never really flows well, especially when you have a ton of people in the engineering space and in your engineering team who just don't have the confidence and the skills yet.

But you come in and you find those workflows and traditional workflow management and product management type stuff is you find the bottlenecks and you start squashing them and you start working on them. Bottlenecks don't necessarily have to be a person, they could be something that AI can pick up and make happen for you or it kicked the can down the road a little bit better to help your teamwork better. I think right now we're really hitting a point where everybody is overloaded with work, has too much going on and we have to make more happen.

And I think instead of us getting deep heads down into just getting it or making it happen, we need to start looking at these workflows and improving them. Make the AI work for us so we don't have to as much. Yeah, right. I love that you went somewhere completely different with the concept than I initially presented. I asked you, hey, how should I look at my staffing? And you said, slow up, Keith. Let's talk about practical, pragmatic AI. What can this tool do for me today?

Like I have these processes, I have these bottlenecks, I have these tickets, I have these themes that I need to either summarize, I need to help my people out, link to the HPE story around the town of Vail of how they didn't use AI to replace people, but to be able to go back and summarize microfiche data. Like that was transformative for their business and not necessarily adopting AI to replace people or having their people learn AI. They had their people be able to leverage the tool in a way that's practical.

All right, that's all the time we have for this episode. We're gonna do some really amazing experimentation on LinkedIn. I'm gonna come out with a problem statement from one of the bio rooms, and you're going to help me kind of walk through it from a technical perspective. We're gonna do this as a live AC discussion on LinkedIn. You wanna follow this conversation, follow either me or Ryan on LinkedIn. com. Ryan, where can we find you? Oh man, LinkedIn is probably the best place to find me.

I should be under my name, Ryan Booth. I'm also on Substack, I have my blog going there. It's actually under Abstract Ryan. You'll find me, but you'll find a link there. Also my portfolio page, this is where I do a lot of exploratory work around advertising and AI for personal branding and stuff like that. So I have my portfolio out there that shows a lot of my work. It's agentic friendly and it's interactable both by a human and an AI.

If you wanna see what that looks like and how it can be handled, feedback's always welcome. All right, Ryan, thanks a lot for joining the program. Talk to you guys next CTO Advisor podcast.