The Art of Network Engineering

How does an English major with no technical background become one of the most recognizable voices in network engineering?
Drew Conry-Murray didn't start his career configuring routers, chasing certifications, or working in a NOC. He started as a copy editor who barely understood the networking articles crossing his desk.
Then someone threw him into a technical interview with a firewall vendor.
He had to figure it out.
That moment became part of a career spanning Network Computing, Interop, Packet Pushers, Network Break, Heavy Networking, and years of conversations with some of the smartest people in the networking industry.
In this episode of The Art of Network Engineering, Andy sits down with Drew to talk about the career behind the microphone: learning networking without formal technical training, developing the ability to ask better questions, surviving layoffs and career uncertainty, building relationships that create opportunities, and adapting as technology changes.
And, inevitably, they get into AI.
Drew explains why network engineers should become conversant with AI without assuming they need to become AI experts, why understanding software may matter more than writing every line yourself, and why human relationships still create an advantage even as technology becomes more capable.  
In this episode:
 How Drew went from English major to networking journalist 
 Learning networking by being thrown into the deep end 
 Why asking good questions is a technical skill 
 The uncomfortable reality that learning in tech never ends 
 Drew's path from Network Computing and Interop to Packet Pushers 
 What losing a job does to your identity 
 Why relationships create career opportunities 
 Whether network engineers really need to learn Python 
 How AI may reshape technical careers 
 Why being good at your job isn't always enough 
One of the strongest lessons from Drew's career is simple: you don't need to know everything before you start. You need enough curiosity to keep figuring out the next thing.
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John Capobianco is back, and this time the two of us are sitting in Munich building a subnetting game from scratch, live, with spec-driven development.

I've been vibe coding automations for the show for about six months. Some of it works. A lot of it falls over, and I've spent too many late nights chasing bugs in software I couldn't rely on. 
John wanted to show me a more structured way to build with an LLM: a constitution first, then a spec, then a clarify step where the model comes back with questions, then a plan, then the code.

Along the way we get into what a spec really is (closer to a network change plan than you'd think), why the tests get written and run without you asking, the token bill that caught John by surprise, and the CCNA study pain that nearly made both of us quit over subnetting. Eric Chou stops in partway through with his own take on why he doesn't get stuck anymore.

It's a real build, so it's messy in the good way.

John Capobianco: https://artofnetworkengineering.com/guests/john-capobianco
Eric Chou: https://artofnetworkengineering.com/guests/eric-chou
Spec Kit: https://github.com/github/spec-kit
NAF / AutoCon: https://networkautomation.forum/
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How much time did you invest in your career last year?
At AutoCon 5 in Munich, Andy sits down with Mike Bushong for a candid conversation about career growth, automation, AI, and staying valuable as network engineering continues to change.
Mike pushes back on one of the industry's most common narratives: learn automation and AI or get left behind.
Technology is changing, and learning new skills creates opportunity. But Mike argues that career development shouldn't be driven by fear. It should be about creating optionality; giving yourself more possible paths as your career and the industry evolve.
Then comes the foosball story.
Mike once worked with an engineer who desperately wanted to move into leadership but wasn't making progress. Over the course of a year, that engineer spent roughly 500 hours getting very good at foosball.
Mike asked him a much harder question:
How many hours did you spend improving your career?
That leads to the central idea of this episode: your expectations and your effort have to match.
Andy and Mike explore how network engineers can keep growing without chasing every trend, why deep technical knowledge may become more valuable as AI commoditizes access to information, and how gaining a little exposure across different areas creates "surface area" for future knowledge to accumulate.
You don't need to improve along every axis. You don't need to become an expert in everything. But you do need to keep growing.
Start small. Build exposure. Go deep where it matters. Let knowledge compound.
And every once in a while, ask yourself:
500 hours of foosball. How many hours on your career?
Full show notes, transcript and links: https://artofnetworkengineering.com/episodes/500-hours-of-foosball-20-hours-on-your-career-mike-bushong-on-staying-valuable
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AI is rapidly changing software development, but why are network engineers still hesitant to trust it?
In this sponsored episode, Andy welcomes back CBT Nuggets trainer and Data Knox creator Knox Hutchinson to discuss the intersection of AI, networking, and modern operations. Before building Transit AI, Knox spent years as a software developer delivering enterprise applications for financial institutions before transitioning into networking, a perspective that gives him a unique view of why AI adoption has looked so different across the two disciplines.
Together they explore:
 Why software engineers embraced AI years before network engineers 
 The real reasons network professionals distrust AI, and whether those concerns are justified 
 How enterprise software differs from "vibe coding" 
 Why AI should investigate network problems, not make changes 
 How junior engineers can troubleshoot complex outages with confidence 
 The role of guardrails, policy enforcement, and local LLMs in enterprise networking 
 A live demonstration of Transit AI troubleshooting a DMVPN outage in under a minute 
Rather than replacing engineers, Knox argues that AI can eliminate cognitive overload, accelerate troubleshooting, and help teams collaborate more effectively, while keeping humans firmly in control of production networks.
Links:
- Download Transit AI's free-forever SSH, serial, and API client:
https://transitai.app/aone

- Test drive Transit AI's investigation-only troubleshooting capabilities with their 14-day free trial.

For all things AONE, check out https://artofnetworkengineering.com/
*Transit AI is an AI-assisted SSH client designed to help network engineers investigate and troubleshoot infrastructure while preventing AI from making configuration changes.
Full show notes, transcript and links: https://artofnetworkengineering.com/episodes/cursor-for-network-engineers-meet-transit-ai
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In Linux, the whoami command returns the identity of the current user.
But what happens when engineers ask that same question about themselves?
Who am I if I am no longer the person who knows every command? Who am I if automation can perform the work I spent years mastering? Who am I if AI can write code I never learned how to write?
At AutoCon 5 in Munich, Andy Lapteff sat down with Network Automation Forum founders Chris Grundemann and Scott Robohn to examine one of the biggest barriers to technological change: identity.
For decades, network engineers built their careers around mastering the CLI. Certifications, maintenance windows, troubleshooting experience, and vendor-specific knowledge reinforced a particular definition of what it meant to be a skilled engineer.
Automation challenges that definition.
When our skills become part of our identity, new tools do not simply feel unfamiliar. They can feel threatening. Instead of objectively evaluating the technology, we protect the version of ourselves that the technology appears to be replacing.
This conversation explores how identity shapes our worldview, determines which ideas we are willing to consider, influences our career decisions, and ultimately affects our outcomes.
Andy also shares his own journey from publicly resisting network automation to working with Python, GitHub, AI coding tools, and open-source collaboration.
The group discusses why automation reallocates attention rather than simply saving time, how it reduces cognitive load, why engineers do not need to become professional programmers, and how AI is changing what technical expertise looks like.
The tools will keep changing.
The more important question is whether your identity can change with them.
Links:
• AONE Website: https://artofnetworkengineering.com
• NAF: https://networkautomation.forum/
• Scott Robohn: https://www.linkedin.com/in/scottrobohn/
• Chris Grundemann: https://www.linkedin.com/in/cgrundemann/
Full show notes, transcript and links: https://artofnetworkengineering.com/episodes/whoami-network-engineering-s-identity-crisis
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For everything AONE:  https://artofnetworkengineering.com/