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“AI Won’t Replace You, But Someone Using AI Might”

AI is everywhere; stickers, marketing, hype. Network engineers are understandably skeptical.

In this episode, Andy Lapteff is joined by longtime friend of the show John Capobianco (now Head of AI & DevRel at Itencho) and Mike Bushong for a practical, optimistic “ABCs of AI” discussion designed for working network engineers.

We start with a blunt reality: automation adoption is still low, and the old “automate or die” narrative hasn’t helped. Then we pivot into what’s changed: modern models are strong enough to be useful, but only if you stop treating them like a search bar and start connecting them to real tooling and real data.

John explains the core building blocks—LLMs, RAG, agentic workflows, and especially Model Context Protocol (MCP)—and why MCP may be the protocol that finally makes AI feel operationally real.

Finally, we land on a concrete “Hello World” for neteng: connect an AI client to a source of truth like NetBox or Nautobot (in a sandbox), start with read-only workflows (logs, config deltas, compliance), and build from there—safely.

If you’ve been curious but overwhelmed, this is your on-ramp.

This episode has been sponsored by Meter.

Go to meter.com/aone to book a demo now!

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What does “mission-critical networking” really mean?

At St. Jude Children’s Research Hospital, it’s not about uptime SLAs or dashboard metrics; it’s about supporting the research and care that helps save children’s lives.

In this episode, we sit down with Remington Loose and Josh Morris to explore the architecture, scale, and responsibility behind one of the most meaningful networks in the world.

We dig into:

• How research networking differs from traditional enterprise IT
• The massive data demands behind pediatric cancer research
• Designing networks where downtime isn’t just inconvenient, it’s unacceptable
• Supporting clinicians, researchers, and life-saving applications simultaneously
• Lessons enterprise engineers can learn from healthcare environments

From high-performance data movement to reliability strategies that operate without margin for error, this conversation reframes what networking looks like when human outcomes are on the line.

Because in environments like St. Jude…

The network isn’t just infrastructure; it’s part of the care team.

This episode has been sponsored by Meter.

Go to meter.com/aone to book a demo now!

You can support the show at the link below.

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Find everything AONE right here: https://linktr.ee/artofneteng

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Erika Dietrick (aka “Erika the Dev”) is back on the show, and she’s days away from a major life change (welcome, Baby Dev). In this follow-up conversation, we dig into the thing that keeps coming up in network engineering careers: programming is no longer a “nice-to-have.”

Erika breaks down her free YouTube course designed specifically for network engineers: Level 1 is “programmatic thinking” (the mindset + foundations), Level 2 is where AI becomes your learning accelerator, and Level 3 is about generating code responsibly, without falling into the “vibe coding” trap.

We also talk about why coding feels so foreign to CLI lifers, why so many “slick” courses lose beginners, and how to use AI like Google-on-steroids. If you’ve ever thought, “I’m not smart enough for this” or “I don’t have time,” this one’s for you.

What we cover:
- Why network engineers struggle with coding (and it’s not your fault)
- The difference between using AI while coding vs vibe coding
- How to build foundations that make AI actually useful
- Why libraries matter, and how Level 2 focuses on network automation libraries
- Career reality: why Python shows up in job descriptions everywhere

Find Erika:
YouTube: https://www.youtube.com/@UCkWURMuDQZox53bskCFS6vw
LinkedIn: https://www.linkedin.com/in/erikadietrick/

This episode has been sponsored by Meter.

Go to meter.com/aone to book a demo now!

You can support the show at the link below.

Support the show

Find everything AONE right here: https://linktr.ee/artofneteng