Category: Worth Reading

Kyle Kingsbury published a long (10-part) article about his frustrations with AI, aptly named The Future of Everything is Lies, I Guess.

Regardless of where you are on the skeptic-to-fanboy spectrum, I would highly recommend you read it, even if you believe you’ll disagree with everything he wrote.

A while ago, I found the How Automatic Return Routing solves IP overlap article on Cloudflare’s blog. They evidently have a technology that addresses a pain point well worth solving (access to shared resources from clients using overlapping address ranges). I just hate how they’re selling it. Go read the article first; I’ll wait.

OK, here’s what bothers me: the “VRFs and NAT are bad” claims, while they use the same technology in disguise.

@sjhloco wrote an excellent in-depth description of how you can use containerlab and netlab to manage your labs as code.

He also documented a few netlab shortcomings (one of which caused a crash); fortunately, I found his blog post (admittedly over a year later) and fixed most of them in release 26.04:

Another week, another interesting AI article (is anyone writing about anything else these days?), this time from Noah Smith (another author worth following). I found this gem hidden in his weekly roundup:

Instead of trying to write a piece of code from scratch, or prove a math theorem from scratch, or figure out some piece of knowledge for yourself, you just ask AI to do it all for you. So everyone ends up getting the right answers to questions whose answers are already known, so they don’t end up adding anything new.

Phil Gervasi wrote an interesting article describing Rail-Optimized Networking for AI Training Workloads. Go read it first; I’ll wait.

Does it sound interesting? Were you able to see behind the curtain and figure out what it’s really about?

Milan Zapletal, the author of the biggest netlab topology I’ve seen so far (full story), has published a nice introductory article explaining What is Netlab and Why Network Engineers Should Care.

Thank you, Milan! Much appreciated ;)

In a recent article, Scott Alexander made an interesting point: What AI produces are not hallucinations but shameless guesses (also known as bullshit) because the training process rewards the correct answers but does not penalize the incorrect ones. After all, having an AI model say, “I don’t know that” is not good for business, is it?

On a tangential note, calling those blunders hallucinations was a marketing masterstroke. Not being a native English speaker, I might be missing some nuances, but I feel like hallucinations might be something you’re not responsible for (some of the time), whereas we all know who’s responsible for bullshit and shameless guesses – and responsibility is something the AI companies are clearly trying to stay as far away from as possible.

Avery Pennarun published yet another excellent article: every layer of review makes you 10x slower, effectively reiterating what I’ve been saying for decades: all the technology in the world won’t help you unless you re-architect the broken processes.

AI is no exception, but of course, the AI evangelists, LinkedIn AI Wranglers¹, and Thought Leaders will never tell you that (or even admit it).

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Geoff Huston published an article supposedly describing the challenge of securing NTP, but as is usually the case, he couldn’t skip the prior art going all the way back (almost) to the formation of Earth.

Before coming to the how do we secure NTP section, you’ll learn everything about the wobbly Earth rotation, the changes in the Earth’s angular speed, the impact of tides, the smearing of leap seconds, the differences between UT1 and UTC, why we use quasars to measure time, and everything there is to know about NTP. Have fun!

The never-ending “we will replace developers” (or networking engineers) pipe dream didn’t start with the latest bout of AI hype (or SDN). As Stephan Schwab explains in his Why We’ve Tried to Replace Developers Every Decade article, it started with COBOL, the magic high-level programming language that businesspeople would use to write their own programs.

At least some of us know how well that ended. I was also unfortunate to be there for the 5GL hype, the forms-driven programming hype, the “everyone will solve every problem out there with Excel macros” (it does work for networking inventory, doesn’t it?), and a few others. So please excuse me if I remain a bit skeptical about the latest fad, even though I find it (like all the previous ones) very useful when used conservatively in limited domains.