I get extra excited day by day as I be taught one thing new. Nonetheless, I even have my fair proportion of considerations concerning the future—particularly on the subject of AI and the way it will affect the function of community engineers. Okay… I in all probability have extra than my fair proportion of considerations. (That received’t come as a shock for those who’ve been following the previous couple of years of my journey, exploring the “AI FUTURE!!!”)
First off, I wish to be very clear. I’m excited about the way forward for community engineering, community automation, and my place on this fantastic world and neighborhood. In actual fact, my latest weblog, Navigating the AI Period as a CCIE, discusses how superior it’s to be a CCIE proper now.
I typically concentrate on the place I see the optimistic potentialities. How AI could make our lives and work as community engineers higher.
However in the present day, I wish to speak about one thing that worries me: how the AI future is being mentioned and described. My hope is that by discussing it, we are able to keep away from the worst potential dystopian imaginative and prescient of that future. Whereas I like studying books or watching motion pictures about these dystopian futures (a responsible pleasure of mine), I don’t wish to reside in a type of worlds. I’m additionally hoping that you simply, my neighborhood, might help me perceive whether or not my concern about the way forward for AI is overblown. So, let’s dive in, we could?
I don’t wish to be an AI babysitter…
There’s a phrase that has been exhibiting up in displays, blogs, articles, movies, press releases, authorities documentation, and nearly in every single place else discussing how AI will affect the way forward for work. The phrase refers to an strategy known as “human-in-the-loop.”
So, what is “human-in-the-loop?”
I simply did a Google seek for “‘human within the loop’ ai cisco” and Gemini was useful in giving me this abstract:
Cisco emphasizes “human-in-the-loop” AI, which means integrating human oversight and suggestions into AI techniques to make sure accountability, moral concerns, and dependable decision-making, particularly in areas like safety and knowledge evaluation.
That doesn’t sound dangerous, proper? Right here’s one other snippet from a paper I lately learn on AI and the way forward for job roles:
The extent to which it [Gen AI] can exchange people within the office will rely on the need for human oversight of machine-performed duties.
Little doubt you’ve seen or heard comparable descriptions of what it’s going to take to “safely” combine AI into day-to-day duties. Right here’s my understanding of why human-in-the-loop comes up again and again in discussions.
It comes down to some factors:
- Utilizing AI affords a “worth” companies can NOT ignore. What that worth is can fluctuate, however it typically comes down to hurry: AI is just sooner than people.
- AI isn’t at all times proper. And AI can’t be held accountable for errors.
- By having a human log out on the AI work, errors will probably be caught. And in the event that they aren’t, there’s somebody to be held accountable.
I’m NOT saying that the above factors are factually legitimate. In actual fact, every of these statements on their very own deserves quite a lot of deep consideration and dialogue. However for the sake of this weblog submit, let’s take them as they sit to additional discover my considerations a couple of future the place Hank is a “human within the loop” for AI techniques.
Right here’s the issue with “human-in-the-loop”
I like being a community engineer. I like creating community designs to satisfy enterprise calls for. I get pleasure from creating configurations and engineering strong routing protocols. I discover the method of troubleshooting a community challenge rewarding.
I’ve spent years of my life studying the talents it takes to DO community engineering. And I nonetheless have a few years forward of me as a community engineer. I even have so much to supply the businesses, networks, and workforce members I’ll work with sooner or later.
Each description I’ve learn or heard about “human within the loop” locations the human close to or on the finish of “the loop.” An AI software is posed an issue, query, or set of information to work on. Then, AI generates its answer, which is then despatched to a human to assessment, settle for, reject, or make modifications.
After I take into consideration this idea, I can’t assist however conjure up an image of row after row of people spending their days listening for the “ding” of a brand new proposed AI work merchandise, ready for the human to do their factor so the AI can proceed on its “loop,” finishing the work. That simply doesn’t sound like the longer term community engineer I wish to be.
Which is able to come first: AI or expertise?
There’s something else I ponder about on this “human within the loop” imaginative and prescient of the longer term. A human community engineer’s capacity to establish a mistake made by AI depends on whether or not that community engineer has made that very same mistake prior to now. Or, on the very least, they want sufficient community engineering expertise to note when one thing is unsuitable.
As of now, we’ve got skilled community engineers who can “oversee” AI brokers and establish potential points. Heck, that’s half of what senior community engineers and CCIEs do anyway: assist the up-and-coming community engineers on our workforce by reviewing their work and serving to them be taught from their errors.
However how will future up-and-coming community engineers acquire the expertise of being a community engineer if they’re merely a cog in “the loop?”
And sure, I’m absolutely conscious that that is an excessive instance and never what individuals imply after they say “human within the loop” or “human oversight.” Regardless, it’s vital that we contemplate this kind of excessive consequence now, when the way forward for community engineering is being written. As a result of I completely suppose there’s a means this narrative might be rotated—a future imaginative and prescient the place community engineers proceed to be community engineers greater than in identify solely.
Let’s flip it round: “AI-in-the-loop”
I suggest that we invert the loop. Make no mistake—synthetic intelligence completely affords worth to community engineers doing community engineering jobs day in and day trip. In actual fact, I exploit it myself. However I exploit AI as a useful resource—like some other—at my disposal.
Suppose I’m known as in to troubleshoot an intermittent routing downside at our Web edge. Utilizing my well-worn community troubleshooting abilities, I collect particulars concerning the challenge, carry out completely different checks, and attempt to replicate it. I examine operational output from the routers and take a look at our community administration techniques. Possibly I ask round, “What modified?”
And if everybody tells me, “Nothing. Nothing modified.” I then ask, “Properly, what modified earlier than nothing modified?”
As I do all of this, I leverage many instruments and assets. I’ll seek the advice of our inner documentation concerning the community. I’ll assessment the latest change requests. I would head over to Cisco.com and seek for error messages or situations. (Properly… no, I’ll in all probability go to my favourite search engine and seek for error messages and situations. 🙂 )
It’s right here, throughout this a part of my work, the place I’ll convey AI into “the loop.” Not solely is AI quick, however it has been skilled on and has instantaneous entry to all kinds of helpful knowledge that’s related to my work.
AI-in-the-loop: A software for community engineers
I could also be struggling to recollect the precise present command to show all the main points concerning the BGP prefixes discovered by my router. Or I’ll wish to arrange a filtered packet seize and am on the lookout for an instance configuration. Or I’m reviewing tons of of traces of debug messages and will use assist in shortly discovering the anomalies. These are examples the place AI could make ME a greater, extra environment friendly community engineer.
You see, I’m a community engineer. I’m a fairly respectable community engineer. I’ve typed thousands and thousands of CLI instructions with my fingers, seen numerous pings drop, configured routing protocols, entry management lists, VPNs, coverage maps, EtherChannels, and so forth and so forth. However I’m nonetheless only a human, not a pc. I’ll not have instantaneous entry to the whole lot buried in my mind, however I do know when the reply is in there. I do know that if I see the proper reply (or one thing shut), I can acknowledge it and get to the answer. It’s the identical cause an skilled community engineer can remedy a posh downside with one net search and a look at a discussion board submit or Cisco command reference.
We should always keep within the driver’s seat. We should always keep accountable for the networks and the community engineering. We should always embrace the capabilities of AI to enhance our community engineering work. AI shouldn’t be utilizing us to enhance its community engineering work—we needs to be utilizing AI as a useful resource to develop into simpler community engineers—now and into the longer term.
Actually Hank… is that each one AI needs to be?
So, you may be pondering:
Oh, Hank, you good previous boomer community engineer. Get with the instances… AI affords us far more than only a next-generation search engine!
Sure, it completely does—and I’m enthusiastic about quite a lot of the enhancements to the techniques and software program we use day by day. To not point out the fully new techniques and software program which can be enabled by AI. Simply Cisco’s bulletins within the AI house this previous yr excited me about its potential for community engineers.
Simply think about what we’ll be capable of do sooner or later. For the reason that first community engineer began capturing log knowledge, we’ve acknowledged that it’s practically unattainable for a human engineer to make sense of the flood of data in any well timed vogue. Consider all of the outages that would have been prevented if we have been capable of finding the small and early hints buried in counters, NetFlow knowledge, and log particulars. As for safety… wow. There’s a lot potential within the safety house to establish and reply sooner.
Embedding AI capabilities into networking merchandise will give us an enormous enhance as community engineers. However this additionally isn’t something all that new. For a few years now, machine studying capabilities have been added and iterated on to reinforce the community assurance options for the campus, WAN, and knowledge heart. They’re getting a brand new enhance from the GenAI hype and buzz proper now, however most of them aren’t GenAI.
One thing is coming to the community engineers’ world that pertains to GenAI that has me very, very excited. Pure Language Interface, or NLI, will quickly be part of the a lot cherished and lauded Command Line Interface (CLI) and the slightly-bummed-it-isn’t-the-new-kid-on-the-block-anymore Software Programming Interface (API) as strategies community engineers work together with the gadgets and techniques we handle. And that will probably be superior. Really, a sport changer.
Sure, a part of changing into a community engineer is studying all the particular instructions required to make the community work. When community engineers collect collectively and share conflict tales, somebody will at all times complain (lovingly) about the way it is not sensible that it’s “ip ospf authentication-key” however “ip authentication mode eigrp,” and why can’t they simply be the identical?! And we’ll snort and snort and snort.
However let’s be sincere. It isn’t memorizing particular command line syntax that makes us community engineers. It’s understanding how, why, and when we have to configure authentication for our routing protocol that’s essential. Received’t we be a lot happier once we can merely inform our router:
“Allow authentication for EIGRP and OSPF on all interfaces. EIGRP ought to use md5 with key-chain 5, and OSPF wants to make use of plaintext due to the legacy machine we’re related to.”
Certain, some community engineers will grumble and say issues like “again in my day.” However I do know I’ll be happier for all of it.
So what now?
So what now, you ask? Properly, I wish to hear what you all suppose. Don’t be shy. Should you suppose I’m overreacting, please inform me. Should you share my considerations, let me know I’m not alone. What excites you about the way forward for community engineering with an AI assistant in your pocket? Are there some duties you possibly can’t watch for AI to take over for you? Go away a remark under to let me know your ideas!
Within the meantime, listed here are some solutions for glorious locations to be taught extra about AI and begin constructing abilities. As a result of there’s one factor I’m completely certain of… AI is coming, and we gotta be prepared for it.
- Spend about 45 minutes Understanding AI and LLMs as a Community Engineer with this nice tutorial by Kareem Iskander.
- Make investments extra time on this glorious Community Academy course, Introduction to Fashionable AI, with my new favourite teacher, Eddy Shyu. (Don’t let the truth that it’s on Community Academy scare you away. It’s improbable for anybody seeking to get a stable basis in AI.)
- Dive in deep and “Rev Up” your recertification journey (34 Persevering with Schooling credit!) with AI Options on Cisco Infrastructure Necessities. Free in Cisco U. till April 26, 2025, and with content material and movies from 5xCCIE (and my hero) Ahmed Moftah.
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