I get extra excited day-after-day as I study one thing new. Nonetheless, I even have my justifiable share of issues concerning the future—particularly on the subject of AI and the way it will impression the position of community engineers. Okay… I in all probability have extra than my justifiable share of issues. (That received’t come as a shock for those who’ve been following the previous few years of my journey, exploring the “AI FUTURE!!!”)
First off, I need to be very clear. I’m excited about the way forward for community engineering, community automation, and my place on this fantastic world and group. In truth, 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 constructive prospects. How AI could make our lives and work as community engineers higher.
However at this time, I need 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 doable dystopian imaginative and prescient of that future. Whereas I like studying books or watching films about these dystopian futures (a responsible pleasure of mine), I don’t need to reside in a kind of worlds. I’m additionally hoping that you just, my group, may also help me perceive whether or not my concern about the way forward for AI is overblown. So, let’s dive in, lets?
I don’t need 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 all places else discussing how AI will impression the way forward for work. The phrase refers to an strategy referred to 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, that means integrating human oversight and suggestions into AI methods to make sure accountability, moral issues, 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 depend upon the need for human oversight of machine-performed duties.
Little doubt you’ve seen or heard comparable descriptions of what it can 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 a couple factors:
- Utilizing AI provides a “worth” companies can NOT ignore. What that worth is can range, however it typically comes down to hurry: AI is just quicker than people.
- AI isn’t at all times proper. And AI can’t be held accountable for errors.
- By having a human log off 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 truth, every of these statements on their very own deserves plenty of deep consideration and dialogue. However for the sake of this weblog put up, let’s take them as they sit to additional discover my issues a couple of future the place Hank is a “human within the loop” for AI methods.
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 take pleasure in creating configurations and engineering strong routing protocols. I discover the method of troubleshooting a community problem 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 rather a lot to supply the businesses, networks, and group 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 instrument is posed an issue, query, or set of knowledge to work on. Then, AI generates its resolution, which is then despatched to a human to overview, settle for, reject, or make adjustments.
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 long run community engineer I need 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 long run. A human community engineer’s means to establish a mistake made by AI depends on whether or not that community engineer has made that very same mistake previously. Or, on the very least, they want sufficient community engineering expertise to note when one thing is mistaken.
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 group by reviewing their work and serving to them study 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 totally 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 crucial that we take into account this sort of excessive end result now, when the way forward for community engineering is being written. As a result of I completely assume there’s a approach this narrative could be circled—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 provides worth to community engineers doing community engineering jobs day in and day trip. In truth, I exploit it myself. However I exploit AI as a useful resource—like some other—at my disposal.
Suppose I’m referred to as in to troubleshoot an intermittent routing downside at our Web edge. Utilizing my well-worn community troubleshooting expertise, I collect particulars concerning the problem, carry out totally different assessments, and attempt to replicate it. I examine operational output from the routers and take a look at our community administration methods. Possibly I ask round, “What modified?”
And if everybody tells me, “Nothing. Nothing modified.” I then ask, “Nicely, what modified earlier than nothing modified?”
As I do all of this, I leverage many instruments and sources. I’ll seek the advice of our inside documentation concerning the community. I’ll overview the latest change requests. I’d head over to Cisco.com and seek for error messages or eventualities. (Nicely… no, I’ll in all probability go to my favourite search engine and seek for error messages and eventualities. 
)
It’s right here, throughout this a part of my work, the place I’ll carry AI into “the loop.” Not solely is AI quick, however it has been skilled on and has on the spot entry to all kinds of helpful knowledge that’s related to my work.
AI-in-the-loop: A instrument for community engineers
I could also be struggling to recollect the precise present command to show all the main points concerning the BGP prefixes realized by my router. Or I’ll need to arrange a filtered packet seize and am in search of an instance configuration. Or I’m reviewing tons of of strains of debug messages and will use assist in rapidly 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 reasonably respectable community engineer. I’ve typed tens of millions 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 on the spot entry to all the things 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 put up or Cisco command reference.
We must always keep within the driver’s seat. We must always keep accountable for the networks and the community engineering. We must 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 long run.
Actually Hank… is that each one AI needs to be?
So, you could be considering:
Oh, Hank, you good previous boomer community engineer. Get with the instances… AI provides us far more than only a next-generation search engine!
Sure, it completely does—and I’m enthusiastic about plenty of the enhancements to the methods and software program we use day-after-day. To not point out the utterly new methods and software program which can be enabled by AI. Simply taking a look at Cisco’s bulletins within the AI house this previous yr excited me about its potential for community engineers.
Simply think about what we’ll have the ability to do sooner or later. For the reason that first community engineer began capturing log knowledge, we’ve acknowledged that it’s practically unimaginable for a human engineer to make sense of the flood of knowledge in any well timed vogue. Consider all of the outages that might 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 quicker.
Embedding AI capabilities into networking merchandise will give us a large increase 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 boost the community assurance options for the campus, WAN, and knowledge heart. They’re getting a brand new increase 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 a 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 Utility Programming Interface (API) as strategies community engineers work together with the gadgets and methods we handle. And that will probably be superior. Really, a recreation changer.
Sure, a part of turning into a community engineer is studying all the precise instructions required to make the community work. When community engineers collect collectively and share warfare tales, somebody will at all times complain (lovingly) about the way it is senseless that it’s “ip ospf authentication-key” however “ip authentication mode eigrp,” and why can’t they simply be the identical?! And we’ll snigger and snigger and snigger.
However let’s be trustworthy. 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 necessary. 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 linked to.”
Positive, 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? Nicely, I need to hear what you all assume. Don’t be shy. If you happen to assume I’m overreacting, please inform me. If you happen to share my issues, 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’ll be able to’t look forward to AI to take over for you? Depart a remark beneath to let me know your ideas!
Within the meantime, listed below are some strategies for glorious locations to study extra about AI and begin constructing expertise. 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 Trendy AI, with my new favourite teacher, Eddy Shyu. (Don’t let the truth that it’s on Community Academy scare you away. It’s incredible for anybody trying to get a strong basis in AI.)
- Dive in deep and “Rev Up” your recertification journey (34 Persevering with Training 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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