I get extra excited day-after-day as I be taught one thing new. Nevertheless, I even have my fair proportion of considerations in regards to 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 if you happen to’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 great world and group. In actual fact, my current weblog, Navigating the AI Period as a CCIE, discusses how superior it’s to be a CCIE proper now.
I usually concentrate on the place I see the constructive potentialities. How AI could make our lives and work as community engineers higher.
However at the moment, I wish to discuss one thing that worries me: how the AI future is being mentioned and described. My hope is that by discussing it, we will 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 wish to reside in a type of worlds. I’m additionally hoping that you simply, my group, may 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 method 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, that means integrating human oversight and suggestions into AI programs to make sure accountability, moral concerns, and dependable decision-making, particularly in areas like safety and information evaluation.
That doesn’t sound dangerous, proper? Right here’s one other snippet from a paper I not too long ago learn on AI and the way forward for job roles:
The extent to which it [Gen AI] can change people within the office will depend upon the need for human oversight of machine-performed duties.
Little doubt you’ve seen or heard related descriptions of what it’ll take to “safely” combine AI into day-to-day duties. Right here’s my understanding of why human-in-the-loop comes up time and again in discussions.
It comes down to a couple factors:
- Utilizing AI affords a “worth” companies can NOT ignore. What that worth is can fluctuate, but it surely usually comes down to hurry: AI is solely quicker than people.
- AI isn’t all the time proper. And AI can’t be held accountable for errors.
- By having a human log out on the AI work, errors might 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 loads 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 few future the place Hank is a “human within the loop” for AI programs.
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 situation rewarding.
I’ve spent years of my life studying the abilities 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 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 software is posed an issue, query, or set of information to work on. Then, AI generates its resolution, which is then despatched to a human to assessment, 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 wish to be.
Which is able to come first: AI or expertise?
There’s something else I’m wondering about on this “human within the loop” imaginative and prescient of the long run. 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 fallacious.
As of now, we have now 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: help the up-and-coming community engineers on our group by reviewing their work and serving to them be taught from their errors.
However how will future up-and-coming community engineers achieve 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 folks imply after they say “human within the loop” or “human oversight.” Regardless, it’s vital that we think about 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 method this narrative may be circled—a future imaginative and prescient the place community engineers proceed to be community engineers greater than in title 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 another—at my disposal.
Suppose I’m known as in to troubleshoot an intermittent routing drawback at our Web edge. Utilizing my well-worn community troubleshooting abilities, I collect particulars in regards to the situation, carry out completely different checks, and attempt to replicate it. I examine operational output from the routers and have a look at our community administration programs. Perhaps 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 sources. I’ll seek the advice of our inside documentation in regards to the community. I’ll assessment the current change requests. I’d 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 carry AI into “the loop.” Not solely is AI quick, but it surely has been educated on and has on the spot entry to all types of helpful information 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 in regards to the BGP prefixes realized by my router. Or I’ll wish to arrange a filtered packet seize and am in search of an instance configuration. Or I’m reviewing lots 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 first rate 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 on the spot entry to all the pieces 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 purpose an skilled community engineer can resolve a fancy drawback with one internet search and a look at a discussion board submit or Cisco command reference.
We must always keep within the driver’s seat. We must always keep answerable 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 turn into more practical community engineers—now and into the long run.
Actually Hank… is that every one AI needs to be?
So, you is perhaps 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 loads of the enhancements to the programs and software program we use day-after-day. To not point out the fully new programs and software program which can be enabled by AI. Simply Cisco’s bulletins within the AI house this previous 12 months excited me about its potential for community engineers.
Simply think about what we’ll be capable of do sooner or later. Because the first community engineer began capturing log information, we’ve acknowledged that it’s practically not possible for a human engineer to make sense of the flood of knowledge in any well timed trend. Consider all of the outages that would have been prevented if we had been capable of finding the small and early hints buried in counters, NetFlow information, and log particulars. As for safety… wow. There may be a lot potential within the safety house to establish and reply quicker.
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 information 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 beloved 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 units and programs we handle. And that might be superior. Really, a recreation 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 struggle tales, somebody will all the time 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 chuckle and chuckle and chuckle.
However let’s be sincere. It isn’t memorizing particular command line syntax that makes us community engineers. It’s figuring out how, why, and when we have to configure authentication for our routing protocol that’s essential. Gained’t we be a lot happier after 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 assume. Don’t be shy. If you happen to assume I’m overreacting, please inform me. If you happen to 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’ll be able to’t look ahead to AI to take over for you? Depart a remark under to let me know your ideas!
Within the meantime, listed here are some ideas for wonderful locations to be taught extra about AI and begin constructing abilities. As a result of there’s one factor I’m completely positive 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 wonderful 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 unbelievable 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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