I get extra excited each day as I be taught one thing new. Nonetheless, I even have my fair proportion of issues concerning the future—particularly on the subject of AI and the way it will impression the function of community engineers. Okay… I in all probability have extra than my fair proportion of issues. (That gained’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 neighborhood. 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 optimistic prospects. How AI could make our lives and work as community engineers higher.
However at this time, I need 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 need to reside in a kind of worlds. I’m additionally hoping that you just, my neighborhood, 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 shows, blogs, articles, movies, press releases, authorities documentation, and nearly in every single place else discussing how AI will impression the way forward for work. The phrase refers to an method 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 programs to make sure accountability, moral issues, and dependable decision-making, particularly in areas like safety and knowledge evaluation.
That doesn’t sound unhealthy, 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 rely on the need for human oversight of machine-performed duties.
Little doubt you’ve seen or heard related 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 time and again in discussions.
It comes down to some 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 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 likely be caught. And in the event that they aren’t, there may be 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 submit, let’s take them as they sit to additional discover my issues 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 sturdy routing protocols. I discover the method of troubleshooting a community concern 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 crew 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 answer, which is then despatched to a human to evaluate, settle for, reject, or make modifications.
Once 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’m wondering about on this “human within the loop” imaginative and prescient of the long run. A human community engineer’s skill 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 improper.
As of now, we’ve 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 crew 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 absolutely conscious that that is an excessive instance and never what folks imply once they say “human within the loop” or “human oversight.” Regardless, it’s essential that we think about one of these excessive final result now, when the way forward for community engineering is being written. As a result of I completely suppose there’s a means this narrative may 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 provides worth to community engineers doing community engineering jobs day in and time out. In truth, I take advantage of it myself. However I take advantage of AI as a useful resource—like some other—at my disposal.
Suppose I’m referred to as in to troubleshoot an intermittent routing drawback at our Web edge. Utilizing my well-worn community troubleshooting expertise, I collect particulars concerning the concern, carry out completely different assessments, and attempt to replicate it. I examine operational output from the routers and take 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 inner documentation concerning the community. I’ll evaluate 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 educated 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 could need to arrange a filtered packet seize and am on the lookout for 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 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 could not have on the spot entry to every thing 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 clear up a posh 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 in command of 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 ought to be utilizing AI as a useful resource to develop into simpler community engineers—now and into the long run.
Actually Hank… is that every one AI ought to be?
So, you is likely to be pondering:
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 programs and software program we use each day. To not point out the fully new programs and software program which might be enabled by AI. Simply Cisco’s bulletins within the AI area this previous 12 months 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 inconceivable for a human engineer to make sense of the flood of knowledge in any well timed style. 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 may be a lot potential within the safety area to establish and reply sooner.
Embedding AI capabilities into networking merchandise will give us an enormous 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 reinforce 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 liked 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 will likely be superior. Really, a sport changer.
Sure, a part of turning into a community engineer is studying all the particular instructions required to make the community work. When community engineers collect collectively and share battle tales, somebody will at all times complain (lovingly) about the way it is unnecessary that it’s “ip ospf authentication-key” however “ip authentication mode eigrp,” and why can’t they simply be the identical?! And we’ll giggle and giggle and giggle.
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 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 system 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 need to hear what you all suppose. Don’t be shy. If you happen to suppose 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 may’t await AI to take over for you? Depart a remark beneath to let me know your ideas!
Within the meantime, listed below are some ideas for wonderful locations to be taught extra about AI and begin constructing expertise. As a result of there may be 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 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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