I get extra excited day by 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 affect the position of community engineers. Okay… I most likely have extra than my justifiable share of issues. (That received’t come as a shock in the event you’ve been following the previous few 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 reality, my latest 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 optimistic prospects. 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 attainable 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 dwell in a type of worlds. I’m additionally hoping that you just, my neighborhood, will 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 shows, 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 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, which 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 knowledge evaluation.
That doesn’t sound unhealthy, proper? Right here’s one other snippet from a paper I just lately learn on AI and the way forward for job roles:
The extent to which it [Gen AI] can substitute people within the office will depend upon the need for human oversight of machine-performed duties.
Little question you’ve seen or heard related 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 time and again in discussions.
It comes down to some factors:
- Utilizing AI presents a “worth” companies can NOT ignore. What that worth is can range, however it 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 off on the AI work, errors will probably 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 reality, every of these statements on their very own deserves numerous 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 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 get pleasure from creating configurations and engineering sturdy routing protocols. I discover the method of troubleshooting a community challenge 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 loads to supply the businesses, networks, and staff 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 device 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 evaluate, settle for, reject, or make adjustments.
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 longer term community engineer I wish to be.
Which can come first: AI or expertise?
There’s something else I’m wondering about on this “human within the loop” imaginative and prescient of the longer term. A human community engineer’s capability 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 flawed.
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: assist the up-and-coming community engineers on our staff 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 once they say “human within the loop” or “human oversight.” Regardless, it’s essential that we take into account any such excessive consequence now, when the way forward for community engineering is being written. As a result of I completely suppose there’s a approach this narrative could 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 presents worth to community engineers doing community engineering jobs day in and day trip. In reality, 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 challenge, carry out completely different exams, 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 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 eventualities. (Properly… no, I’ll most likely 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 deliver AI into “the loop.” Not solely is AI quick, however it has been skilled on and has instantaneous entry to all types of helpful knowledge that’s related to my work.
AI-in-the-loop: A device for community engineers
I could also be struggling to recollect the precise present command to show all the small print concerning the BGP prefixes realized by my router. Or I could wish to arrange a filtered packet seize and am on the lookout for an instance configuration. Or I’m reviewing a whole bunch 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 reasonably first rate community engineer. I’ve typed hundreds of 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 instantaneous entry to every part 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 fancy drawback with one internet search and a look at a discussion board put up or Cisco command reference.
We should always keep within the driver’s seat. We should always keep answerable 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 ought to be utilizing AI as a useful resource to turn into more practical community engineers—now and into the longer term.
Actually Hank… is that each one AI ought to be?
So, you is perhaps pondering:
Oh, Hank, you good previous boomer community engineer. Get with the instances… AI presents us far more than only a next-generation search engine!
Sure, it completely does—and I’m enthusiastic about numerous the enhancements to the programs and software program we use day by day. To not point out the utterly new programs and software program which are 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 be capable of do sooner or later. Because the 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 data in any well timed vogue. Consider all of the outages that might have been prevented if we had 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 house to establish and reply quicker.
Embedding AI capabilities into networking merchandise will give us a large 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 boost the community assurance options for the campus, WAN, and knowledge middle. 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 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 gadgets and programs we handle. And that will probably be superior. Actually, a sport changer.
Sure, a part of changing into a community engineer is studying all the precise instructions required to make the community work. When community engineers collect collectively and share conflict tales, somebody will all the time 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 snicker and snicker and snicker.
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 vital. 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.”
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? Properly, I wish 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 possibly can’t look ahead to AI to take over for you? Go away a remark beneath to let me know your ideas!
Within the meantime, listed below are some strategies for wonderful locations to study extra about AI and begin constructing expertise. As a result of there may be 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 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 incredible for anybody seeking to get a strong 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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