Think of it as Yoga for the brain, we are going to stretch a bit.
Is AI going to do to cyber Security what it did to SEO? Let’s have a conversation about it.
“AI didn’t end cybersecurity—it just gave the attackers a factory line. Now defense has to build one too, or keep losing the race one alert at a time.” — YNOT
Let’s sit down over a couple beers and have an AI – Cyber Security Talk
Characters
Riley — cyber pro who’s convinced AI agents are about to eat the entry-level world.
Morgan — cyber pro who thinks AI will multiply the need for security, not shrink it.
Riley: Alright, I’m gonna say the quiet part out loud: in ten years, there’s no help desk. No SOC analysts. No pen testers. That whole “entry-level ladder” gets kicked over by AI agents.
Morgan: I love your optimism. It’s like watching somebody say, “Cars will eliminate traffic.” That’s not how humans work. Or attackers.
Riley: Come on. We’re already seeing agentic SOC. We’re already seeing agentic pentesting. The trend line isn’t subtle. If your job is “manually parse logs” or “search Splunk all day,” you’re basically training your replacement.
Morgan: Or you’re building your foundation. But yeah—manual-only roles get squeezed. I agree with that. Where I disagree is the leap from “AI does tasks” to “cyber jobs disappear.”
Riley: Explain how the jobs don’t disappear when the machines do the work faster, cheaper, and 24/7.
Morgan: Easy. They do the work faster, cheaper, and 24/7… for attackers too. You think only the defenders get cool toys?
Riley: Sure, attackers will use it. But that still means fewer humans needed on the defense side.
Morgan: Fewer humans for the old workflow. More humans for the new chaos. AI doesn’t reduce risk; it changes the shape of it. The surface area expands. The speed increases. And the cost of making mistakes drops to basically zero.
Riley: That’s dramatic.
Morgan: It’s accurate. When it costs an attacker pennies to generate phishing variants, rotate infrastructure, write malware, and probe your entire org like a swarm of caffeinated interns—your “security posture” becomes a moving target.
Riley: Fine. But a moving target can be defended by an AI moving faster.
Morgan: Sometimes. Until your AI breaks, gets tricked, or gets fed garbage. You remember your own advice: “Can we trust AI models with the data we give it?” Short answer: absolutely not—especially cloud models. If your org starts piping sensitive incident data into third-party systems like it’s a public trash chute, that becomes the breach.
Riley: That part I agree with. People are dumping secrets into cloud chat tools like they’re writing in a diary. If that gets hacked, you’re… well, you know.
Morgan: Exactly. So the new security work becomes: governance, model security, data boundary controls, local/private model deployments, encryption, policy, vendor risk, audit trails, and incident response for AI-powered incidents.
Riley: Sounds like GRC people cheering because they finally get to say “I told you so.”
Morgan: Don’t underestimate GRC. Somebody has to translate “cool tech” into “not going to court.” But it’s not just paperwork. It’s architecture. It’s threat modeling AI workflows. It’s validating the agent isn’t quietly doing something dumb at 3:12 AM because it “interpreted” your instructions creatively.
Riley: So your big pitch is: AI replaces the keyboard monkeys, and the rest of us become AI babysitters?
Morgan: If you want to say it rudely, sure. I’d call it “security engineering for autonomous systems.” Because the moment you run agentic tools, you’ve got new questions:
What permissions do they get?
How do you scope them?
How do you log and prove what they did?
What happens when the agent is wrong with confidence?
Riley: Okay, but let’s get practical. Somebody asked, “Best way to secure a home server.” That’s not theory—what do you tell them?
Morgan: The basics still matter. You can do something like:
Run services in containers (Docker).
Use Portainer if you want a nicer management layer.
Don’t expose ports directly to the internet if you can avoid it.
Use a secure remote access method—like Tailscale—so only authorized devices can connect.
Riley: Exactly. That’s what I tell people. Tailscale is basically an allow-listed VPN vibe. You install it only on devices you trust. Now you can reach your home lab without opening your firewall to every bored teenager with Shodan.
Morgan: Right—and AI doesn’t change that. It just changes who finds your exposed port first. Spoiler: it’s an automated scanner. Always.
Riley: And learning cyber? People ask that like there’s a secret handshake. The best way is to do it. Learn fundamentals. Learn Linux. Then dabble: red team, blue team, GRC, threat hunting, incident response, forensics—find what you like.
Morgan: Linux is still the gym. You don’t get strong by reading workouts.
Riley: And if someone’s new and asks, “Switch to Linux or run it in a VM?” I say VM. Don’t nuke your main machine while you’re learning.
Morgan: Agreed. Practice without fear. Fear makes people quit early.
Riley: Now back to the jobs. I’m telling you—entry-level tech jobs are going to vanish. There’ll be new “entry-level AI jobs,” like configuring the help desk AI. But the classic SOC path? Gone.
Morgan: The old SOC path is going to be redesigned. Not gone. And honestly, that’s overdue. We’ve been burning out humans doing repetitive triage like they’re disposable.
Riley: So you’re saying AI saves people from soul-crushing tasks.
Morgan: Sometimes. Other times it just creates bigger workloads. Because organizations will deploy ten new systems the second staffing “gets easier,” which means ten new places to get hacked. It’s like giving a company a faster car and being shocked they drive farther.
Riley: Fair. And content creation? Everybody thinks that’s easy.
Morgan: Making the video is easy. Making money is hard. Consistency is hard. Ideas are hard. KPIs, analytics, hooks, thumbnails—turns out it’s marketing with a camera, not magic.
Riley: So, where do we land?
Morgan: We land here: AI will absolutely automate a chunk of cybersecurity work—especially repetitive tasks. But it also scales both attack and defense. And when speed goes up, the penalty for weak foundations gets worse.
Riley: Meaning?
Morgan: Meaning cybersecurity doesn’t shrink. It mutates. The job titles will change, the tooling will change, the workflows will change. But the core problem—humans building systems and other humans breaking them—doesn’t disappear just because you added a clever robot in the middle.
Riley: So my “no more SOC analysts” take…
Morgan: …is half right and twice dangerous. Because the real risk is people hearing that and deciding security doesn’t matter anymore—right before the most automated threat landscape in history shows up.
Riley: That’s the twist, isn’t it? AI doesn’t end cybersecurity.
Morgan: Nope. It just makes insecurity faster, cheaper, and more scalable—so the bill for “we’ll deal with it later” comes due immediately.
Riley: And it always comes due.
Morgan: With interest.
If AI is handing bad guys a bigger crowbar, what doors are they prying open—and how do we bolt them shut?
Top threat vectors AI is promoting (the “how the bad day starts” list)
AI for security training: personalized simulations + just-in-time coaching
Counters #1, #2, #3
Adaptive phishing/vishing drills tailored to your org’s real workflows; micro-training when users are most likely to slip.
Near Future – AI in MIDDLE
The punchline nobody likes (but everyone needs)
AI doesn’t remove the need for cybersecurity. It removes the excuses for sloppy security. Because the attacker now has a cheap, dark factory—and if you don’t build your own defensive factory, you’re bringing a pocketknife to a conveyor belt.
And here’s the other truth: you can be right a thousand times. They only have to be right once.
Meanwhile, you’re not just fighting attackers—you’re fighting internal inertia, budget cycles, procurement delays, and the comforting lie that “we’ll prioritize security next quarter.” Attackers don’t have quarterly planning meetings. They don’t work 9-to-5. Their incentives are cleaner, their feedback loop is faster, and the payoff can be huge.
So yes, you’re at a disadvantage—unless you get smarter.
You set traps. You reduce their options. You slow them down. You force noise. You buy time to detect and respond. Because defense isn’t about being perfect—it’s about making the attacker spend more time, take more risk, and make more mistakes than you do.
You already know this. The problem is, we all need the reminder: the window to react is shrinking in the world of AI.
