Mastodawn

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

Nobody likely wants to hear this, but if you plan to get into or stay in IT, software development, systems administration, or any discipline within "cybersecurity”, you *ABSOLUTELY* need to make or take time this year to identify what you can do that AI cannot do, and create some of those items if your list is short or empty. The weavers in the 1800s used violence to get a 20-year pseudo-reprieve before they were pushed into obsolescence. (1/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

We've (this includes me) got ~maybe 18mos.

I'm as pushback-on-this-“AI”-thing as makes sense/is possible. I’d like for the bubble to burst. Even if it does, the rulers of our clicktatorship will just fuel a quick rebuild. (2/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

In the past ~4 weeks I have personally observed some irrefutable things in "AI" that are very likely going to cause massive shocks to the employment models in the aforementioned sectors. I know some have already seen minor shocks. They are nothing compared to what's highly probably ahead.

In my (broad) field, I think that there are some things that make humans 110% necessary: (3/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

First is “Judgment under uncertainty with real consequences.” These new "AI" systems can use tools to analyze a gazillion sessions and cluster payloads, but they do not (or absolutely should not) bear responsibility for the "we're pulling the plug on production" decision at 3am. This “weight of consequence” shapes human expertise in ways that inform intuition, risk tolerance, and the ability to act decisively with incomplete information. (4/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

Organizations will continue needing people who can own outcomes, not just produce analysis. (5/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

Another is “Adversarial creativity and novel problem framing.” The more recent “AI” systems are actually darn good at using tools to do pattern matching against known patterns and recombining existing approaches. They absolutely suck at the “genuinely novel”; y'know, the attack vector nobody has documented, the defensive technique that requires understanding how a specific organization actually operates versus how it should operate. (6/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

The best security practitioners think like attackers in ways that go beyond "here are common TTPs." (7/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

A yuge one is “Institutional knowledge and relationship capital.” Understanding that the finance team always ignores security warnings — especially Dave — during quarter-close, that the legacy SCADA system can't be patched because the vendor went bankrupt in 2019, that the CISO and CTO have a long-running disagreement about cloud migration are just a few examples of where context shapes what recommendations are actually actionable. (8/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

Many technically correct analyses are organizationally useless.

The biggest one? “The ability to build and maintain trust.” When a breach happens, executives don't want a report from an “AI”. They want someone who can look them in the eye, explain what happened, and take ownership of the path forward. The human element of security leadership is absolutely not going away. (9/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

It'd be great if folks in very subdomain-specific parts of cyber would provide similar lists. I try to stay in my lane.

So, what are some of these “very human-only things”?

Develop depth in areas that require your presence (physical or virtual) or legal accountability. Disciplines such as incident response, compliance attestation, or security architecture for air-gapped or classified environments. These have regulatory and practical barriers to full automation. (10/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

Build expertise in the seams between systems. Understanding how a given combination of legacy mainframe, cloud services, and OT environment actually interconnects requires the kind of institutional archaeology (or the powers of a sexton) that doesn't exist in training data. (11/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

I know this will get me tapping mute or block alot, but I'm fairly certain you're going to need to get comfortable being the human in the loop for “AI”-augmented workflows. The analyst who can effectively direct tools, ****validate outputs**** (b/c these things will always make 💩 up), and translate findings for different audiences has a different job than before but still a necessary one. (12/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

**Learn to ask better questions.** Bring your hypotheses, domain expertise, and knowing which threads are worth pulling to the table. That editorial judgment about what matters is undervalued, and is going to take a while to infuse into "AI” systems. (13/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

The very uncomfortable truth: there will be fewer entry-level positions that consist primarily of "look at alerts and escalate." That pipeline into the field is narrowing at a frightening pace. (14/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

Again, this is gonna lose me follows (aw) and cause me to mute/block alot of replies, but the folks who thrive will be those who can figure out what "AI” capabilities aren't complete garbage and wield them with uniquely human judgment rather than competing on tasks where “AI” has clear advantages. A year ago, even with long covid brain fox, I could out-"John Henry" all of the commercial models at programming, cyber, and writing tasks (both in speed and quality). (15/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

Now, with the fog gone, I'm likely ~3-months away of being slower than “AI" on a substantial number of core tasks that it can absolutely do. I've seen it. I've validated the outputs. It sucks. It really really sucks. And, it's not because I'm feeble or have some other undisclosed brain condition (unlike 47). These systems are being curated to do exactly that: erase all of us John Henrys (ref for those unawares of the lore: https://en.wikipedia.org/wiki/John_Henry_(folklore)) (16/19)

John Henry (folklore) - Wikipedia

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

My formal essay on this a cpl weeks ago said the following in way too many pages: (17/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

What concerns me most isn't the senior practitioners; I'll/they'll/you'll adapt and likely become that much more effective. It's the junior folks who won't get the years of pattern exposure that built our intuition in the first place. That's a pipeline problem the industry hasn't seriously grappled with yet and isn't likely to b/c of the hot, thin air in the offices and board rooms of myopic and greedy senior executives. (18/19)

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

NOTE: I will mute or block all caustic replies from "AI Vegans”. You do your religion the way you want to. I'm trying to practically help folks.

Adding in enough hashtags **solely** to help the folks blocking "AI" content.

#AI #ArtificialIntelligence #LLM #ChatGPT #Claude #Gemini #Anthropic #OpenAI #Google #Microsoft #agentic #MCP #agent (19/19)

@hrbrmstr this just got posted to slashdot

https://it.slashdot.org/story/26/01/10/1926209/ai-fails-at-most-remote-work-researchers-find

AI Fails at Most Remote Work, Researchers Find - Slashdot

A new study "compared how well top AI systems and human workers did at hundreds of real work assignments," reports the Washington Post. They add that at least one example "illustrates a disconnect three years after the release of ChatGPT that has implications for the whole economy." AI can acco...

hrbrmstr 🇺🇦 🇬🇱 🇨🇦Jan 10

@Viss Aye (boy howdy has that made the rounds) but I didn't say "automate jobs away". And, there's no way I'd give any model a visual task to complete (in the setup preferences in my Claude I have a note saying "never ever make a chart").

There are some design flaws with the study too.