Awareness is the first casualty of convenience

Back when I worked in IT infrastructure, we had all kinds of monitoring systems. SNMP tools gave us stats—uptime, disk space, CPU load. You could look at a dashboard and feel like you knew what was going on.

But if you’d ever worked in a real server room, you knew the tools didn’t tell the full story.

They didn’t tell you how hot it was in the back of the rack. 

They didn’t tell you if a fan was whining just a little off pitch. 

They definitely didn’t tell you if it smelled wrong—that faint burnt plastic smell that meant something was about to fry.

And sometimes, the fix wasn’t technical at all.

There was a running joke about the vacuum. Every so often, a server would go down. Logs would show nothing. Power was out. No alerts triggered. Nine times out of ten, it turned out someone from the cleaning crew had unplugged the power strip to plug in a vacuum.

No dashboard catches that. But the on-site tech who knew the cleaning schedule? They figured it out in seconds.

That’s edge intelligence.

Not just local processing. Not just faster response times. But decisions made with proximity, context—and awareness.

Today, AI lives on the edge. Embedded in phones, cars, appliances, workflows. We don’t ask it questions. We just let it act. And most of the time, that feels fine. Better than fine. Convenient.

Until something doesn’t smell right.

And by then we had stopped paying attention.

I first wrote about this idea back in 2018, before ChatGPT or GenAI were part of the conversation. The post was called AI + IoT + Humans = Intelligence on the Edge, and at the time, edge computing was mostly a technical buzzword. But the core question—where do we want decisions to live, and what happens when we stop noticing them?—feels even more urgent now.

But even then, I was asking the same question: Where should decisions live? And now, with AI embedded in everything, that question feels even more urgent.

Simple, Complicated, Complex

I first revisited this in Forget STEM, Get a BFA, where I broke down systems into three types:

• Simple is a recipe.

• Complicated is launching a satellite into space.

• Complex is raising a child.

Right now, technology is excellent at simple. It’s getting pretty good at complicated. But complex is still where humans shine. Because complex systems aren’t just about inputs and outputs—they’re about adaptation, ambiguity, and interpretation.

The danger isn’t that AI takes over. It’s that we let it step into complexity and stop paying attention.

AI Doesn’t Replace Judgment—It Replaces Noticing

We think of automation as replacing effort. But what it often replaces is awareness. Small nudges. Tiny decisions. Things we used to notice but no longer do, because the system already “took care of it.”

But was that the decision we would have made? 

Did it consider what we would have considered?

This isn’t about being anti-AI. 

It’s about being pro-agency.

Scale Without Awareness Is Drift

I talk a lot about scale. But scale without awareness is drift. Human judgment doesn’t scale like software—but it does adapt. It learns. It feels. It hesitates. It zooms out and says, “wait, something’s off.”

Edge intelligence isn’t just a technical concept—it’s a leadership test.

A System That Nudges You Is Still a System That’s Steering

We assume AI is “just helping” when it finishes our sentence, flags a message, or reroutes a call. But every system that nudges you is a system that’s shaping your behavior. That’s not inherently bad—but it’s not neutral either.

And if we don’t notice it… 

Who’s really making the call?

Leaders Need Clarity at the Edge

For founders, executives, and anyone building systems:

• Where are decisions being made in your org?

• What’s being automated that no one’s watching anymore?

• What “common sense” have you accidentally designed out of your workflows?

One of the lessons I come back to again and again:

That’s not just a technology truth—it’s an organizational one. As things become more dynamic, we push decisions to the edge. But if we don’t stay aware of what’s happening at the edge, we risk becoming strangers to our own systems.

Practical First Steps

1. Walk the edge: Get close to where decisions are actually being made—by systems and people.

2. Audit your automations: What have you stopped noticing? What’s being handled “by default”?

3. Teach awareness, not just procedure: Equip teams not just to execute, but to sense and interpret.

Because awareness is the first casualty of convenience. And agency is the cost.

The Personal Edge

On a personal level, I see this everywhere now. My watch tells me to stand. My car nudges me to stay in my lane. My inbox drafts the email before I’ve finished the thought.

It’s helpful. And unsettling.

Like when my daughters play a few Chappell Roan songs on my YouTube Music account, and suddenly the algorithm decides I’m a Chappell Roan superfan. Every playlist, every mix, every suggested track—Chappell Roan. And it doesn’t reset. One moment of borrowed curiosity becomes the new me.

That’s why I’ve developed a system. I actually appreciate the recommendations YouTube Music gives me—when they’re based on my listening habits. So I’ve started managing my algorithms like they’re sensitive ecosystems.

I love Christmas music. One of my guilty pleasures. From Thanksgiving to New Year’s, it’s basically a holiday soundtrack. But I don’t want it to mess up my algorithm. So I listen to it on Spotify.

Same goes for my “High Energy Baroque” playlist. It’s my go-to when I need to concentrate. But I don’t want YouTube thinking that’s my main vibe. So that’s Spotify too.

I’m not just choosing what to listen to— 

I’m choosing what gets counted.

Because in the background, choices are always being made. 

The question is: 

Which ones am I actively making—and which ones am I letting the system make for me?

That’s the real edge. Not where the technology lives. But where awareness fades.

Berkson's Bits 

Do you trust Yelp reviews? YouTube comments? Even business sites like Trustradius and G2?

Now what if I build agents to generate massive amounts of comments and reviews at scale? We make a lot of our purchasing decisions based on social trust—a referral or recommendation, word-of-mouth. Over the last decade I've watched an erosion of trust in the platforms built to support, enable, and encourage this.

If I have my own agent that can communicate at scale with the agents of people I know and trust, does that obviate the need for platforms? Anyone want to build that?

What I’m Listening To...

I grew up in the Saturday Morning Cartoon generation. Schoolhouse Rock was a critical element of my education. I learned about the Constitution and the legislative process, math, science, and grammar. In grammar, I learned about nouns, verbs, and even adverbs (some of you are singing "Lolly, Lolly, Lolly..." in your head right now).

And, of course, conjunctions. I just came across this cover of Conjunction Junction by Couch and I am obsessed! Enjoy!

(For those who want to hear the original, check it out here.)

We all have some measure of automation that we take for granted or are even unaware of. Vendors are trying really hard to add more features every day. No, Google Workspace, I do NOT need a summary of every email at the top of my email.

I’d love to hear your stories—about automations that worked, ones that didn’t, or moments when you caught yourself handing off something you should’ve held onto.

I’ve also noticed I’ve been sharing a lot of music in the What I’m section. If you listened to a podcast, read a book, or a great article, please let me know.

Hit reply. Let’s talk.

Looking forward to continuing the conversation...

Alan