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The AI That Saved $25 Million a Year and Couldn’t Save the Company That Built It

The story of XCON, the first commercially successful expert system — and what its triumph and its company’s collapse can teach every builder about the difference between solving a problem and leading an organization.

A company drowning in its own success

In 1978, Digital Equipment Corporation had a problem that was, in a strange way, the best kind of problem to have. They were selling too many computers and couldn’t keep up.

DEC — the second-largest computer company in the world, behind only IBM — built the VAX, a family of powerful minicomputers that businesses could customize to their specific needs. The selling point was the customization: each VAX system was configured from thousands of individual components — processors, memory modules, disk drives, controllers, cables, cabinets, power supplies — assembled into a unique combination tailored to what the customer ordered.

The problem was that configuring these systems required deep technical expertise, and even the experts got it wrong. A lot. If a customer ordered a disk drive, someone had to make sure the order also included the right disk controller, the right cables, the right power supply for the additional load, and the right cabinet space to house it all. A single VAX system could involve thousands of separate components, and the relationships between them were complex, interdependent, and poorly documented. Human configurators were getting orders wrong somewhere between 30 and 40 percent of the time. Wrong components shipped. Incompatible parts arrived at the customer site. Systems that should have worked didn’t. The manual configuration process was taking ten to fifteen weeks per order. DEC was hemorrhaging money on returns, rework, and angry customers — and the more systems they sold, the worse the problem got.

Into this mess walked a researcher from Carnegie Mellon University named John McDermott.

Five Thousand Years to Get Here

A brief history of every tool humanity ever built to teach its children — and the one that finally broke the pattern.

By D.W. Denney

Every tool on the same curve

I want to tell you a story that covers five thousand years and fits on the back of a napkin. It’s the story of every educational technology humanity has ever invented, and the punchline is that until very recently, they were all doing the same thing.

Here’s the napkin version. Somebody knows something. They need to get it into somebody else’s head. Every tool we’ve ever built for that purpose — every single one, across all of recorded history — has been a more efficient way to do one of four things: store information, distribute information, drill information into memory, or assess whether the information stuck. That’s it. Four functions. Five millennia. One curve.

Let me walk you through the timeline, and watch how the technology changes while the function doesn’t.

Oral tradition. Before writing, knowledge lived in the mouths of elders and was transferred by speech. The teacher spoke. The student listened, repeated, and memorized. If the elder died before the transfer was complete, the knowledge died with them. The storage medium was the human brain. The distribution method was the human voice. The range was the distance sound carries across a campfire. This worked, and it worked for a long time, and the stories and songs and genealogies that survived this era are a testament to how powerful the human memory can be when it has no other option. But the system was fragile. One forgotten line, one dead elder, one scattered tribe, and the knowledge was gone.

Beyond the Bullet Point List

How Cognitive Science and Neurodiversity Research Should Reshape the Way We Teach Complex Ideas

Open almost any online course, corporate training module, or educational slide deck in 2026 and you will find the same default gesture: dense content broken into bullet points. The bullet is the visual idiom of modern learning design. It signals clarity. It promises ease. For many of us, it is the first formatting move we make when a paragraph starts to feel “too long.”

Yet decades of cognitive science suggest that this default is often wrong — not slightly wrong, but consequentially wrong for the kinds of learning we say we care about most. The bullet is excellent at one thing (quick reference) and poor at something else entirely (building durable understanding of connected ideas). When we confuse these two goals, we produce materials that feel educational while failing to educate.

This article makes the case, from the research literature, for a more careful approach to formatting complex material — one that treats format not as decoration but as a cognitive variable that directly shapes what learners take away. We will look at what working memory can and cannot do, why prose and bullets operate on different cognitive systems, and what research on neurodivergent learners reveals about a common but mistaken assumption: that fragmenting information is always an act of accessibility. The truth, as is so often the case, is more interesting than the folk wisdom.

The Healing in the Headset

What the research actually says about virtual communities and mental health — and why the therapeutic power of virtual belonging turns out to be more real than most people expected.

A thing you already know but might not have words for

If you’ve ever spent real time in a virtual community — not just passing through, but actually living there, building things, forming relationships, coming back night after night to the same group of people — you already know something that the clinical research is only now catching up to. You know that the connections you formed in that space were real. You know that the support you received there mattered. You know that the person who stayed up until 2 AM talking you through a bad night wasn’t less of a friend because you’d never shaken their hand.

You also know that if you said any of this out loud to certain people, they’d look at you like you were describing an addiction. “You should get off the computer and make real friends,” they’d say. “Those aren’t real relationships.” And maybe you nodded, because the cultural script says they’re right, even though something inside you knew they were wrong.

The research says you were right and the script was wrong. Not in every case, not without nuance, and not without some genuine risks that are worth being honest about — but in ways that are documented, measured, and increasingly well-understood. Virtual communities are producing real therapeutic outcomes for real people, in populations that desperately need them. I want to walk you through four of the documented areas, because if you’re going to build virtual worlds, you need to understand that the spaces you create may end up being, for some of your users, the most important support system in their lives.

That’s a weight worth carrying carefully.

Why Your Virtual Village Feels Like Home

The science of why people grieve when their Minecraft house burns down, trade favors with strangers they’ve never met in person, and develop inside jokes about things that never happened in the real world.

A house that isn’t there

Let me tell you about something that happens all the time and that almost nobody takes seriously. Somebody builds a house in a video game. A digital structure, made of digital blocks, sitting on a digital plot of land that exists only as data on a server somewhere. They spend hours on it — maybe weeks. They choose the materials carefully. They place the windows where the light comes in right. They build a little garden out back, because the garden makes it feel complete. The house is not real. It cannot be lived in. It has no value on any market that deals in physical objects.

And when somebody griefs it — when some other player comes along and burns it down or blows it up for laughs — the person who built it feels a surge of anger and loss that is, by any honest measure, real. Not metaphorical. Not exaggerated. The feeling is genuinely comparable, in both quality and intensity, to the feeling of having something physical vandalized. They feel violated. They feel robbed. Some of them log off and don’t come back.

Every experienced gamer knows this. Most people outside of gaming dismiss it. But there is a growing body of research in psychology, neuroscience, and behavioral economics that says the gamers are right and the dismissers are wrong — and that the feelings people develop about virtual places, virtual objects, and virtual communities are not pale imitations of “real” feelings. They are the same feelings, running on the same psychological machinery, triggered by the same mechanisms. The virtual village feels like home because your brain is using the same hardware to process it that it uses to process your actual home.

I want to walk you through four pieces of that research, because they map almost perfectly onto four dynamics that make virtual communities work. And if you’re somebody who designs virtual worlds for a living — or wants to — understanding these dynamics is not optional. They are the difference between building a world people visit and building a world people belong to.

The Four Pillars of a Mind

A scholarly look at why memory, personality, emotional intelligence, and motivation are the four things that make a character — or a person — feel real. And what cognitive science has to say about each of them.

The tavern keeper problem

Picture two tavern keepers. Both are characters in a game you’re playing, or in a novel you’re reading, or in an immersive world you’ve been invited to spend time in. Both pour you a drink, both take your coin, both say hello when you walk in.

The first one does nothing else. Every time you walk into the tavern, she gives you the same greeting. She doesn’t remember you. She doesn’t react to whether you saved her village last week or betrayed it. She has no opinions about the weather, no complaints about her back, no idea that the barrel of ale in the corner is cursed. She is, functionally, a vending machine for drinks wearing a person-shaped costume.

The second tavern keeper is also a character. Also pours drinks, also takes coin, also says hello. But she remembers that you helped her daughter recover from the fever six months ago, and her greeting is warmer because of it. She’s naturally cautious — when you ask about the cursed barrel, she weighs the question for a moment before answering, the way a cautious person would. She notices that you look tired tonight and pours you something a little stronger without being asked. And she wants something for herself, too, underneath all of this — she’s been saving up to buy out her brother-in-law’s share of the tavern, because she thinks she could run it better alone, and that ambition colors everything she does.

You know which tavern keeper is the memorable one. You also know which one is more expensive and time-consuming to build, whether you’re writing her as a novelist, scripting her as a game designer, or configuring her as an AI system. The question I want to walk through in this post is why. Why does the second one feel like a person and the first one doesn’t? What are the specific ingredients that have to be present for a character to cross the line from puppet into presence?

The answer, it turns out, is that there are exactly four of them. And they are not a designer’s preference. They correspond to four dimensions that cognitive scientists have been studying in humans for the last fifty years — four specific things the human mind uses to recognize another mind as being real. When you design a character who has all four, you’re not faking personhood. You are activating the parts of your audience’s brain that are already wired to respond to personhood, and those parts don’t care whether what’s in front of them is digital, printed, or physical.

I call these the Four Pillars. Let me walk you through each one, and the research that makes each of them load-bearing.

Always On

On what we already know about minds that never look away — and what it might mean to wear the screen on your face.

A different kind of question

The first three posts in this series were about things we can measure. Eye strain, with tens of thousands of subjects across decades of optometry research. Inattentional blindness, with controlled studies in driving simulators and flight cockpits. Pedestrian deaths, with police accident reports and peer-reviewed papers. All of that is real. All of that is solid ground.

This last post is going to walk us off the solid ground a little, and I want to be honest about that up front. The question of what happens when augmented reality moves from a thing you sometimes use to a thing you always wear is, as of this writing, an open question. The glasses are not yet ubiquitous. The contact lenses don’t exist yet. The data set we’d need to answer the big version of the question hasn’t been collected, because the experiment hasn’t been run on a big enough population for long enough.

So I’m not going to make predictions. I’m not going to tell you what AR glasses are going to do to society in 2035. I have no idea, and anybody who tells you they do is selling you something. What I’m going to do instead is something a little sneakier and a lot more honest: I’m going to walk you through what we already know about what phones have done to human attention, memory, and presence — because phones are basically AR glasses that haven’t quite made it onto your face yet, and the research on phones is a lot further along than the research on glasses. Then I’ll let you do the math.

The Gorilla You Didn’t See

On attention, AR, and the strange truth that more information in your field of view often means less awareness of the world.

A famous experiment, in case you haven’t seen it

Sometime around 1999, two psychologists named Daniel Simons and Christopher Chabris ran an experiment that has since become one of the most famous demonstrations in cognitive science. They filmed a short video of six people in a room passing two basketballs back and forth — three players in white shirts, three in black. They asked viewers a simple question: count how many times the players in white shirts pass the ball.

Most people watch the video carefully, count the passes, and report a number — usually correct. Then the experimenters ask: did you see the gorilla?

The viewers stare at them. What gorilla?

They play the video again. About thirty seconds in, a person in a full gorilla suit walks into the middle of the frame, stops, faces the camera, beats their chest, and walks off the other side. The gorilla is on screen for a full nine seconds. It is not subtle. It is not hidden. It is, by any normal measure, the most interesting thing in the video.

And about half of all viewers, on the first watch, do not see it at all.

This effect has a name. It’s called inattentional blindness, and once you know about it, it changes how you think about pretty much every visual interface you’ve ever used. Including, very specifically, augmented reality.

Your Eyes Were Not Built For This

The physical cost of putting a digital layer in front of your face — and why the most exciting thing about AR is also the part nobody’s solved yet.

A weird little experiment you can try right now

Hold your finger up about six inches from your face and look at it. Really look at it — focus on the fingerprint, the little ridges, the half-moon at the base of your nail. Now, without moving your finger, shift your focus past it to something across the room. A doorway. A window. Watch what happens to your finger. It splits into two ghostly versions of itself, blurred and translucent, while the doorway snaps into clarity.

Now do the reverse. Focus on the doorway. The doorway is sharp; your finger is a fuzzy double-image. Switch back. Doorway blurs, finger sharpens. Switch again.

What you just did is two things at once, and your brain handled them so smoothly you probably never noticed. Your eyeballs physically rotated inward and outward to point at the right depth — that’s called vergence. And the lenses inside your eyes physically squished and stretched to focus at the right distance — that’s called accommodation. Your visual system has been doing these two things together, in perfect lockstep, since you were a few months old. They are so tightly coupled that neuroscientists don’t really treat them as two separate systems anymore. They’re one system with two outputs, and the outputs always agree with each other, because in the natural world they always have to agree.

I’m telling you about this because in the last few years, humanity invented a way to make them disagree. And then we strapped that thing to our faces and called it the future.

Where Two Worlds Become One: Building a Browser-Based Mixed Reality Tool for Education

By Donald Denney | Realm Forge Academy

There’s a moment in every emerging technology’s lifecycle when it crosses over from novelty to necessity. For mixed reality, that moment is now — and it’s happening inside web browsers.

As part of the Realm Forge Academy course Defining a New Reality: Enter the Metaverse, I’ve built a browser-based mixed reality tool that lets students use their device camera to detect a flat surface in their physical environment and place a 3D avatar into a fixed position in the real world. No app store. No headset. Just a browser and curiosity.

[Image: Screenshot of the MR tool detecting a surface and placing an avatar]