Forget the hype, the frameworks, and the “AI roadmaps.” Here’s what actually works. Let’s get this out of the way: most AI “strategies” are theater. Decks. Demos. Buzzwords wrapped in billable hours. You’ve seen it. A consultant rolls in with a 70-slide presentation full of “maturity matrices” and “transformation frameworks.” They talk about aligning AI to business objectives, governance layers, and something-something operational synergy. And yet—three months later, your tea

Somewhere between a vending machine in Anthropic’s lobby and a meme painted on a Memphis rooftop, capitalism quietly booted up a new operating system. We used to say “AI is coming for your job.”Now it’s coming for your org chart. The Dawn of Machine Capitalism Let’s start with a vending machine.A simple, stupid, beautiful vending machine. Anon Labs gave an AI $500 and said, “Go make a profit. ” No human babysitter. No preloaded logic tree. Just a digital brain, an API key, an

Somewhere along the line, the culture shifted. We stopped pretending. For decades, success was about the illusion of control. The polished pitch deck. The glossy commercial. The polished founder who never broke a sweat — even when everything was on fire behind the scenes. That’s the “fake it till you make it” era.And it’s over. Because right now, we’re watching something wild happen across the entire digital landscape: the rise of the Build-in-Public crowd — the people who ar

A while back, I wrote about The Meaning Economy  — the idea that as AI and automation steadily absorb traditional labor, the next wave of value creation won’t come from what we do for a living , but from what we create, express, and share  as humans. That idea felt theoretical at the time — but now we’re starting to see the first real-world on-ramps appear. One of the clearest? Tech storytelling. The Human Layer That Machines Can’t Replace Across industries — politics, media,

And why AI might finally slow us back down. There was a time when running a process meant you could go make a sandwich. Back in the day, computing was slow. You’d start a program, watch the progress bar crawl, maybe hear the hard drive click like a heartbeat, and then… you waited. Compiling code? Go grab lunch. Rendering a video? See you in the morning. Early computing was a Zen garden of patience and progress wheels. Then we got impatient.We wanted faster chips, shorter wait

There’s a feel to precision—the instant a mechanism locks into place and the world goes quiet for half a second.Right before that click, though, there’s the glide: friction drops, alignment happens, inevitability hums. That’s where we are with quantum. The parts are lining up, the resistance is gone, and you can almost feel the system seat itself. History Has a Rhythm Every so often we get a cycle big enough to reset the world.They’re far enough apart that we forget what they

You ever notice how every era has its buzzword bullshit? Like, back in the day, every computer was bragging about its clock speed. “1.4 gigahertz!” “2.0 gigahertz!” It was the language of power. Nobody actually knew what it meant, but it had a number, and bigger numbers meant better computers, right? Same with RAM. Same with hard drives. Same with every tech label we could slap on a box. “Intel Inside” was practically gospel — and it didn’t matter if anyone understood it. Mar

I just got back from a data conference in Chicago, and I left honestly stunned. Not by the technology — by the people. Panel after panel, supposedly “leaders” in data science, logistics, and analytics — all of them dancing around the same idea: “We’re being cautious about AI.” Cautious. That word kept coming up like a reflex, a corporate mantra. “We’re waiting for regulation.” “We’re concerned about bias.” “We don’t trust the outputs.” It was like watching a room full of data

It used to be the one with the title. The corner office. The authority. Not anymore. Today, the most dangerous person in any room isn’t chasing applause, approval, or perception. They’re the one sitting quietly in the back — calm, confident, and completely underestimated — because they’re running a system in their head no one else can see. That’s operational power — and it’s rewriting everything you think you know about hierarchy, influence, and control. The Old Game: Power T

This all started with a phone call. An old friend of mine, Boris — a fellow IBM alum and one of the few people who still remembers what IRQ conflicts felt like — called me out of the blue a few weeks back. He had a question about AI. Simple enough. But if you’ve ever talked to two lifelong tech guys, you know how that goes. Five minutes in, we were no longer talking about AI — we were talking about everything that led to AI . We fell straight down the nostalgia rabbit hole: A

Let’s start with a truth that’s equal parts uncomfortable and undeniable: If you’ve got deep expertise in anything  — consulting, medicine, engineering, marketing, welding, whatever — you’re training your replacement right now. And no, not the human one. The AI one. Projects like Argentum  (Bloomberg’s scoop about hundreds of ex-McKinsey, Bain, and BCG consultants training AI to do entry-level consulting) and Project Mercury  (ex-bankers teaching financial modeling to models)

Let’s be honest—process mapping used to suck. It was the equivalent of eating your vegetables before you could touch the steak. Necessary? Sure. Fun? Not remotely. Whether it was defining database structures before writing a single line of code, or sketching out user journeys before building an app, process mapping always felt like the preamble to the “real” work. But here’s the thing: it was always the most important part. If you've ever written a business plan, mapped out a

Let me tell you something strange: We don’t know how to build the Space Shuttle anymore. NASA had the plans. The blueprints. The specs.What they didn’t have was the team —the network of minds, habits, and shared mental models that made it all work. That knowledge didn’t live in one document. It lived in hallway conversations. In hand gestures. In intuition built through repetition and failure. When those engineers retired or moved on, the Shuttle didn’t just become obsolete.

There’s a hard truth nobody wants to say out loud: if you’re not adapting to modern tools — if you’re not using AI, automating your workflows, or streamlining with the tech that’s already freely available — you are the problem. Not the market. Not the system. You. We’re living in an adapt or die  era. Technology isn’t creeping forward anymore — it’s sprinting. AI has hit escape velocity. What used to take teams of people and days of work can now be done in minutes. For free.

If you’ve been on the internet in the last 48 hours, you’ve probably seen that  photo — a massive white-roofed facility in Memphis with MACROHARD  painted across it in letters so huge you can literally see them from space. And of course, it came straight from Elon Musk’s X account. Classic Elon: half-joke, half-omen, and somehow both at the same time. This is the same man who named a car line “S3XY,” sent a sports car into orbit, and made flamethrowers a consumer product. So

Let’s be clear: the cloud isn’t dying. But the age of unquestioned cloud supremacy  — that decade-long reign where every ounce of intelligence had to pass through someone else’s API — that’s beginning to crack. We’re entering the post-imperial  phase of compute. The Great Inversion For twenty years, the cloud has been the empire of cognition: centralized, industrial, and rented by the teraflop. It made sense. The economics of scale were brutal. Training frontier models requir

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