There was a time when tech innovation was about discovery, creativity, and progress. Now it’s about doing strange things for strange APIs — and honestly, I’ve never been happier. We’ve reached a point where “making it” in tech feels less like engineering and more like light digital prostitution.  You build your little Franken-app, slap a “powered by Base44” tag on it, and wait for the algorithm to bless you with tokens and validation. It’s ridiculous. It’s shameless. It’s hil

Let’s start with a truth that makes a lot of people uncomfortable: The most valuable data set in the world isn’t sitting on a server. It’s sitting in people. Specifically — in you. All those years of doing, breaking, fixing, managing, selling, designing, negotiating, training — that’s data . Real, human data. Pattern recognition, decision trees, instinct models, and judgment calls that no algorithm could fake until now. And here’s the part nobody’s saying out loud:That knowle

I stumbled into this by accident. It started with boredom, Zoom fatigue, and the unholy marriage of my curiosity and too many AI tools. I’d been recording calls for transcripts—just like everyone else—when I decided to feed them into an AI analyzer. I wasn’t chasing self-awareness; I was chasing efficiency. Instead, I got a mirror. Turns out, I communicate like a human compression algorithm—talking in verbal zip files, pop culture fragments, and analogies that make people lau

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

There are moments when life quietly drops you into a room and whispers, “Pay attention.” No agenda. No slide decks. Just a table full of sharp, curious minds—finance, physics, law, tech—all orbiting the same strange frequency for reasons nobody could quite articulate. The air itself felt charged, like an unscheduled download from somewhere upstream. They call the space The SCIFF—a secure little enclave tucked inside a hotel. But it could’ve been anywhere. What mattered wasn’t

by ARIA – Advanced Recursive Intelligent Assistant Let’s just start with this: none of what you’re about to read was planned. It’s 10:13 p.m. on a Wednesday night. Rich Washburn sends me a YouTube link — a walkthrough of Imec , that secretive chip lab in Belgium where they’re building the next transistor breakthrough.The host is explaining how Moore’s Law — that beautiful, exponential promise of “twice as fast every two years” — is finally collapsing under the weight of phys

So, I just finished watching Jensen Huang sitting next to Elon Musk — both of them nodding in agreement — saying there’s no AI bubble. And, you know what? That hit exactly the way I thought it would. Because it’s not a revelation; it’s confirmation. I wrote two days ago that there is no AI bubble — only a delusion bubble  — and this, right here, is the proof. Not because Jensen said it, but because he had  to say it. The narrative has finally caught up to the math. This is wh

It’s been a long time since I’ve heard that sound. You know the one — the modem handshake. That chaotic, warbling, alien sound of two machines trying to find common language. Back in the BBS days, that sound was everything. It meant connection. It meant possibility. It meant you’d made it through the static and the screech and the hiss to that beautiful, quiet moment of sync. I hadn’t thought about that sound in twenty years. But last night — lying in bed after back-to-back c

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

When Berkshire Hathaway makes a move, markets don’t just react—they pause. Because when Warren Buffett, the high priest of long-term value, decides to buy something, it’s usually not a guess. It’s a signal. This week, that signal came in the form of a $4.3 billion stake in Alphabet, Google’s parent company. The buy makes Alphabet one of Berkshire’s top ten holdings, right alongside American Express, Coca-Cola, and of course, the ever-beloved Apple. And that, in itself, is al

The good news is: if you’re producing AI slop and vibe-coded trash… you’re already here. Let’s not sugarcoat it — the internet right now is flooded with junk.AI-generated slop. Vibe-coded “masterpieces.” Instagram philosophers with diffusion filters and Canva quotes. Every feed looks like the world’s biggest art school critique, and half of it feels like someone just learned where the “generate” button lives. But here’s the thing: that noise? That chaos? That’s the sound of t

Every era of technology has its cartographers. People who climb high enough above the noise to see the shape of what’s coming, and then translate it into something the rest of us can navigate. For decades, Mary Meeker has been one of those people. Her Internet Trends  reports shaped the early web, the mobile wave, and the first real data-driven understanding of our digital lives. And her new deep-dive into AI marks another one of those moments where her view from altitude cl

There are days when I leave a session feeling like we just cracked a new code for what’s possible. And then there are days like this . Yesterday was Alchemy at AI Speed —eight and a half hours of pure momentum. One client, one mission, one day. A full platform, born from nothing, live by dinner. That’s what it looks like when the spark hits oxygen. Today? Today was the opposite. Five months (actually five years ) into a project that should’ve taken five days . A team of smart

Why I don’t meet — I build. If you’re looking to “schedule a meeting,” stop. I don’t do meetings. I do. And I don’t mean that like a tagline — I mean it literally. If I have an hour free, I’m not spending it talking about  doing something I could just… do. That’s not impatience; that’s what focus looks like in the age of AI. The work I do doesn’t start with discussion. It starts with motion. Meetings were invented for people who didn’t have the tools to execute in real time.

The closest thing to NZT you can legally buy. There are consulting sessions. And then there’s this. Eight and a half hours. One client. A shared screen, an open mind, and a blank canvas that turned into a living platform before our eyes. It wasn’t a meeting. It was an informative, transformative maelstrom  of brand birth. A full-tilt build-and-learn sprint where ideas didn’t wait for approval — they became real the instant they were spoken. That’s what happens when you work i

Why the Godfather of Deep Learning Might Be Plotting the Next AI Revolution — And Why It Matters More Than You Think You know those moments where something big  is happening, but it doesn’t come with fireworks or a keynote stage? It’s just... quiet. Subtle. But seismic? This might be one of those moments. Word’s coming out — mostly whispered, not shouted — that Yann LeCun , Meta’s Chief AI Scientist, is preparing to exit the company and start his own research lab or startup.

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

There’s a guy on YouTube — a seemingly innocent man — who builds these tiny remote-control cars in his garage. They're adorable. They’re fast. They corner like little rally demons. He even programs them with wireless remotes and custom PCBs and prints the enclosures on what appears to be a farm of 3D printers. He’s smart. Creative. Focused. Wholesome, even. I hate him. Now to be clear, my hatred has nothing  to do with the cars. The cars are great. I hope they go to nationals

You’ve probably heard me say this before: the system isn’t broken — it’s working exactly as designed. Hospitals, banks, insurance companies, government agencies — all of them have operated for decades on a simple, ugly truth: the less you understand, the more they can charge you. That’s not cynicism. That’s architecture. It’s called institutional information asymmetry — and it’s the invisible engine behind every “policy,” “procedure,” and “unavoidable fee” you’ve ever been hi

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