Ai

Years ago, something clicked when I read about Anthony Bourdain’s approach to feeding crowds. It was his stunt turkey technique, where he cooks an extra turkey the week before the actual event. It made me think about how we release software. It seemed absurd at first: why would you cook two turkeys for one dinner? Then I realized what he was really doing: load balancing across time. That extra turkey unlocks a cascade of optimizations that aren’t obvious until you think through the dependencies. Turkey stock made a week ahead means better gravy and more flavourful stuffing. It also means practice runs; most people only roast a turkey once or twice a year, so that stunt turkey is essentially a fire drill. Having stock and rendered fat ready lets you prep other components days in advance. Suddenly your Thanksgiving-day workflow changes from frantic juggling to orchestrated execution. ...

Remember autoconf? If you were building software in the late ’90s or early 2000s, you probably have scars. You’d write some configuration rules, run the tool, and out popped a perfectly functional makefile. It felt like magic, until it didn’t. The moment autoconf broke, you were debugging generated shell scripts that stretched for thousands of lines. The abstraction that seemed so elegant suddenly became opaque hell. You needed to understand not just what you wanted, but how the magic worked, where it could fail, and why. ...

I was debugging a power issue with my thermostat last week when it hit me: I had no idea how many batteries were in my house. Not approximately. Not even close. Twenty years ago, I knew exactly where every battery lived; the TV remote, the kitchen clock, maybe a flashlight. Today? They’re everywhere and nowhere. In sensors, in remotes, in devices I’ve forgotten I own. They’ve crossed the threshold from technology to invisible infrastructure. ...

We’ve been watching the AI gold rush unfold for the past two years now, and honestly? It’s giving me serious déjà vu. Remember the early days of mobile apps when everyone and their cousin was building a flashlight app? Or when “on the blockchain” was supposedly going to revolutionize everything from grocery shopping to dental records? We’re in that phase with AI right now. The phase where adding “AI-powered” to your deck is supposed to make VCs throw money at you. Where every developer with a weekend and an OpenAI API key thinks they’re building the next unicorn. Where demos that only work some of the time are being pitched as production-ready solutions. ...

I’ve been thinking about the current AI moment, and I can’t shake the feeling that we’re about to hit a wall. Not a failure wall, more like the wall Web 1.0 hit right before everything changed. Remember when every startup was “webr.com” and the height of innovation was animated GIFs? We’re in the AI equivalent of that era right now. Just as Web 2.0 wasn’t really about AJAX or rounded corners, AI 2.0 won’t be about better chatbots. We’re about to witness a fundamental shift in how AI gets built, deployed, and integrated into our daily tools. And honestly? It can’t come soon enough. ...