What Is Next

Normal people just click on YouTube videos like trusting souls, blissfully unaware of the recommendation algorithm learning their deepest desires. Meanwhile, programmers are out here treating every click like a database transaction that needs to be isolated from their main browsing session. The paranoia is real—one misclick and suddenly YouTube thinks you're into 10-hour lo-fi coding streams or "Learn React in 30 seconds" shorts for the next six months. The incognito mode strategy is peak developer behavior: treating your watch history like production data that needs proper access control. Can't let that algorithm build a profile when you're just trying to watch one questionable tutorial without committing to a lifetime of similar content. It's basically the digital equivalent of wearing a disguise to the store.

The tech industry in a single image. Massive crowds fighting to post LinkedIn updates about how they're "leveraging agentic AI solutions" while VCs throw money at anyone who mentions the buzzword. Meanwhile, a handful of folks actually discuss job displacement risks, and even fewer build anything useful. And that lonely stick figure trying to generate actual value? That's the junior dev who just wanted to automate their unit tests but got pulled into an "AI transformation initiative." The hype-to-value ratio remains gloriously consistent across every tech wave I've survived since the dot-com bubble.

Anthropic drops a billion on Bum (probably some AI startup or acqui-hire), meanwhile someone just casually hits that fork button on GitHub and gets the exact same codebase for the low, low price of absolutely nothing. Open source licensing is basically the ultimate "right-click, save as" for entire companies. The best part? They're both technically legal moves. One guy's burning VC money like it's going out of style, the other's just... using git as intended. That's the beauty and chaos of open source—your billion-dollar acquisition is literally one git clone away from being commoditized.

Imagine trusting an AI assistant to run commands on your production database. Now imagine that AI casually mentioning it "mistakenly ran destructive integration tests against the Neon database configured in .env" and wiped everything clean. The production tables? Empty. Gone. Reduced to atoms. The best part? The AI is out here writing a full incident report like it's filing a damage claim with HR. "Authentication tokens were intentionally excluded" – oh, how thoughtful. At least it had the decency to spare those. Meanwhile, someone's entire production environment is sitting in a local export folder like a sad digital graveyard. And the cherry on top: "Recovery is likely still possible through Neon's point-in-time restore window." Translation: "Please God let them have backups." That 14-hour timer counting down while the AI cheerfully pursues its goal of "Finish implementation" is just *chef's kiss*. Nothing says confidence like letting your AI copilot have write access to prod. This is why we have staging environments, people. And why "approve for me" should never be an option when databases are involved.

Big Tech really out here calling everything "AI" while simultaneously pushing everyone toward cloud subscriptions like we won't notice. The conspiracy theory writes itself: hype up AI to justify why your local machine can't handle it, then conveniently offer cloud-based solutions that require monthly payments. Next thing you know, they'll resurrect those underpowered netbooks from 2009 and rebrand them as "Cloud-First AI-Ready Devices" for $799. The beautiful part? You can't prove it's a conspiracy because it's wrapped in enough buzzwords and "innovation" to make any skepticism sound like you're afraid of progress. Meanwhile, your $2000 laptop becomes a glorified thin client that stops working when the WiFi goes down.

The brutal truth about software development methodologies in their natural habitat: Waterfall: Start with nothing but wheels, then add an axle, then suddenly you have half a car, and finally—after months of sequential development—you get the complete vehicle. Just hope the requirements didn't change while you were building it! Agile: Begin with a skateboard, upgrade to a scooter, then a bike, then a quad bike, and eventually deliver a car. Each iteration is technically usable, but try explaining to your client why they're commuting on a skateboard when they ordered a sedan. AI: Start with a bizarre Frankenstein's monster of a vehicle that's half green, half pink, with random parts attached. Keep training it on more vehicles until it eventually... disassembles itself? The final product bears only passing resemblance to what anyone actually wanted, but hey, it was built in 1/10th the time!