Sorry Gamers, AI Called Dibs

GASP! The AUDACITY of developers thinking they can hide behind AI! 💅 When you run git blame to find out which MONSTER broke the code, it reveals the actual HUMAN criminal - not GitHub Copilot! Your AI assistant isn't taking the fall for your disaster of a commit, sweetie! That's right, your name is PERMANENTLY etched in the git history hall of shame! There's no escaping accountability in this dystopian developer hellscape!

Ah, the modern tech hero's journey: "I wrote a prompt, AI generated an API, and now I'm basically the next unicorn founder." Sure buddy, and I once wrote a regex that worked on the first try – doesn't mean I'm Jeff Bezos. The gap between "my AI prompt worked once" and "billion-dollar company" is roughly the same as the gap between "I installed Linux" and "I now run NASA." Those compute bills will hit harder than the reality that prompt engineering isn't the same as actually engineering. Ten years in the trenches and I've learned one truth: the harder someone humble-brags about how easy something was, the more spectacularly it'll explode in production.

That moment when it hits you—your entire coding career has been reduced to "vibes" since ChatGPT arrived. No more grinding through Stack Overflow at 3 AM; now it's just "Hey AI, fix this mess" and hoping for the best. Your carefully cultivated programming skills? Just expensive intuition for prompting. Your CS degree? Just fancy paper to frame next to your "I used to write my own code" participation trophy.

When you dive into machine learning without understanding the fundamentals, things go sideways real quick. Poor Hulk thought he'd build a sophisticated image recognition system, but ended up with code so broken it's just spitting out random numbers. It's the classic journey from "I'll just follow this tutorial" to "why is my neural network predicting that cats are submarines?" The tears are real – we've all been there, staring at our monitor at 2AM wondering how our brilliant AI project turned into digital soup. Machine learning: expectation vs reality in its purest form.

Every decade brings a new "revolutionary" way to make developers obsolete, yet here we are, still debugging at 3 AM. Visual Programming in the '90s promised drag-and-drop salvation, MDA in the 2000s swore models would auto-generate everything, No-Code platforms in the 2010s claimed anyone could build apps without writing a line. Now we've got "Vibe-Code" where you just describe what you want and AI does the heavy lifting. Spoiler alert: someone still needs to fix it when the AI hallucinates a database schema or generates a sorting algorithm that runs in O(n!). The pattern is clear—each generation thinks they've cracked the code to eliminate coding itself. Meanwhile, programmers keep getting paid to clean up the mess these "solutions" create. Job security through eternal optimism, baby.

The classic boardroom meeting where everyone gets to play the blame game for tech layoffs. First guy immediately points at AI because his JavaScript skills are now worth about as much as a Blockbuster gift card. Middle person blames foreigners because obviously someone in Bangalore stole their job and not their inability to learn anything past jQuery. Only the third person mentions actual economic factors while getting yeeted out the window for bringing reality into a tech conversation. Turns out the industry doesn't want solutions—just convenient scapegoats that don't require updating your resume or learning Rust.