Garbage In, Garbage Out: The GitHub Roast

Ah, the classic "sleeping peacefully until cloud costs jolt you awake" nightmare! This cat sleeps through earthquakes, thunderstorms, and even alien attacks, but shoots wide awake in pure terror when remembering there's a forgotten cloud instance still running somewhere, silently draining your bank account at $0.25/hour. Nothing triggers fight-or-flight response in a developer quite like realizing you spun up that "temporary" GPU instance three weeks ago and forgot to shut it down. That sudden 3am realization is scarier than any horror movie!

Foreign intelligence agencies are having their easiest day ever. Nothing says "career suicide" quite like uploading Department of Defense codebase to a random AI app with a blue whale logo. The intern's about to learn why security clearances exist and why "helpful" free apps are sometimes just fancy honeypots. Next week's headline: "Former intern seeks asylum in country with no extradition treaty."

The stack of support holding up our broken code is too real! Your janky codebase is somehow balanced on a precarious tower of AI suggestions, desperate Google searches, StackOverflow copy-pasta, that one tutorial from an Indian guy with 240p video quality but god-tier explanations, ancient Git repositories nobody's touched since 2013, and pure dumb luck. The dog (your code) has absolutely no business standing on that wobbly pile, yet somehow it works! Every developer knows that touching ANY part of this fragile ecosystem might send the whole thing crashing down. The compiler isn't impressed, but hey—ship it anyway!

Ah yes, the mythical "real programmer" – that elusive creature who apparently codes everything from scratch using nothing but pure brain power and cosmic vibes. Meanwhile, in reality, the rest of us mortals are over here frantically Googling syntax, copying from Stack Overflow, and begging AI to fix our broken code at 3 AM. The gatekeeping is strong with this one! Next thing you'll tell me "real programmers" only code on punchcards while standing barefoot in the snow, uphill both ways.

Looks like GitHub Copilot just went full 1950s mode! Two functions side by side: one for men that returns the salary unchanged, and another for women that returns 90% of the input. Copilot didn't just write code—it accidentally coded up the gender pay gap! This is what happens when your AI learns from historical data without an ethics class. The machine isn't biased... it just perfectly mirrors our messed-up world. Maybe the next update should include a "modern society" plugin.

The four stages of training an AI model, as experienced by every data scientist who's ever lived: First panel: Innocent optimism. "Training time!" Oh, you sweet summer child. Second panel: Desperate pleading. "C'MON LEARN FASTER" while staring at that pathetic learning curve that's flatter than the Earth according to conspiracy theorists. Third panel: The error messages. Just endless red text that might as well be hieroglyphics. *SIGH* indeed. Fourth panel: Complete surrender. "3, 6, 2!!!" *shoots model* "I'LL GO GET THE NEXT ONE." Because nothing says machine learning like throwing away hours of work and starting from scratch for the fifth time today. The real joke is that we keep doing this voluntarily. For money. And sometimes fun?