If AI Learns From My Code, Doesn't It Mean My Job Is Safe?

So Linux developers looked at all the pressing issues they could solve—security vulnerabilities, driver compatibility, UI improvements—and decided "You know what the world really needs? A Flatpak app to un-pixelate adult videos." This is peak open source: someone had an itch, and by God, they scratched it. Three-star rating though, so I guess the algorithm still needs work. Meanwhile, I'm still waiting for my printer to work without sacrificing a goat.

The classic Schrodinger's AI paradox! That metronome perfectly captures the bipolar relationship developers have with generative AI. One minute you're watching it hallucinate that Python has a print_slowly() function, the next it's writing a perfectly optimized algorithm you couldn't dream up in a week of Red Bull-fueled coding sessions. The cognitive dissonance is real - simultaneously believing it's both useless garbage AND the technology that's going to automate us all into unemployment. The needle just violently swings between "why did I prompt this thing for 20 minutes when I could've coded it myself in 5?" and "holy recursive function Batman, it just solved my impossible edge case!"

Looks like someone's trying to stump ChatGPT with real-world physical tasks. Asking an AI to finish constructing a building is like asking me to fix production bugs without coffee – theoretically possible but practically insane. The construction worker's smug grin says it all – some jobs still require actual hands and a hard hat, not just clever algorithms. No matter how many tokens you feed the model, it's not going to pick up a hammer anytime soon. Next they'll be asking it to fix the office coffee machine or handle those awkward team-building exercises. Some nightmares even AI can't solve.

Someone's out here generating AI frappuccinos while the rest of us are still trying to justify $500 for 32GB of RAM to our managers. The irony is beautiful—we're burning through GPU cycles and cloud compute credits to create cute little coffee drinks, probably using more processing power than the Apollo moon landing, and somehow RAM prices are still stuck in 2021 scalper mode. Every AI enthusiast running Stable Diffusion locally knows the pain: your model needs 16GB VRAM minimum, your IDE wants 8GB, Chrome's eating another 12GB with those 47 tabs you swear you'll close later, and Docker containers are having a RAM buffet in the background. Meanwhile, someone's training models to generate aesthetically pleasing beverages. Priorities. The real kicker? Those AI frappuccinos probably consumed more electricity and memory than it would cost to just buy an actual frappuccino. But hey, at least they're cute.

Look at these peasants SPRINTING to ChatGPT while the door to actual knowledge stands wide open and COMPLETELY ABANDONED! Why learn binary trees when an AI can vomit code for you?! The absolute BETRAYAL of computer science fundamentals! Meanwhile, universities are still teaching sorting algorithms like it's 1995 and not like we're living in the AI APOCALYPSE. The data structures door might as well have cobwebs on it at this point!

The absolute DEVASTATION on that developer's face when they realize their entire career, years of education, blood, sweat, and debugging sessions... all reduced to typing "pls fix" into a chatbot. Meanwhile, Chad AI over here just casually solving problems like it's nothing, looking absolutely majestic while doing it. The existential crisis is REAL. We went from "10x engineers" to "please sir, may I have some code" in record time. The future is here, and it's weirdly polite and terrifyingly efficient.