Leave Me Alone I Am Fine

When your neural network tutorial makes more money on the "other" platform than YouTube. 🤔 Turns out the thirst for knowledge takes on a whole new meaning when it's hosted on Pornhub! $1000 vs $340 per million views? Guess we've all been uploading our algorithms to the wrong site this whole time. The real big brain move isn't optimizing your SEO—it's changing your video platform. And here I am, like an idiot, trying to monetize technical content on YouTube like some kind of peasant.

Corporate tech in a nutshell. Some executive burns through millions on AI "innovations" that are basically expensive tech demos destined for the graveyard. Meanwhile, the kid who'll inherit this mess someday is already recognizing the corporate cycle of wasted resources. The real kicker? Those hundreds of proof-of-concepts probably could've been one solid product if someone had just said "no" to the next shiny AI buzzword. But that wouldn't look good on the quarterly innovation report, would it?

The asylum of programming sins is now accepting new patients! Left to right, we have the poor soul who thought regex was a sensible XML parsing solution (narrator: it wasn't), the delusional dev who reinvented the wheel with a custom date/time library (because clearly, humanity hasn't solved that problem in the last 50 years), and finally—the pièce de résistance—the screaming maniac who blindly copy-pasted AI-generated "fixes" straight into production. The padded walls of this code asylum are the only things keeping these developers from harming themselves or others with more terrible technical decisions.

The hard pill that data scientists refuse to swallow! While everyone's obsessed with fancy neural networks and complex algorithms, the brutal reality is that garbage data produces garbage results, no matter how sophisticated your model is. It's like putting lipstick on a pig - your 17-layer deep learning architecture won't save you from the mess of unclean, biased data you're feeding it. The real heroes aren't the ones with the fanciest models but the poor souls who spend weeks cleaning datasets nobody will ever appreciate. Next time someone brags about their model's accuracy, ask them about their data preprocessing steps and watch them squirm!

The generational divide in tech has never been more savage! Old-timer dev with his magnificent beard is schooling these youngsters about the ancient art of coding without AI assistance. “ChatGPT? When I was your age I had to write my own code” hits different in 2024 when half of us are just prompt engineers now. It's like bragging about churning your own butter or hunting woolly mammoths. The irony? That senior probably copy-pasted from StackOverflow anyway. The tech cycle continues—today's juniors will someday lecture about the primitive days of having to type prompts instead of just thinking them.

The existential dread hits different when you realize all those hours grinding through algorithm puzzles were just feeding the beast that'll eventually replace you. Competitive programmers spent years optimizing solutions to the most obscure problems, only to discover they've been unwittingly training their silicon successors. The ultimate plot twist: your LeetCode grind wasn't preparing you for a job interview—it was preparing AI to ace it instead. Talk about creating your own replacement with extra steps.