Bruh

Backend engineers getting distracted by shiny machine learning tech while production bugs silently judge them from behind. Tale as old as git. We all swear we'll fix that NullPointerException right after we finish this "quick" TensorFlow tutorial that's only been open in a browser tab for 47 days.

Ah, the classic corporate dilemma: "We need more engineers!" *proceeds to post job listings* while simultaneously a headline announces an AI that can supposedly replace them. The irony is delicious. Companies are still desperately hiring humans while breathlessly hyping the AI that will make us obsolete. Fifteen years in this industry and I've seen this movie before—neural networks, blockchain, quantum computing—all going to revolutionize everything... until they don't. Meanwhile, some poor hiring manager is still trying to find a senior dev with 10 years experience in a 3-year-old framework for entry-level pay. The circle of tech life continues.

So Michael Burry thinks trade jobs are "AI-proof" and uses Claude to do electrical work around his house. Then he drops the absolute bomb: "I am not so sure." The guy who predicted the 2008 housing crisis is now betting against the "AI won't replace blue-collar jobs" narrative. If an AI chatbot can guide someone through electrical work—a field requiring years of apprenticeship, code knowledge, and the ability to not die from 240V—what's stopping it from replacing actual electricians? The irony is chef's kiss: while using AI to do trade work, he realizes trade work might not be safe from AI. It's like watching someone discover they're standing on the thing they're about to short sell. The "Big Short 2026" format suggests we're heading toward another market collapse, except this time it's the job market getting wrecked by AI. Burry's track record of being catastrophically right about catastrophic things makes this extra unsettling. Time to learn underwater basket weaving—surely AI can't do that... right?

Someone discovered you can skip the entire computer science curriculum by copy-pasting transformer code from Hugging Face. Why waste years learning Python, data structures, algorithms, discrete math, calculus, and statistics when you can just import a pre-trained model and call it "AI engineering"? The escalator labeled "attention is all you need" (referencing the famous transformer paper) goes straight to the top while the stairs gather dust. Turns out the only prerequisite for a six-figure AI job is knowing how to pip install and having the confidence to say "I fine-tuned a model" in interviews.

Ah yes, the revolutionary AI integration strategy: squirting a tiny bit of machine learning onto a bar of legacy code and calling it "innovation." That soap dispenser is working exactly as intended – technically dispensing something, but completely missing the point. Just like how adding a chatbot that can only say "Have you tried turning it off and on again?" somehow justifies a 20% price increase. Investors impressed, users unimpressed, developers wondering if they should update their resume.