Microsoft Took Our Jobs

Documentation: *exists* Developers: *immediately pull out the "I-don't-care-inator"* Let's be honest—reading documentation is like flossing. We all know we should do it, but somehow we'd rather blast it into oblivion and ask ChatGPT to explain that obscure method in five words or less. Ten years of experience has taught me that the time saved skipping docs is always paid back with interest during 3 AM debugging sessions. Yet here we are, finger hovering over the ChatGPT tab, ready to type "how to center a div" for the 500th time.

The modern developer dichotomy in its full glory! Up top we've got the polished, well-groomed developers who just copy-paste from Stack Overflow, Google search results, and ask ChatGPT to fix their bugs. Meanwhile, the documentation readers below look like they've been coding for 72 hours straight, sustained purely by Monster Energy and sheer determination. Reading docs is apparently the programming equivalent of staring into the void until the void stares back. The best part? Those documentation demons probably write better code than the rest of us combined. Choose your fighter: pretty but dependent, or unhinged but powerful.

You signed up for data science thinking you'd be building cool AI models and predicting the future, but NOPE—here you are, cramming optimization algorithms into your brain like it's finals week in calculus hell. Second-order optimization methods? Dynamic programming? Gradient descent variations? Girl, same. The existential crisis is REAL when you realize "fun with data" actually means memorizing mathematical nightmares that would make your high school math teacher weep with joy. Plot twist: nobody warned you that "data science" is just "applied mathematics with extra steps" in disguise. 📊💀

Someone just discovered AI and decided to use it for... checking if numbers are even. You know, that incredibly complex problem that's stumped humanity for centuries and definitely requires a large language model API call instead of a simple modulo operation. The first few rows show manual answers (No, Even, No, Yes) like a normal human would do it. Then row 8 hits and suddenly it's =GEMINI("Is this number even?",A8) all the way down. Someone's burning through their API quota to solve what could've been =MOD(A8,2)=0 . This is what happens when you have a hammer (AI) and everything looks like a nail. Next week they'll probably be using GPT-4 to add two numbers together. The cloud bills are gonna be *chef's kiss*.

Every VC pitch deck in 2023 summarized in one image. Those "build a full app in hours" AI DevAgent demos always skip the part where you spend three days debugging why your database connection keeps timing out or why CSS decided today was the day it would ignore gravity. Anyone who's shipped actual production code knows that "within hours" means "within hours... plus several weeks of fixing edge cases that the AI completely overlooked."

So you're sitting there watching AI models devour RAM like it's an all-you-can-eat buffet, and suddenly your perfectly adequate 800-dollar PC from last year is now basically a potato compared to the 18,000-dollar monstrosity you need to run ChatGPT's cousin locally. The stock market guy is standing there absolutely BEWILDERED because the laws of economics have been shattered—your PC didn't depreciate normally, it got OBLITERATED by the AI revolution. Remember when 16GB of RAM was considered "future-proof"? LMAO. Now you need 128GB just to run a medium-sized language model without your computer turning into a space heater. The AI bubble has single-handedly made everyone's hardware obsolete faster than you can say "but I just upgraded!" It's like watching your savings account evaporate in real-time, except it's your PC's relevance instead.