Just Give Us The Extension

The corporate tech evolution in one image! On the left, we have Steve Ballmer's infamous sweaty "DEVELOPERS!" chant from 2000—back when human coders were the golden ticket to success. Fast forward to 2023, and CEOs are now calmly announcing how AI will "revolutionize our lives" while simultaneously telling HR to fire thousands of the same developers they once desperately needed. The tech industry's relationship status with developers: "It's complicated." Yesterday's rockstars are today's budget line items. Nothing says "thanks for building our trillion-dollar empires" quite like being replaced by the very tools you created.

The iceberg of AI terror is real, folks! On the surface, it's just "AI" - those fancy chatbots everyone's talking about. Dive a bit deeper and you hit "Machine Learning" where your code starts making decisions without you explicitly telling it how. But the true horror? That murky "Deep Learning" zone where neural networks do their black magic. And what's holding this entire technological monstrosity together? Some poor developer's spaghetti Python code and linear algebra that they barely remember from college. The whole industry is basically running on StackOverflow answers and caffeine. Next time someone says they "work in AI," remember they're just the tip of an iceberg floating on a sea of mathematical duct tape and prayer.

Chrome tabs and AI models - the two horsemen of RAM apocalypse. ChatGPT casually using 13.8 GB of memory like it's nothing, while your computer quietly weeps. Remember when we thought 4GB was excessive? Now our browsers are out here consuming memory like tech bros at an all-you-can-eat buffet. Your PC isn't running an AI assistant - it's financing its therapy sessions.

Sorting imports by character length instead of alphabetically or by module type? That's like organizing your sock drawer by how much each sock weighs. Sure, it looks oddly satisfying with that gradient effect, but your code reviewer is probably drafting your performance review right now. The real horror isn't the sorting method – it's that you're importing both matplotlib AND sklearn in the same file. That poor memory usage never stood a chance.

Ah, the eternal developer paradox. When someone shows us AI-generated code, we instantly recognize it as a tangled mess of bugs and questionable design choices. "This is brilliant," we say with thinly veiled sarcasm. But then there's our own code—equally disastrous, probably held together with duct tape and prayers—and somehow we're irrationally attached to it. "But I like this." It's like criticizing someone else's kid for being messy while your own demon spawn is literally setting the house on fire. The cognitive dissonance is strong in this profession.

The eternal management fantasy: someone built an entire system in 2 days using GPT-4! Meanwhile, you're sitting there knowing it would take weeks of actual coding, testing, and debugging to make anything remotely production-ready. But sure, let's pretend AI can magically "vibe code" complex systems while ignoring all those pesky details like security, edge cases, and technical debt. Next they'll be asking why you can't just "GPT" the entire codebase over the weekend for free. Bonus points if they use the phrase "it's just a simple feature" while explaining their impossible timeline!