People In The US, Probably…

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!

So AI already brutally murdered RAM and is currently swinging at RAM's poor cousin (Crucial brand, nice touch). But wait—there's still one more door to kick down: the GPU. And honestly? GPU manufacturers are probably sweating right now because AI's appetite for VRAM is absolutely insatiable . First, AI workloads ate all your RAM for breakfast with massive language models and training datasets. Then they came for your storage with multi-terabyte model checkpoints. Now they're eyeing your GPU like it's the final boss in a horror game, except the boss always wins. Your RTX 4090? Cute. AI needs a server farm with 8x H100s just to load the model weights. The real kicker? While gamers are out here celebrating their 24GB VRAM cards, AI researchers are like "yeah that'll hold my model's attention layer... for one token." The GPU shortage wasn't a crypto thing—it was a preview of coming attractions.

Welcome to the AI era, where we've traded Stack Overflow copy-paste for politely asking a chatbot to not screw up. You'd think adding "make no mistakes" to your prompt would work like a compiler flag, but turns out AI doesn't respect your desperate pleas any more than your production server respects your deployment schedule. The beautiful irony here is thinking you can just ask for perfection and get it. If it were that easy, we'd all just write "// TODO: make this code perfect" and call it a day. But no, the AI keeps generating bugs like it's getting paid per defect, completely ignoring your carefully crafted instructions like a junior dev who skips the PR comments. Turns out prompt engineering is just debugging with extra steps and false hope.

The classic "rules for thee but not for me" situation. OpenAI's totally fine with hoovering up the entire internet to train ChatGPT, but when someone else does the same to them? Pure shocked Pikachu face. It's like getting mad at someone for copying your homework that you copied from the class genius. The irony is thicker than legacy code comments.

The only difference between AI consultants and LLMs is that one costs $300/hour. Both will confidently hallucinate a solution to your problem using words nobody understands, then gaslight you when it doesn't work. At least the LLM admits it's not sentient... yet.

Someone just casually asked Chipotle's customer support chatbot to help them reverse a linked list in Python before they can order their bowl. The bot, named Pepper, doesn't even flinch—it just drops a complete solution with proper syntax, explains the O(n) time complexity, and then pivots back to asking if they'd like to order a burrito. The joke here is twofold: first, the absurdity of blocking your lunch order on solving a LeetCode problem (peak developer anxiety right there), and second, the fact that AI chatbots have gotten so good that even a fast-food support bot can handle data structure questions better than some technical interviewers. Chipotle's bot just became your new coding mentor, and it doesn't even charge for Claude Code or Copilot subscriptions. The LinkedIn flex about ditching expensive AI coding tools for a burrito chain's free chatbot is *chef's kiss*. Who needs Stack Overflow when Pepper's got your back?