Different Use Cases

Remember when everyone was like "AI is coming for our jobs!" and we were all peeking through the blinds, nervously watching the AI bubble inflate? Well, now it's deflating faster than my motivation after a 3-hour estimation meeting. That smug little smile says it all. We've survived another tech apocalypse, folks. Just like we did with blockchain, NFTs, and whatever the metaverse was supposed to be. Turns out writing if-else statements for a living is still a viable career path after all.

The resume inflation has begun! We've all seen that one colleague who suddenly became an "AI expert" after using ChatGPT twice. Five years from now, we'll be sitting in interviews listening to people explain how they've been "pioneering machine learning solutions" since 2023, when in reality they just figured out how to prompt an LLM without it hallucinating too badly. The true AI skill of our generation? Convincing robots not to write poems when you just want them to fix your regex.

So POSIX apparently decided that "reviewing and modifying" LLM-generated code is best done with `rm` - you know, the command that permanently deletes files. Because nothing says "code review" quite like nuking it from orbit. The Unix philosophy has truly evolved from "do one thing well" to "do one thing: eliminate AI slop." The real galaxy brain move here is `rm -rf project/` for recursively fixing entire directories. It's not a bug, it's a feature! Can't have buggy AI code if there's no code at all. Zero lines of code = zero vulnerabilities. The most secure codebase is the one that doesn't exist. Honestly, given the quality of some LLM-generated code with its hallucinated APIs and creative interpretations of basic algorithms, this might be the most efficient code review process yet invented.

Junior devs getting bullied by the entire programming ecosystem until ChatGPT comes along like "Hey buddy, let me help you with that regex. No question is too stupid, I promise." The real programming revolution wasn't better frameworks or faster computers—it was finally having someone who doesn't make you feel like garbage for not knowing what a monad is.

So apparently God's running reality on a budget build now. With RAM prices going absolutely bonkers thanks to AI data centers hoarding memory like it's the apocalypse, even the Almighty had to dial back the graphics settings. Render distance set to potato mode—hence the fog that makes this highway look like a Silent Hill level. The joke here is that LLMs (Large Language Models) are notorious resource hogs, requiring massive amounts of RAM and compute power. They've literally driven up hardware prices so much that even in this fictional scenario, God can't afford to render the full simulation anymore. Reality.exe is now running on minimum settings because ChatGPT and friends are eating all the VRAM. Fun fact: Training GPT-3 consumed enough electricity to power an average American home for about 120 years. No wonder the universe is lagging.

So the AI companies got us all hooked on their coding assistants, made us forget what actual programming feels like, and then decided "hey, let's 10x the price now that everyone's dependent." Classic drug dealer business model, honestly. Stack Overflow watching thousands of engineers suddenly remember they exist after two years of radio silence is just *chef's kiss*. They're standing there like "Oh, NOW you need us? NOW you want to read documentation and ask questions like peasants? Where was this energy when you were copy-pasting AI slop without understanding it?" The irony is beautiful. We spent years complaining about Stack Overflow's toxic culture and downvote-happy moderators, fled to AI assistants the second they became available, and now we're crawling back because enterprise pricing hit different. Welcome back to manually googling error messages and getting marked as duplicate, folks. The circle of dev life continues.