Too Afraid To Ask About LLM Benchmarks

The stack of support holding up our broken code is too real! Your janky codebase is somehow balanced on a precarious tower of AI suggestions, desperate Google searches, StackOverflow copy-pasta, that one tutorial from an Indian guy with 240p video quality but god-tier explanations, ancient Git repositories nobody's touched since 2013, and pure dumb luck. The dog (your code) has absolutely no business standing on that wobbly pile, yet somehow it works! Every developer knows that touching ANY part of this fragile ecosystem might send the whole thing crashing down. The compiler isn't impressed, but hey—ship it anyway!

Oh snap! The classic tech industry bait-and-switch! 😂 Companies be like "Check out our REVOLUTIONARY AI system" and then the fine print reveals it's actually just outsourced human labor! Amazon's "just walk out" checkout tech that everyone thought was some magical computer vision breakthrough? Surprise! It was 1,000 humans in India watching cameras the whole time! The astronaut meme perfectly captures that moment when the tech bubble bursts and we realize the "AI" behind the curtain is just people working for cheaper wages. Next time someone brags about their company's "AI solution," I'll be side-eyeing them wondering how many humans are actually powering that "algorithm"!

Left guy's in denial about AI coding tools while right guy's already seen the git blame logs from the future. The eternal cycle continues: new tech emerges, developers panic, then end up maintaining the mess it creates. The only constant in programming is cleaning up after the latest "revolutionary" tool. Just wait until we're all writing prompts to fix the prompts that fixed the code that broke the system.

The classic tech hype cycle in its natural habitat. First, AI writes 90% of code. Then AI writes 100% of code. Then reality hits and humans get paid premium wages to fix the AI's spaghetti code. Reminds me of that time we deployed an "automated" monitoring system that generated so many false alerts we had to hire three people just to monitor the monitoring system. Progress!

The railroad tracks of progress have certainly gotten more complex! On the left, we have the traditional straight-line coding path—simple, predictable, and takes you 5 hours to reach a single destination. On the right, the AI-assisted coding multiverse with infinite possibilities, chaotic intersections, and enough track switches to give a train conductor an existential crisis. Sure, you'll build your app in 5 minutes with AI, but then spend the next 4 hours and 55 minutes figuring out which of the 47 different generated solutions actually works without summoning digital Cthulhu to your codebase. The real question: are we moving faster or just creating more impressive train wrecks?

The tech revenue showdown nobody expected! While OpenAI's impressive $3.7B looks solid in its professional attire, OnlyFans struts around in flamboyant pants with nearly double the revenue at $6.6B. Just goes to show that while we're building sophisticated AI models and neural networks, the most profitable tech isn't always the most complex. Sometimes the simplest user-generated content model wins by a landslide. Venture capitalists frantically taking notes right now: "Less transformers, more... transformations?"