Reality Is Often Disappointing

BEHOLD! The two genders of tech bros: those who scoff at astrology while those SAME MEN will literally build an entire neural network to figure out if their crush likes them back! 💀 Like, sweetie, you're writing complex AI algorithms with multi-head attention mechanisms to predict relationship outcomes when you could just TEXT HER?! The DRAMA of using gradient descent to calculate the probability of getting back together instead of therapy is just... *chef's kiss* peak engineer behavior! Who needs Mercury retrograde when you've got matrix calculations to tell you you're still single? ICONIC.

Oh god, this is brilliant. Just imagine all those LinkedIn posts now: "Our new cocaine-powered chatbot will revolutionize customer service!" or "Top 10 ways cocaine will disrupt your industry!" The tech hype cycle and the actual cocaine cycle have the same phases: initial euphoria, inflated expectations, crushing disappointment, and somehow still costing you all your money. The only difference is one crashes after 20 minutes and the other after your next funding round.

Sure, AI can build your app in 5 minutes instead of 5 hours, but have fun debugging that spaghetti junction of code! The left shows a nice, simple railway track—straightforward code built without AI. Clean, predictable, gets you from A to B. The right? That's your AI-generated "masterpiece"—a chaotic mess of intersecting tracks going in seventeen different directions at once. Your app might be built faster, but good luck figuring out which track leads where when everything crashes. It's like asking a hyperactive octopus to organize your closet. Speed isn't everything when you're spending the next month untangling what your AI "helper" thought was a brilliant solution!

When GitHub Copilot generates your data class and decides to nest variables like Russian dolls. That's not a class, it's a family tree of Strings going back 17 generations. Somewhere in that code is the String that contains the meaning of life, but you'll need to scroll for 3 days to find it. Enterprise software at its finest—where simplicity goes to die.

The duality of AI code reviews. Non-technical folks see a magical solution that writes perfect code while senior devs spot the nested callbacks, security vulnerabilities, and performance nightmares lurking beneath the surface. It's like watching someone admire a beautifully painted house without noticing it's built on quicksand. The hallucinated documentation is just the cherry on top of this algorithmic disaster cake.

Ah yes, the revolutionary AI integration strategy: squirting a tiny bit of machine learning onto a bar of legacy code and calling it "innovation." That soap dispenser is working exactly as intended – technically dispensing something, but completely missing the point. Just like how adding a chatbot that can only say "Have you tried turning it off and on again?" somehow justifies a 20% price increase. Investors impressed, users unimpressed, developers wondering if they should update their resume.