Comedians In Shambles

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!

Garbage in, garbage out—but with extra steps! When you feed an AI model your terrible code as training data, don't act shocked when it spits back equally terrible solutions. It's like teaching a parrot all your worst swear words and then being surprised when it curses during family dinner. The circle of code life continues: your technical debt just found a way to reproduce itself through artificial intelligence.

Ah yes, the "innovative" AI startup landscape. Buzz Lightyear proudly announcing a "totally unique LLM use case" while the shelves below reveal the harsh truth: it's just ChatGPT API with a wrapper. Like claiming you invented the sandwich when all you did was buy bread from the store and put your logo on the packaging. The Silicon Valley special - repackaging someone else's technology and calling it revolutionary. The digital equivalent of putting racing stripes on a Honda Civic and calling it a Ferrari.

Oracle's giant inflatable bubble proclaiming "AI changes everything" is the perfect metaphor for the tech industry's current state. Billions in funding, grandiose promises, and what do we get? A big blue balloon that could pop at any moment. Just like the dot-com bubble, but with more buzzwords and fewer viable business models. Next year they'll probably need a bigger dome for "Blockchain Quantum AI changes everything... again."

Machine learning algorithms don't question their training data—they just optimize for patterns. So when a concerned parent uses that classic "bridge jumping" argument against peer pressure, ML algorithms are like "If that's what the data shows, absolutely I'm jumping!" No moral quandaries, no self-preservation instinct, just pure statistical correlation hunting. This is why AI safety researchers lose sleep at night. Your neural network doesn't understand bridges, gravity, or death—it just knows that if input = friends_jumping, then output = yes. And this is exactly why we need to be careful what we feed these algorithms before they cheerfully optimize humanity into oblivion.

Ah, the eternal dev dream: "Can AI just handle all this data conversion crap so I don't have to?" Meanwhile, every developer who's spent weeks building custom parsers for legacy government PDFs is quietly sobbing in the corner. The real treasury isn't money—it's the sanity we lost converting Excel to JSON. Pro tip: if you want to feel true pain, try parsing a PDF that was originally a scanned document from 1997 that someone converted to Word and then back to PDF again.