The AI Rebrand Money Printer

The so-called "advanced AI" for processing insurance claims? Just a Python script that flips a coin! The code imports the random module and uses random.choice() to pick between "deny" and "approve" with equal probability. Next time your claim gets rejected, remember it wasn't because of your pre-existing condition—it was because RNGesus wasn't in your favor today. Sophisticated machine learning my foot! It's literally the computational equivalent of "eeny, meeny, miny, moe" but with fewer steps.

The circle of technological bewilderment continues! Future programmers will stare slack-jawed at our primitive coding methods without AI assistance, while we're already scratching our heads wondering how the ancients managed without Stack Overflow to copy-paste from. It's the developer's version of "I walked uphill both ways to school" except each generation's hill gets replaced with fancier tools. Somewhere, a programmer from the 70s is laughing at us all while debugging with actual paper printouts.

The world's most efficient and accurate decision tree in computing history. While VCs throw millions at anything with "blockchain" in the pitch deck, actual engineers have known this truth for years. The 2025 update will just be the same diagram with "Do I need AI?" added, and spoiler alert - the answer is also "No." Unless you're selling to people who don't understand technology but control the budget.

Ah, the classic "let's use a sledgehammer to kill a fly" approach. Every tech startup these days thinks they need machine learning to solve problems that could be handled with an if-statement and a cup of coffee. After 15 years in the industry, I've sat through countless pitch meetings where some bright-eyed founder explains how their revolutionary AI will disrupt the sandwich-ordering process. Meanwhile, their actual problem is that they can't figure out how to store user preferences in a database. The real kicker? When they finally implement their neural network to predict topping preferences, it works worse than random chance. But hey, at least they can put "AI-powered" in their pitch deck!

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.

Copilot is that "helpful" AI pair programmer who creates more problems than it solves. It's like having an intern who confidently writes myAwesomeVariableThatDoesStuff when your codebase uses snake_case, adds comments like "// This function does things" and then has the audacity to hold your actual productivity hostage behind a paywall. The smug satisfaction on that farmer's face perfectly captures Copilot's attitude: "Sure, I wrote garbage code that violates every convention in your project, but hey... it ain't much, but it's honest work." Honest work my keyboard! It's digital sabotage with a subscription fee.