Our Jobs Are Safe For Now

Ah, the classic "pretend to be safe" AI script! Someone created the world's most useless AI safety mechanism - a Python program that just says it can't comply with dangerous requests while continuing to ask for more prompts in an infinite loop. It's basically the equivalent of putting a "Beware of Dog" sign on your fence when you own a goldfish. The filename "SuperSafeSupeIntelligence.py" is the cherry on top of this security theater sundae. Ilya Sutskever (OpenAI's chief scientist obsessed with AI safety) would be having a conniption fit right now.

GASP! The AUDACITY of matrix multiplication to steal someone's job! 😱 What we're witnessing here is the TRAGIC moment when a programmer realizes that AI can now do matrix calculations that used to be their bread and butter. The highlighted columns in the matrices show how AI models like Grok can process these complex mathematical operations in MILLISECONDS while we mere mortals spent YEARS perfecting our linear algebra skills! The desperate plea to Grok (Twitter's AI) to "please explain" is the digital equivalent of watching your career flash before your eyes. It's the mathematical equivalent of finding out your spouse has been cheating on you with a calculator!

The tech industry in a single image. Massive crowds fighting to post LinkedIn updates about how they're "leveraging agentic AI solutions" while VCs throw money at anyone who mentions the buzzword. Meanwhile, a handful of folks actually discuss job displacement risks, and even fewer build anything useful. And that lonely stick figure trying to generate actual value? That's the junior dev who just wanted to automate their unit tests but got pulled into an "AI transformation initiative." The hype-to-value ratio remains gloriously consistent across every tech wave I've survived since the dot-com bubble.

Sorting imports by character length instead of alphabetically or by module type? That's like organizing your sock drawer by how much each sock weighs. Sure, it looks oddly satisfying with that gradient effect, but your code reviewer is probably drafting your performance review right now. The real horror isn't the sorting method – it's that you're importing both matplotlib AND sklearn in the same file. That poor memory usage never stood a chance.

When you ask Jules AI to help with your configuration and it decides security is for the weak. From port 443 (HTTPS) to 8080 (plain HTTP), SSL disabled, and the cherry on top—replacing your environment variable with a hardcoded "password" literally called "dummy." This is what happens when you let AI write your security config. Next up: storing credit card numbers in a public GitHub repo called "definitely_not_important_stuff."

Nothing says "I'm about to create absolute chaos" like importing TensorFlow as plt, Pandas as np, NumPy as tf, and Matplotlib as pd. This unholy alias swap is the data science equivalent of putting the milk in before the cereal. Even Satan himself is impressed by this level of pure evil. It's the kind of code that makes senior devs wake up in cold sweats and frantically check their git blame history.