Thanks Copilot

When every single AI tool bombards you with the same "What do you want to build today?" prompt for the 47th time. Sure, I'll build a blockchain-based social network for cats with AR integration in 0.2 seconds! The rage is real when these no-code platforms promise to turn your napkin sketch into a production-ready app while actual developers are busy fighting dependency hell and merge conflicts. That "build your app in seconds" promise hits different after spending 3 hours configuring webpack.

Content Your first podcast will be awful Your first video will be awful Your first article will be awful Your first art will be awful Your first photo will be awful Your first game will be awful But your first code will be perfect. Zero bugs and a very clean code. It will be "Hello World" Me: ››> Print ("Hellow World!") Traceback (most recent call last): File " ", line 1, in Print ("Hellow World!") NameError: name 'Print' is not defined >›>

The expectation vs. reality of online programming courses hits harder than a production bug on Friday afternoon. Top panel: "What they promise" - a perfect object detection model identifying everything with impressive confidence scores. "Yes, after this course you'll build YOLO models that can detect a mosquito from space!" Bottom panel: "What you actually learn" - a basic linear regression with scattered data points that barely fit the line. "Congratulations, you can now predict housing prices with 60% accuracy and call yourself a 'data scientist' on LinkedIn!" The brutal truth is most courses promise you'll become the next AI genius, but you'll end up struggling to remember which way the x and y axes go. And somehow they'll still charge you $499 for the privilege.

Claiming you've been using ChatGPT since 1996 is like saying you had WiFi in the Middle Ages. For the youngsters: that's Courage the Cowardly Dog typing on a chunky beige PC from when the internet made dial-up sounds that haunted your nightmares. Back then, "AI assistance" meant asking your roommate if they remembered the syntax for a for-loop while they were in the shower. The closest thing to ChatGPT was probably Clippy, and even he couldn't help you reverse a binary tree.

The eternal machine learning love triangle! Your relationship with TensorFlow was going just fine until PyTorch walked by with those sleek dynamic computation graphs and intuitive Python interface. Now you're doing that awkward neck-twist of betrayal while TensorFlow catches you eyeing PyTorch's hot new features. The static graph never felt so... static. Let's be honest, we've all mentally cheated on our ML frameworks. It's not you, TensorFlow, it's your verbose API and that whole session management thing.

Ah, the Venn diagram of modern development. On the left: burnout, technical debt, pointless meetings, and constant reprioritizing. On the right: AI coding assistants speeding things up by Googling boilerplate code. And in that magical intersection? "Generating subtle, devastating bugs." That's efficiency for you—now we can create catastrophic failures twice as fast. Progress!