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The circle of digital life! Your AI coding assistant confidently suggests improvements while secretly running on a diet of Stack Overflow answers from 2014. Meanwhile, those Stack Overflow answers need constant human updates because technology evolves faster than documentation. It's the ultimate ouroboros - AI pretending to be smarter than the humans who created the very content it regurgitates. Next time your AI suggests "optimizing" your perfectly functional code, remember it's just parroting some poor soul who got 47 upvotes seven years ago.

The classic "rub the lamp and make a wish" scenario, but with a programmer twist. Some poor soul wishes NVIDIA wouldn't make GPUs with 8GB VRAM, and the genie's just like "yeah... not happening." It's the digital equivalent of asking for world peace. Even supernatural beings can't convince NVIDIA to put more memory in their mid-range cards without charging you a kidney. The genie doesn't even bother offering three wishes—just straight to "hopeless" because he knows the GPU market better than anyone.

Someone asked ChatGPT about JavaScript's export default App; syntax and got the most refreshingly honest AI response ever: "I honestly have no idea." Finally, an AI that admits defeat instead of confidently hallucinating some nonsensical explanation about React components! If only my junior devs had this level of self-awareness instead of copy-pasting Stack Overflow answers they don't understand. The robots might replace us, but at least they'll be upfront about their limitations.

Putting on glasses to see the difference between "AI Engineer" and "OpenAI-API-to-product-connector" is the most savage reality check of 2023. You're not architecting neural networks—you're just paying $0.002 per token to have ChatGPT write your code while you add water to your ramen. The modern equivalent of "I know HTML" in 1999 is "I'm an AI Engineer" in 2023. Truth hurts, doesn't it?

Top panel: Homer standing confidently with a single <AI> tag on his chest. Bottom panel: Homer covered in a chaotic mess of if statements. The perfect visual representation of how we all pretend our code is elegant AI when really it's just a tangled nightmare of nested conditional statements. That "revolutionary machine learning algorithm"? Just 500 if-statements in a trench coat trying to look sophisticated. The corporate demo vs. the git repository reality.

Started coding a "simple hash function" and GitHub Copilot went full existential crisis mode. Started reasonable with "not cryptographically secure, but fast" then spiraled into "not guaranteed to be stable across different phases of the moon" and "different parallel universes." This is what happens when your AI assistant has seen one too many 3 AM debugging sessions. Somewhere in Silicon Valley, a neural network is clearly having PTSD flashbacks from training on StackOverflow comments.