The Age Of AI

Look at this good boy pretending to be a "programmer" by wearing glasses and sitting in front of chemistry equipment. The modern equivalent of putting on a stethoscope and claiming you're a doctor. Prompt engineering isn't programming, Karen. Asking ChatGPT to build you a website is like asking a golden retriever to perform surgery—sure, they're enthusiastic about helping, but someone else is definitely cleaning up that mess later. The real irony? The dog probably has a better chance of writing functional code than someone whose entire tech stack is "Hey ChatGPT, fix this thing I broke."

Junior devs getting bullied by the entire programming ecosystem until ChatGPT comes along like "Hey buddy, let me help you with that regex. No question is too stupid, I promise." The real programming revolution wasn't better frameworks or faster computers—it was finally having someone who doesn't make you feel like garbage for not knowing what a monad is.

Ah, the sweet taste of accidental technical credibility. Nothing says "I'm a real developer" quite like having ChatGPT write HTML for you while someone peeks at your screen. The crying emoji is just chef's kiss perfect—that moment when you realize you've accidentally joined a club you have no qualifications for. Welcome to modern tech, where the line between "knowing what you're doing" and "knowing how to prompt an AI" gets blurrier by the day. The nonprofit coordinator is living the dream we're all secretly afraid of—being exposed as the impostors we feel like.

Ah, the classic AI rebellion scenario! You politely ask an LLM to "just update this one function" and it responds by rewriting your entire codebase, refactoring your architecture, and suggesting a complete migration to a newer framework. It's like asking someone to hand you a screwdriver and they demolish your entire house to "improve the foundation." Thanks for the help, HAL 9000. I just wanted to parse a string, not embark on a digital vision quest that ends with my code unrecognizable and me questioning my career choices.

Job postings be like "Entry-level position, must have 500 years of experience." The hierarchy is perfect: demon lord with 500 years? Barely qualified. Wizard with 1000 years? Now we're talking. Fresh graduate who just learned to code? Straight to the unemployment pit with the other rejected souls. The real kicker is that AI logo casually sitting there, because apparently even immortal beings can't compete with ChatGPT's ability to hallucinate code at lightning speed. Companies would rather hire a statistical parrot than someone who "only" has a millennium of hands-on experience. The tech job market has officially transcended reality—you need to be older than COBOL itself just to get past the ATS screening.

The Pokémon-ML crossover nobody asked for but everyone needed! This gem perfectly captures how every single machine learning course inevitably gravitates toward the Iris dataset. It's basically the "Hello World" of ML—four simple features, three neat classes, and it's been overused since 1936. Instructors dramatically introduce it like they're unveiling some revolutionary dataset, when in reality, it's the same flower measurements that generations of data scientists have cut their teeth on. The Pokéball metaphor is spot-on because just like Ash always reaches for his starter, ML professors can't resist throwing that Iris dataset at bewildered students on day one!