Real Recognise Real: The Great AI Career Divide

Someone needs to tell Elon about the exponential growth of node_modules folders. While AI might be growing fast, any JavaScript developer knows the true speed champion is watching your disk space vanish as soon as you run npm install . That 5MB project somehow needs 500MB of dependencies, and God help you if you're on a slow internet connection. The real technological singularity isn't AI - it's when a single node_modules folder finally consumes all available storage on Earth.

OH. MY. GOD. Someone actually asked ChatGPT to code the gender pay gap into existence! 😱 The absolute AUDACITY to create a function that multiplies a man's salary by 0.77 to get a woman's salary! This is like asking an AI to mathematically formalize inequality while wearing a suit and pretending it's just "realistic programming." The function is so brutally honest it might as well have variable names like "systematic_inequality" and "patriarchy_coefficient." Whoever prompted this probably also asks for functions to calculate how many kitchen appliances equal one sports car. 💀

Ah yes, the existential crisis of every Python developer. Born in 1991, older than Java (1995), yet somehow still the awkward middle child of programming languages. The counter showing "0 days without suicidal thoughts" is just *chef's kiss* perfect. Meanwhile, Java's out there running banking systems and Android, while Python's still trying to convince everyone that "no really, we're enterprise-ready too!" despite spending most of its time doing data science homework and gluing together other people's actual technologies. The bearded dev staring into the void with coffee is all of us who chose Python for its "simplicity" only to realize we picked the language equivalent of a participation trophy.

The classic programmer's dilemma! When your university teacher announces they'll teach Python for OpenCV because "most students don't know it," but you're standing there with 8 years of experience facing two equally painful paths: either pretend you're learning everything from scratch (boring castle on the left) or flex your skills by showing off some absolutely demonic code that'll make your professor question their career choices (haunted lightning castle on the right). The fork in the road represents that moment of decision every experienced dev faces in intro classes - do I play it safe or do I unleash chaos? Spoiler alert: we always choose chaos.

The modern "full stack" - three AI tabs open in your browser while you pretend to know what you're doing. Remember when being full stack meant actually knowing multiple languages and frameworks? Now it's just knowing which AI to ask for which problem. "Yes, I'm proficient in Claude, ChatGPT, and Perplexity" should be the new line on resumes. The only stack that matters is the stack of browser tabs helping you fake your way through that ticket your PM swore was "just a small change."

The duality of AI in the development lifecycle is painfully accurate. Junior devs are celebrating like they've discovered fire – "Look ma, no hands!" – while generating code they barely understand. Meanwhile, senior developers stare into the existential void as they're forced to review the AI-generated spaghetti mess. That thousand-yard stare says it all: "I've seen things... terrible things... like nested ternaries and 200-line functions named 'doStuff'." The circle of programming life continues – AI just made the mess arrive faster.