The Double Standard Of AI Theft

The eternal struggle of modern coding: the AI vibe coder vs. the ADHD vibe coder. On the left, we have the AI-dependent programmer - a sad, corporate bootlicker waiting for ChatGPT to explain basic packages while producing non-functional code that somehow still gets them hired at FAANG companies. Meanwhile, the ADHD coder on the right is living their best chaotic life - dressed like they raided a highlighter factory, confidently hacking together solutions based on "voices in their head" and that one function they glimpsed three weeks ago. Their code might be a ticking time bomb, but at least it has personality . The real genius here? The ADHD coder's superpower of instantaneous StackOverflow garbage collection. Who needs AI when you've mastered the ancient art of copy-paste-and-pray?

Ah yes, the classic tech industry anatomy lesson. OpenAI and Microsoft Copilot are getting all the attention up top, looking shiny and impressive, while the real MVPs—FOSS projects, independent artists, and venture capital—are doing the heavy lifting down below. It's almost poetic how these AI giants are basically standing on the shoulders of... well, everything else. OpenAI scraped half the internet (including your GitHub repos, you're welcome), Copilot trained on millions of lines of open-source code, and both are propped up by billions in VC money that's desperately hoping this AI bubble doesn't pop before they exit. The irony? The open-source community built the foundation, artists unknowingly donated their work to the training sets, and VCs threw cash at it like confetti. Meanwhile, the fancy AI tools get all the credit while casually forgetting to mention the awkward "how did we get this data again?" conversation. Classic tech move—stand on giants, claim you're flying.

Someone "fixed" OpenAI's UI by making the popup text more concise and readable, then shot their shot asking for a job at $5/hour plus a can of cola. Honestly? That's underselling yourself king, but I respect the hustle. The side-by-side comparison shows how a simple UI tweak can make a huge difference—turns out even AI companies need better UX designers. The salary negotiation strategy is questionable though. Even interns get paid more than that, and they usually don't even get the cola. Fun fact: The original popup is unnecessarily wordy. "Run your next API request by adding credits" vs "Run your next API request by ad..." (cut off). Sometimes the best code is the code you delete, and apparently the same goes for UI copy.

Nothing screams "I let ChatGPT write my entire README" quite like opening a repository and being assaulted by a wall of 🚀✨💡🎯🔥 emojis. Like bestie, I came here for documentation, not a motivational Instagram post from 2019. The sheer AUDACITY of thinking that slapping rocket ships next to your feature list makes your half-baked npm package look professional is truly unhinged behavior. You just KNOW someone copy-pasted an AI-generated template without even reading it, because no human being with a functioning frontal lobe would naturally write "✨ Features ✨" followed by "🎨 Beautiful code architecture 🎨" in a serious technical document. Sir, this is a GitHub repository, not a vision board.

The classic tech startup founder transformation arc, but make it AI. You start with that ambitious gleam in your eye thinking you're about to revolutionize machine learning. Then you dump your entire Series A funding into GPUs and cloud infrastructure because "we need compute power!" Next thing you know, you've automated every single position in your company including your own, because efficiency, right? The punchline? Your AI-powered product is so expensive to run that your target market can't even afford the subscription fees. Turns out training models on petabytes of data and running inference at scale costs slightly more than a Netflix subscription. Who knew that burning through millions in compute costs would make your pricing model look like a luxury yacht rental? The clown makeup progression perfectly captures the descent from "visionary entrepreneur" to "why is my AWS bill six figures this month?" The real kicker is realizing you've essentially built a very expensive solution looking for a problem that can actually pay for it.

Oh look, it's the modern developer's daily ritual! That moment when you check what you stepped in and discover it's not regular garbage—it's AI Generated SQL . The perfect representation of what happens when you let AI write your database queries. Sure, it looks like SQL from a distance, but examine it closely and you'll find a horrifying abomination that would make even the most battle-hardened DBA weep. Nothing says "I've made terrible life choices" quite like debugging code that was hallucinated by an algorithm with the database knowledge of a caffeinated squirrel. Next time just write the query yourself, unless you enjoy explaining to your boss why the production database is suddenly identifying as a toaster.