Do Not Disturb Machine Is Learning

Oh look, a scientific paper proving what we all suspected: our brains turn to mush when we outsource thinking to AI. The title is actually a hidden message – "Does LLMs Really Makes Us Dumb" – with the first letters spelling it out. Brilliant academic trolling right there. Those fancy brain scans? They're showing our neurons basically taking a vacation when using ChatGPT for essays. Seven MIT researchers spent grant money to scientifically confirm that copying AI homework makes you dumber. Could've just asked any TA grading freshman papers. Next groundbreaking study: water is wet, and Stack Overflow copy-paste makes junior devs forget how loops work.

The corporate data science dream team standing around watching one guy with Excel do all the actual work. Classic case of "we hired seven specialists with fancy titles to stare at a hole while the person who's been using VLOOKUP since 2003 actually solves the problem." This is why your company's $2M data infrastructure still ultimately feeds into someone's spreadsheet that crashes every third Thursday. The Excel guru probably makes half what the AI consultants do, but knows where all the bodies are buried in your database.

The evolution of tech support in four painful panels. Reddit: "Stupid." Stack Overflow: "Your question is off-topic." AI chatbot: "That's a very good question." Meanwhile, the kid is asking how to prevent screenshots on a website—something technically impossible but AI will happily pretend it's doable. The cycle of dismissive tech help is broken, but only because AI doesn't know when to say no. Progress?

When your data scientist crush drops the ultimate bombshell: "data matters more than the model." That painful moment when you realize all those weeks perfecting that fancy neural network architecture were pointless because your training data is just a dumpster fire of inconsistencies. The hardest pill to swallow in machine learning isn't some complex math equation—it's accepting that your beautiful, elegant algorithm is worthless without quality data behind it. Garbage in, garbage out... no matter how many GPUs you sacrificed.

The year is 2035. Your GitHub page now takes 15 minutes to load because it's scanning your code with 47 different AI tools, showing ads for Microsoft products, and suggesting you upgrade to Copilot Premium Plus Pro Max. Meanwhile, your diff is still "loading in 2 seconds" like it has been for the past decade. Progress! The real kicker? You'll still need to explain to the AI assistant why your perfectly valid code isn't actually a security vulnerability for the 500th time this week. But hey, at least now it can suggest you build a Pong game while you wait!

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."