The Ultimate Silicon Valley Exit Strategy

Oh. My. GOD. The existential crisis of our generation in TWO FRAMES?! 💀 First he's like "I don't care if AI wins over programmers" acting all tough and unbothered. Then BOOM—the punchline hits: "I just need FAANG to lose." It's the tech industry's villain origin story! Doesn't care about the robot apocalypse as long as those Silicon Valley giants get taken down with us. The PETTINESS! The DRAMA! The absolute CHAOS of prioritizing corporate revenge over humanity's survival! We're not just coding anymore, we're picking sides in the tech civil war. And honestly? Mood.

Oh look, it's the compiler we all secretly want but are too afraid to admit! The "AI C Compiler" (aicc) is basically what happens when you combine a programmer's desperation with their unwillingness to learn proper memory management. Instead of fixing your semicolons and memory leaks like a responsible adult, just throw your garbage code at ChatGPT and pray! "Will your code compile? Will it be fast or slow? Will it have memory leaks?" Who knows! It's like playing Russian roulette with your codebase, except all chambers are loaded and the gun is pointed at your production server. The best part? You don't even need to understand what you're doing anymore! Just make vague gestures at your requirements and let AI figure it out. Programming degree? Waste of money. Stack Overflow? Ancient history. Just whisper sweet nothings to the machine and watch it spit out code that's probably better than yours anyway.

Google's AI Overview just confidently explained that matrix multiplication "is not a problem in P" (polynomial time), which is... hilariously wrong. Matrix multiplication is literally IN the P complexity class because it can be solved in polynomial time. The AI confused "not being in P" with "not being solvable in optimal polynomial time for all cases" or something equally nonsensical. This is like saying "driving to work is not a problem you can solve by driving" – technically uses the right words, but the logic is completely backwards. The AI hallucinated its way through computational complexity theory and served it up with the confidence of a junior dev who just discovered Big O notation yesterday. And this, folks, is why you don't trust AI to teach you computer science fundamentals. It'll gaslight you into thinking basic polynomial-time operations are unsolvable mysteries while sounding incredibly authoritative about it.

Remember when we used to write our own algorithms? Now we're just watching ChatGPT and Deepseek haul our careers up the mountain while we take a nap in the sleeping bag of obsolescence. And the worst part? We have the audacity to brag about our "productivity" like we actually did something impressive. "Look how far I climbed" – yeah buddy, you typed a prompt and took a coffee break while the AI did all the heavy lifting. The only muscle you've exercised is your index finger hitting Ctrl+V.

The eternal dev dilemma: spend 20 minutes crafting the perfect prompt for ChatGPT explaining your obscure bug... or just Google the error message in 10 seconds. We all dramatically surrender to AI like wounded warriors, only to sheepishly crawl back to Stack Overflow five minutes later. The relationship status between developers and LLMs? "It's complicated."

Ah, the rare medical condition known as "Machine Learning Engineer Syndrome." The brain scan shows a human surviving with 90% of their brain replaced by AI, which explains why they can function normally despite writing 200 lines of code to print "Hello World" and claiming "the algorithm did it." This is basically every AI engineer who spends 8 hours prompting ChatGPT instead of learning how to code. The remaining 10% of brain matter is reserved exclusively for explaining why their neural network needs more compute time and arguing that "it's not a bug, it's an undocumented feature."