Is "AI" A Buzzword?

When AI tools and low-code platforms started promising that anyone could build software in minutes, the tech industry collectively nodded and said "sure, Jan." But someone finally said the quiet part out loud: if coding suddenly became 10x easier without any actual innovation in computer science, maybe—just maybe—the whole thing is smoke and mirrors. It's like watching someone claim they invented a revolutionary diet pill that lets you eat whatever you want, except the pill is just a rebranded multivitamin and aggressive marketing. The real kicker? The industry's been hyping these "revolutionary" tools while senior devs are still debugging the same CSS alignment issues they were fighting in 2015.

Einstein called it insanity. Machine learning engineers call it "Tuesday." The beautiful irony here is that ML models literally work by doing the same thing over and over with slightly different random initializations, hoping for better results each time. Gradient descent? That's just fancy insanity with a learning rate. Training neural networks? Running the same forward and backward passes thousands of times while tweaking weights by microscopic amounts. The difference between a broken algorithm and stochastic optimization is whether your loss function eventually goes down. If it does, you're a data scientist. If it doesn't, you're debugging at 3 AM questioning your life choices. Fun fact: Stochastic optimization is just a sophisticated way of saying "let's add randomness and see what happens" – which is essentially controlled chaos with a PhD.

Remember when we thought we'd train AI to help us write code? Top panel: cute little AI cub learning from the wise software engineer master. Bottom panel: six months later, that same AI has evolved into a towering beast while we're still sitting there with our legacy code knowledge from 2019. The career progression timeline has been dramatically compressed. Took me 15 years to become a tech lead. Took AI about 15 minutes to make half my StackOverflow contributions irrelevant. But hey, at least I still know how to exit Vim. For now.

OH. MY. GOD. The BRUTAL truth about our toxic relationship with AI coding assistants! 💅 We're literally gambling our productivity away with these AI slot machines! Type a vague prompt, hit "Generate" and PRAY TO THE CODING GODS that you'll get something that doesn't make your compiler have an existential crisis! "Just one more prompt, I swear this will fix it!" - me, 47 prompts later, sobbing into my energy drink while my deadline approaches at the speed of light. Meanwhile, OpenAI is cackling all the way to the bank! The absolute AUDACITY of spending 3 hours prompting for something that would take 20 minutes to code yourself. But here we are, calling ourselves "prompt engineers" like we've invented a new profession instead of admitting we're just gambling addicts in developer hoodies! 💁‍♀️

Delegating the TypeScript migration to AI is the modern equivalent of tossing your problems over the wall to the junior dev. Nothing says "I've reached peak seniority" like asking Claude to convert your janky JavaScript codebase while you kick back and pretend you're "architecting." The best part? That "make no mistakes" command—as if AI doesn't hallucinate semicolons like I hallucinate deadlines. Next week's ticket: "Fix all the weird union types Claude created that somehow accept both strings and refrigerators."

Multi-threading leaves you looking rough around the edges—classic race conditions and deadlocks will do that. SIMD hits even harder with those vectorization headaches. CUDA cores? You're barely holding it together after debugging memory transfers between host and device. But Tensor cores? You're grinning like an idiot because your matrix multiplications just became absurdly fast and you finally feel alive again. Each level of parallel computing optimization takes a piece of your soul, but the performance gains are too good to quit. You start with simple threading, then you're chasing SIMD instructions, next thing you know you're writing CUDA kernels at 2 AM, and before long you're restructuring everything for tensor operations. The descent into madness has never been so well-optimized.