Hacking The AI Job Gatekeepers

The eternal struggle of being the tech person at a social gathering. There you are, trying to enjoy dinner with your spouse when suddenly their friends ambush you with questions about some obscure tech they heard about on a podcast. DeepSeek-R1 is actually a large language model (like ChatGPT's cousin), but to non-tech people, it might as well be alien technology. Meanwhile, your spouse has seen this movie before and knows exactly how the next hour of conversation will go—you reluctantly explaining machine learning concepts while your food gets cold. Ten years in the industry and I'm still the default tech support/explainer at every gathering. The dog represents my inner self—just wanting to be petted and fed treats instead of discussing transformer architectures over appetizers.

The AI benchmarking cult strikes again! Everyone's obsessed with those radar charts comparing Large Language Models using some bizarre "ball turning test" metric that nobody actually understands. It's just a bunch of geometric shapes that supposedly prove one model is better than another. The joke here is that these comparison charts have become so ubiquitous in AI discussions that even though they're practically meaningless to most developers, everyone nods along pretending to understand what they're looking at. Classic tech impostor syndrome - nobody wants to be the one to ask "what the heck does this actually measure?"

Ever opened a PR from an AI and seen comments like // This is a for loop that iterates through the array ? Welcome to the world of AI-generated documentation—where stating the painfully obvious is considered helpful. It's like having that one intern who explains what a keyboard is every time you sit down to code. Next up: ChatGPT will helpfully inform you that your function returns a value and that variables store data. Revolutionary stuff.

Remember when we used to memorize algorithms and syntax? Yeah, me neither. The meme shows our brains shrinking to pea-size after using ChatGPT for coding. Why bother storing all that knowledge when you can just prompt an AI? "Hey ChatGPT, how do I reverse a binary tree while making coffee?" and boom—instant solution without taxing those precious neurons. Soon we'll just be meat puppets with thumbs for typing prompts while our atrophied brains handle the critical task of deciding when to get more coffee. Progress!

Oh the sweet, sweet irony! 😂 Remember when everyone was freaking out that ChatGPT would replace developers? Now we've got Deepseek coming for ChatGPT's throne! It's like watching AI cannibalism in real-time - the robots are eating each other before they even get to our jobs! The circle of tech life continues... today's disruptor becomes tomorrow's disrupted. Guess ChatGPT should update its resume and start practicing those interview questions! Even AI can't escape the relentless march of newer, shinier technology!

Started coding a "simple hash function" and GitHub Copilot went full existential crisis mode. Started reasonable with "not cryptographically secure, but fast" then spiraled into "not guaranteed to be stable across different phases of the moon" and "different parallel universes." This is what happens when your AI assistant has seen one too many 3 AM debugging sessions. Somewhere in Silicon Valley, a neural network is clearly having PTSD flashbacks from training on StackOverflow comments.