If We Can't Steal, We Can't Innovate

The job market has gone absolutely feral with AI requirements. You've got companies demanding "AI platform" experience, "AI powered" solutions, "AI first" architecture, and the mysterious "AI agentic flow" (because apparently just saying "AI agents" wasn't buzzword-y enough). Meanwhile, you're sitting at the bar like Homer, just trying to land a job with your regular old programming skills. By 2026, every job posting will require 5+ years of experience with AI frameworks that were released 6 months ago. Entry-level positions will demand you've built your own LLM from scratch and trained it on your tears. The kicker? They'll probably use an AI recruiter to reject your application in 0.3 seconds because you didn't use the exact keyword "agentic" in your resume.

So while everyone's having existential crises about AI replacing programmers, here's a friendly reminder that intelligence follows a bell curve. The folks screaming "AI IS SMART" and "AI WILL REPLACE PROGRAMMERS" are sitting at opposite ends of the IQ distribution, both equally convinced they've figured it all out. Meanwhile, the vast majority in the middle are just like "yeah, AI is a tool that's pretty dumb at a lot of things but useful for some stuff." It's the Dunning-Kruger effect in real time: people with minimal understanding think AI is either a god or completely useless, while those who actually work with it daily know it's more like a very confident intern who occasionally hallucinates entire libraries that don't exist. Sure, it can autocomplete your code, but it'll also confidently suggest you divide by zero if you phrase the question wrong. The real galaxy brain take? AI is a productivity multiplier, not a replacement. But nuance doesn't make for good LinkedIn posts, does it?

You ask for proper design documentation—wireframes, user flows, component libraries, maybe some accessibility guidelines—and instead you get a requirements doc that looks like it was generated by an AI that learned UX from reading fortune cookies. The brutal contrast here is *chef's kiss*: one side is desperately pleading for actual design specs, while the other side casually hands over what can only be described as generative AI word vomit wrapped in a Google Doc. The term "slop" has become the perfect descriptor for low-effort AI-generated content that technically exists but provides zero actual value. It's like asking for a Figma prototype and getting back a ChatGPT hallucination formatted as a PRD. The design team probably spent 5 minutes typing "create a requirements document for our app" into some AI tool and called it a day, while you're left trying to build an actual interface from what essentially amounts to corporate lorem ipsum.

You spend hours crafting elegant solutions, architecting clean code, implementing design patterns... and then AI just casually vomits out 47 nested if-else statements that somehow work perfectly. No switch cases, no polymorphism, no strategy pattern—just raw, unapologetic conditional chaos that passes all tests on the first try. Meanwhile you're standing there with your carefully refactored code wondering if those 4 years of CS degree were just an elaborate prank.

Content There are two types of people in this world ... z-index: 999; z-index: 1000;

Half a billion dollars. In one month. Because someone forgot to set API rate limits on Claude. You know that junior dev who kept asking Claude to "just refactor this one more time" and "maybe make it cleaner"? Yeah, turns out they were running it in a loop. For 30 days straight. On the company dime. Every tech lead's nightmare: giving the team AI access without proper guardrails. It's like handing out corporate credit cards at a Vegas buffet. Sure, the code probably looks pristine now, but was it worth the GDP of a small nation? Pro tip: Set. Usage. Limits. Or enjoy explaining to the CFO why your todo app cost more than a SpaceX launch.