Recursion: The Art Of Never Actually Arriving

The classic educational progression: learn to drive an automatic in class, practice with a manual transmission for homework, then take your exam in the cockpit of a Boeing 747. Computer science degrees in a nutshell. "Here's how variables work" on Monday, "implement a neural network from scratch" by Friday, and "invert a binary tree while the building is on fire" during finals week.

Ah, the classic bell curve of AI anxiety. The folks at the low end of the IQ spectrum are blissfully confident they can't be replaced because they don't understand what's coming. The geniuses at the high end know they're safe because they're the ones building the AI overlords. Meanwhile, the rest of us in the middle—just smart enough to understand the threat but not brilliant enough to be irreplaceable—are sweating bullets. This is basically the tech industry's version of "ignorance is bliss" meets "knowledge is power," with the vast majority of us stuck in purgatory. Twenty years in this field and I'm still not sure if I should be learning to code better or learning to make coffee for the robots.

That moment when your senior dev asks you to implement a shrinking algorithm and you decide to just decrement a counter in a loop. The crying cat perfectly captures the pain of code review day when they see your O(n) solution that could've been a simple one-liner. "It technically works" is your only defense as you prepare to rewrite it for the fifth time.

Nothing quite like watching someone with 8 years of academic research flex their theoretical knowledge while completely freezing up when asked to write a simple for-loop. The industry's full of these theoretical gymnasts who can explain quantum computing algorithms but struggle with Git basics. Meanwhile, the bootcamp grad who's been coding for 6 months is shipping features like it's nothing. The classic theory-practice gap in computer science is wider than the average developer's monitor setup.

Japanese train stations 🤝 programmers: indexing from zero. While normal humans count from 1, this train platform proudly displays platforms 0 and 1 for the Shinonoi Line, proving that somewhere, a developer was definitely in charge of the numbering system. The non-tech folks probably wonder why they can't just use normal numbers like civilized people, but we know better. Arrays start at 0, platforms start at 0, life starts at 0. It's the natural order of things if you've spent enough time staring at code until your eyes bleed.

Four years of studying sorting algorithms, computational complexity, and discrete mathematics... only to find yourself completely out of your element in a real-world codebase. That scuba gear in the desert perfectly captures the disconnect between academic theory and industry reality. You're equipped for an ocean of knowledge that simply doesn't exist where you've landed. Meanwhile, your new team casually mentions they need you to refactor a 10-year-old legacy system written by someone who apparently coded with their elbows. No data structure in your textbooks prepared you for that depth of technical debt.