How It Feels Manually Coding Nowadays

Forget complex algorithms! This Python developer decided to outsource the "is odd number" check to ChatGPT. Just casually burning through API credits to determine if a number has a remainder when divided by 2. The function makes a full API call, parses the response, and checks if the answer contains "yes" - all to replace a simple return number % 2 != 0 . Peak computational efficiency! 💸

When someone innocently asks why you know Romanian geography so well, and you have to explain that implementing A* pathfinding means you've traversed every possible route between Bucharest and Cluj-Napoca about 47,000 times in your test cases. The chess board with the AI textbook is chef's kiss – because nothing says "I'm a normal person" like having Russell & Norvig's brick of a book memorized while your pathfinding algorithm treats European cities like graph nodes. Sure, you could just say you like geography, but where's the fun in hiding the fact that you've optimized heuristic functions using Romanian cities as your dataset? The Traveling Salesman Problem hits different when you're actually trying to visit every Romanian city in minimum time.

The five stages of beginner developer delusion, perfectly captured in skeletal form. It starts with innocent enthusiasm, quickly escalates to "I'm learning React to learn JavaScript" (which is like saying "I'm learning to fly a Boeing 747 to understand gravity"), then rapidly descends into the fever dream of building Netflix clones with ChatGPT after 72 hours of coding. By stage four, our protagonist is planning an AI SaaS empire after a week of copy-pasting Stack Overflow answers. The final transformation into a complete skeleton represents the ultimate delusion: dropping engineering college for a bootcamp that "guarantees" job offers. Senior developers watching this evolution: *sips coffee in traumatized silence*

So you're photoshopping watermarks onto your architecture diagrams to make them look AI-generated, just so you can blame the AI when juniors discover your frontend is hitting the database directly. Galaxy brain move right there. Instead of fixing the architectural nightmare you created, you're manufacturing plausible deniability. "Sorry, the AI made some questionable decisions" is the new "it works on my machine." At least now we know what the real use case for AI in enterprise is: a scapegoat with unlimited capacity for blame absorption.

Remember when buying a GPU was just an expense and not a second mortgage? In 2009, dropping $500 on a graphics card felt like a splurge. Fast forward to 2025, and you're staring at a $4,799 price tag with the same horrified expression as someone who just found out their entire codebase has no comments. Thanks crypto miners, AI enthusiasts, and whatever unholy alliance of market forces conspired to make rendering pixels cost more than my first car. At this rate, we'll soon be trading organs for ray tracing capabilities.

OpenGL? Friendly handshake. OpenCV? Sure, let's be buddies. OpenSSH? Come here, friend! OpenCL? Absolutely! OpenVPN? Of course! But then OpenAI shows up and suddenly everyone's like "wait, you're calling yourself WHAT now?" The irony is absolutely *chef's kiss* because OpenAI is about as open as a bank vault on a Sunday. They literally went from a non-profit promising open research to a multi-billion dollar company keeping their models more locked down than Fort Knox. Meanwhile, all the other "Open" technologies are actually, you know, OPEN SOURCE. The betrayal! The audacity! It's like showing up to a potluck empty-handed and still putting "generous" in your Instagram bio.