Also In My Bank Account 😁

From moon landings to being trapped in Vim—what a downgrade! The 1960s programmer stands tall with actual documentation and the audacity to claim they'll conquer space, while 2025's version is just a doge meme begging for help to escape an editor that's been around since 1991. Modern devs have ChatGPT, StackOverflow, and Spotify, yet still can't figure out how to type ":q!" without a Reddit thread. Progress? I think not. The only thing we're flying to these days is the coffee machine between debugging sessions.

Content How it feels working at the office without an RGB keyboard, gaming mouse and gaming chair:

Remember when we actually knew how to build websites? Now I've got a decade of experience but can't center a div without asking ChatGPT. The moment those AI servers go down, I'm reduced to a praying mantis in human form, desperately hoping my muscle memory kicks in for basic HTML tags. "What was that flexbox syntax again? Is it justify-content or align-items? LORD HELP ME."

Ah, the modern tech hero's journey: "I wrote a prompt, AI generated an API, and now I'm basically the next unicorn founder." Sure buddy, and I once wrote a regex that worked on the first try – doesn't mean I'm Jeff Bezos. The gap between "my AI prompt worked once" and "billion-dollar company" is roughly the same as the gap between "I installed Linux" and "I now run NASA." Those compute bills will hit harder than the reality that prompt engineering isn't the same as actually engineering. Ten years in the trenches and I've learned one truth: the harder someone humble-brags about how easy something was, the more spectacularly it'll explode in production.

The tech industry's obsession with acronyms just got an upgrade. Remember when everyone wanted to work at FAANG (Facebook/Meta, Apple, Amazon, Netflix, Google)? Well, throw that resume in the trash. Now we've got GAYMAN – Google, Amazon, Y-combinator (I guess?), Meta, Apple, Nvidia. Because nothing says "I'm tracking the market" like reorganizing the same companies every 6 months into increasingly questionable acronyms. Notice how Netflix got kicked to the curb faster than a junior dev who pushed to production on Friday afternoon. Meanwhile, Nvidia swooped in riding that sweet, sweet AI GPU money train. The circle of tech life continues.

For decades, error handling was that thing everyone nodded about in code reviews but secretly wrapped in a try-catch that just logged "oops" to console. Nobody wrote proper error messages, nobody validated inputs, and stack traces were treated like ancient hieroglyphics. Then AI showed up and suddenly everyone's an error handling expert. Why? Because when your LLM hallucinates or your API call to GPT-4 fails, you can't just shrug and refresh the page. Now you need graceful degradation, retry logic, fallback strategies, and detailed error context. The massive book represents all the error handling knowledge we should've been using all along. The tiny pamphlet is what we actually did before AI forced us to care. Nothing motivates proper engineering practices quite like burning through your OpenAI API credits because you didn't handle rate limits correctly.