VC Interview Be Like

The classic learning curve of doom! Newbie programmers staring up at the programming staircase of despair where even the first step (Hello World) looks like Mount Everest. Meanwhile, they're already Googling "how to build Skynet with no programming experience" and wondering why their neural networks aren't sentient yet. The irony is that most tutorials literally start with printing "Hello World" to the console, but somehow folks want to skip straight to building the next ChatGPT without understanding variables. It's like trying to compose a symphony when you can't even play "Hot Cross Buns" on the recorder.

The corporate tech joy ride that ends in a ditch. First, management gets ChatGPT Enterprise and everyone's excited. Then they add Windsurf and the party continues. Soon developers are "vibe coding" instead of writing proper tests. Finally, the AI is reviewing pull requests, and that's when your phone rings at 3 AM because production is on fire. Nothing says "career advancement" like explaining to the CTO why an AI approved code that deleted the customer database because it had "good vibes."

Content You're a bunch of node.js hipsters that just HAVE to install everything you read on Hacker News! But Docker allows us to run our applications anywhere! Do you hear yourself? Why do we need docker if we're running a VM? A container inside a container!!!

Ah, the ultimate showdown between nature and technology! Both parrots and ML algorithms babble nonsensical phrases they don't understand, but only one comes in a cute feathery package. Billion-dollar AI companies frantically trying to replicate what evolution perfected millions of years ago, and still can't match the "is adorable" checkbox. Maybe we should just train parrots to write our code instead of spending all that GPU money? At least when a parrot crashes, it just loses a few feathers instead of your entire production database.

The modern freelance developer's business model in its purest form. Get paid $20 to fix a bug, immediately spend half of it on a Copilot subscription that probably wrote the buggy code in the first place, and pocket a measly $10 profit. The smug anime girl just makes it perfect – that face when you realize you're essentially paying GitHub to help you fix the mess their AI created. It's the circle of tech life: create problems, sell solutions, repeat.

Nine data professionals standing around watching while one Excel guru does all the actual work. Classic corporate data science theater. The entire AI department, with their fancy degrees and machine learning models, rendered useless by someone who mastered VLOOKUP and pivot tables. That's what happens when you spend $2 million on a data lake but can't figure out how to drain a real one.