VC Interview Be Like

OH. MY. GOD. The absolute CARNAGE of career trajectories! 2025 is coming for data scientists with a VENGEANCE! 💀 While AI engineers strut around looking like they just walked off a Silicon Valley fashion runway, data scientists are transforming into depressed philosophers drowning their sorrows at the bar! The AUDACITY of this career market! Remember when everyone and their mother was rushing to become a data scientist? "It's the sexiest job of the 21st century!" they screamed. Well, honey, the AI revolution waits for NO ONE. Those fancy regression models aren't looking so hot now that ChatGPT can do your entire job while also writing poetry about it!

The duality of AI in the development lifecycle is painfully accurate. Junior devs are celebrating like they've discovered fire – "Look ma, no hands!" – while generating code they barely understand. Meanwhile, senior developers stare into the existential void as they're forced to review the AI-generated spaghetti mess. That thousand-yard stare says it all: "I've seen things... terrible things... like nested ternaries and 200-line functions named 'doStuff'." The circle of programming life continues – AI just made the mess arrive faster.

The classic "I know better than the buzzwords" conversation that happens in every tech company these days. You're just trying to be the voice of reason suggesting a simple algorithmic solution, but management's been reading too many LinkedIn posts about AI revolutionizing everything. That "how dare you?" reaction is what happens when you threaten someone's chance to put "AI-powered solution" on their quarterly achievements slide. Ten years in the industry and I've learned questioning the AI hype is basically career suicide at this point.

The tech industry's selective standards are painfully real. They'll reject a fresh grad for not implementing some theoretical O(n) algorithm they'll never use again, but will happily throw billions at AI models running on brute-force compute that would make any algorithm professor have an existential crisis. For those who don't know, O(n) refers to linear time complexity - basically how efficiently an algorithm scales. Companies obsess over this in interviews then proceed to ignore efficiency completely when it comes to their shiny new toys. Next time you're rejected for not optimizing a binary tree traversal fast enough, just remember - somewhere a data center is melting the polar ice caps to generate a cat picture.

The modern dev dependency crisis in full display! Remember when we used to actually write code instead of prompting AI for solutions? Now it's all "Hey ChatGPT, implement a binary search tree" while our actual coding muscles atrophy. The mannequin perfectly represents that dev who freezes up when GitHub Copilot goes down for maintenance. Pure panic. Meanwhile, the rest of us dinosaurs who learned to code before AI assistants are just watching the chaos unfold with a mix of amusement and existential dread. Evolution is brutal.

OMFG, the absolute DELUSION! 💀 Someone thinks they can build ChatGPT for $750 when it actually costs $100 MILLION?! That's not a budget gap, that's the Grand Canyon of financial reality checks! It's like showing up to build the Titanic with a pool noodle and some duct tape. The train is OpenAI's massive infrastructure, the school bus is what this person thinks they need, and that pathetic $588 bid? That wouldn't even cover the ELECTRICITY for ChatGPT to say "hello world" for a day! The audacity! The drama! The complete disconnect from reality! This is peak "I watched a YouTube tutorial once, so I'm basically an AI engineer now" energy!