Me In Five Years

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.

When asked about AI integration in job applications, this person went full eldritch horror mode instead of the usual "I used ChatGPT to debug my code" nonsense. The poetic description of AI as a forest monster that "speaks with a thousand voices" and "wears your face" is both hauntingly accurate and infinitely more interesting than whatever corporate-friendly answer HR was fishing for. Bonus points for acknowledging the existential dread of AI tools that "know not truth from lie, though it speaks them all the same" while everyone else pretends they're just fancy spell-checkers.

Someone at Microsoft gave a presentation on Copilot's RAG architecture and apparently couldn't resist the urge to doodle all over the slide like a caffeinated toddler with a red marker. The diagram shows how Copilot supposedly grounds AI responses using retrieval from enterprise sources (SharePoint, Microsoft 365, Internal Docs), but those aggressive red circles screaming "Retrieval API," "SharePoint," and "Combigent, veritable" (yes, combigent ) make it look less like professional documentation and more like a crime scene investigation board. The irony is palpable: you're trying to explain how your AI produces "verifiable" answers while simultaneously circling random words like you're not entirely sure what they mean yourself. Nothing says "enterprise-grade AI solution" quite like documentation that looks like it was annotated during a panic attack. Also, "combigent" isn't even a word—maybe the AI wrote this slide too and nobody bothered to ground that response. Fun fact: In RAG (Retrieval-Augmented Generation), "grounding" means anchoring AI responses to actual retrieved data instead of letting the model hallucinate. But when your documentation itself looks hallucinated, we've got bigger problems.

Before AI: A handful of indie devs grinding away at their laptops, while a modest group of paying users actually valued the niche problems being solved. There was balance in the force. After AI: The market got absolutely flooded with indie developers armed with ChatGPT and Cursor, all churning out "micro SaaS" products faster than you can say "npm install." Meanwhile, the paying users? They've been diluted into oblivion, scattered across thousands of half-baked AI-generated tools that solve problems nobody actually has. The AI gold rush turned every developer with a weekend free into a SaaS entrepreneur. Now we've got 10,000 "AI-powered productivity tools" competing for the same 50 people who are still willing to pay for software. The barrier to entry dropped so low it's basically underground. Good luck finding product-market fit when everyone and their bootcamp buddy is shipping the same vibe-coded MVP that "uses AI to revolutionize [insert mundane task]."

The perfect comparison doesn't exi— oh wait, it does! "Vibe coding" with AI tools is basically gambling with extra steps. You trade real programming skills for the dopamine rush of watching the cursor blink while an AI model hallucinates your next function. That feeling when you're absolutely convinced the next prompt will fix everything is eerily similar to thinking your next pull on the slot machine will make you rich. Meanwhile, actual software engineers are watching prompt engineers with the same expression casino dealers have when someone explains their "foolproof system." And that last row? Pure gold. Nothing quite captures the existential crisis of modern development like realizing you just spent 4 hours crafting the perfect prompt when you could've just written the damn code yourself.

Chrome tabs and AI models - the two horsemen of RAM apocalypse. ChatGPT casually using 13.8 GB of memory like it's nothing, while your computer quietly weeps. Remember when we thought 4GB was excessive? Now our browsers are out here consuming memory like tech bros at an all-you-can-eat buffet. Your PC isn't running an AI assistant - it's financing its therapy sessions.