LLM Marketing Evolved

Ah yes, the pinnacle of software engineering: using a multi-billion dollar AI model to add 1 + 2. That's like hiring a NASA rocket scientist to operate your toaster. The code imports OpenAI, sets two variables, then asks ChatGPT to perform basic arithmetic that the language could do natively with a simple + operator. Congratulations, you've just made the world's most expensive calculator with the worst possible performance. Next week: using quantum computing to check if a number is odd.

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!

The corporate data science dream team standing around watching one guy with Excel do all the actual work. Classic case of "we hired seven specialists with fancy titles to stare at a hole while the person who's been using VLOOKUP since 2003 actually solves the problem." This is why your company's $2M data infrastructure still ultimately feeds into someone's spreadsheet that crashes every third Thursday. The Excel guru probably makes half what the AI consultants do, but knows where all the bodies are buried in your database.

Modern problems require modern solutions! This dev is playing 5D chess with AI - opening tabs for ChatGPT, Gemini, Claude, Grok, and DeepSeek to ask them all the exact same coding question. Then the real programming begins: copy-paste each AI's answer into separate Python files, run them all, and cherry-pick the winner. It's basically Hunger Games for AI models. The ultimate "why debug your own code when you can make five AIs fight to the death for the correct solution?" approach. Bonus points for efficiency - why spend hours on Stack Overflow when you can delegate your decision paralysis to multiple neural networks simultaneously?

The duality of developer existence, captured in Shiba Inu form. On the left, we have the battle-hardened veteran—muscular, imposing, and completely unimpressed by technology that can't handle basic functionality. Meanwhile, the right side shows the innocent newcomer, blissfully celebrating an AI-generated website that probably has the structural integrity of a house of cards in a hurricane. The experienced dev knows that "generated in 5 minutes" means "will cause 5 months of debugging." The circle of life continues.

Ah, the modern developer's workflow. Empty try block, followed by a catch that just calls OpenAI to fix whatever broke. Why debug your own code when you can outsource your incompetence to an AI? Next up: a ChatGPT plugin that automatically adds this snippet to all your repositories. Efficiency through surrender.