When You See Purple On Landing Page

The irony is palpable! A job posting demanding "50% of code must be done by AI" while simultaneously requiring you to sacrifice your firstborn to the startup gods. Let me translate this corporate poetry: "We want cutting-edge AI integration, but also need you in an overpriced SF apartment, grinding weekends away while jet-setting to client sites. Your work-life balance? Sorry, that's not in our Jira board." The "vibe coding experience" requirement is just chef's kiss perfection. Because nothing says "we understand modern development" like demanding both AI automation AND soul-crushing overtime in the same breath.

Putting on glasses to transform from "LLM Engineer" to "Knows about openai, anthropic and google-genai package" is peak tech industry smoke and mirrors. It's like calling yourself a "Cloud Architect" because you once deployed a WordPress site to AWS. The glasses don't add intelligence—they just help you see through the BS of your own job title. Next time someone introduces themselves as an "LLM Engineer," ask them if they can actually explain a transformer architecture or if they just know how to copy-paste API keys.

That moment when your team casually mentions Jupyter notebooks in the standup and you're nodding along like you totally know what they're talking about. Ten years of development experience and somehow this popular data science tool completely flew under your radar. The tech world moves so fast that even seasoned devs have these knowledge black holes. Pro tip: Just smile and Google it later like the rest of us do. The alternative is admitting ignorance and watching the intern explain it to you with barely concealed pity.

The great developer migration of 2023 visualized. Massive crowd flocking to ChatGPT while one lonely soul still visits Stack Overflow. Remember when we had to actually read through 15 answers, each starting with "Actually, you shouldn't do it that way" before finding a solution that worked? Now we just ask the AI and get code that's wrong in exciting new ways instead of the familiar old ways. Progress!

When your AI pair programmer decides your codebase needs an "intervention"... 3,000+ lines of pristine, architecturally sound code that's completely non-functional. It's like hiring a interior designer who replaces your cozy but functional IKEA setup with museum-quality furniture you can't actually sit on. That moment when you realize Claude 4 has simultaneously solved and created all your technical debt in one go. Your git diff is now longer than the entire Lord of the Rings trilogy.

When your machine learning course gets too intense, so you take it to the next level—literally. This is what happens when someone takes "deep learning" a bit too literally. While neural networks are diving into layers of abstraction, this person is diving into a pool with their textbook. The irony is palpable—studying underwater won't make your AI algorithms any more fluid, but it might make your textbook unusable. Next up: "reinforcement learning" at the gym and "natural language processing" by shouting at trees.