How I Vibe-Coded a Full-Stack AI Word Game — With Zero Web Dev Experience

I'm an ML/algorithm engineer. My day job involves training models, tuning embeddings, and writing Python scripts. I had never built a web app. No React. No CSS. No "deploy to production" experience beyond python app.py . But I had an idea: what if I could turn semantic similarity — the thing I work with every day — into a game anyone could play? The result is Hot and Cold Game , a daily word-guessing puzzle where AI tells you how "hot" or "cold" your guess is based on meaning, not spelling. Think Wordle meets word embeddings. I built the entire thing through vibe coding — using AI tools to handle the parts I didn't know, while leveraging my ML expertise for the parts I did. Here's how. The Idea: Making Embeddings Fun In my day job, I use text embeddings constantly. One day I was debugging a similarity search and noticed something: the distance between "ocean" and "wave" was small, while "ocean" and "bicycle" was huge. That's... basically a game. I knew about Contexto and Semantle — sim