Fridays project on vector stores will be "fire". @powerful-horse-58724 hooked me up with a new car, and I can't stop driving it. "What if your AI could instantly search through hundreds of pages of documentation and give you a precise, sourced answer in seconds — running entirely in the cloud, with no infrastructure to manage? That's exactly what this project demonstrates. A production RAG chatbot that takes a customer support question, semantically searches a pgvector database to find the most relevant content, then hands those results to Claude to generate a grounded answer — all orchestrated automatically on Union.ai. The key insight: we're not keyword matching. We're converting text into 384-dimensional vectors and finding meaning through geometry. And every step — embedding, retrieval, generation — runs as a tracked, cacheable, parallelizable task on Union's compute cluster.

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