John and Bobby broke down how RAG actually works and why the real battle isn’t the LLM, it’s the chaos sitting in PDFs, Excel files, post-job reports, random folder structures, and handwritten scans. They showed how extraction, chunking, and embeddings fall apart when data is messy, and why clean structure, good metadata, and consistent organization matter way more than people want to admit. They also hit on how tools like MCP and text-to-SQL let AI pull from WellView, production systems, and databases in one place, instead of everyone living in 20 different apps. The takeaway was simple: AI gets powerful fast when the data is ready, but if the inputs are junk, you’ll just get faster junk back.

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