The retrieval pipeline. Query → embed → vector search → rerank → inject into prompt → generate. Know each stage and what can go wrong at each. The pipeline looks simple but the quality is determined...

Build a RAG pipeline end-to-end. Ingest documents (PDF, HTML, markdown), chunk them (choose strategy based on document structure), embed with a chosen model, store in a vector DB, implement retrieval...

"Walk me through how you'd build a RAG system for [enterprise knowledge base]." Start with document analysis (format, structure, volume, update frequency). Choose chunking strategy based on document...