i found a github repo that teaches you to build production RAG systems the way actual companies do it it's called production-agentic-rag-course. here's what you are going to learn: week 1: docker, fastapi, postgresql, opensearch, airflow week 2: automated arxiv paper ingestion pipeline week 3: bm25 keyword search foundations (before touching vectors) week 4: hybrid search with embeddings + rrf fusion week 5: complete rag with local llm and streaming responses week 6: langfuse tracing + redis caching for production monitoring week 7: agentic rag with langgraph + telegram bot what i like about this approach is the sequencing most tutorials skip straight to vector search and call it a day. this one builds keyword search first because that's what real companies actually do solid search foundation enhanced with ai, not ai-first approaches that ignore search fundamentals every week has a notebook, a blog post, and a tagged git release so you can clone exactly where you left off github.com/jamwithai/product… one thing is clear and its that if you want to build real ai systems, you have to understand the plumbing first. the people who skip to the fun parts are the ones whose agents break in production