Jam with AI launches production RAG course

This is less a tutorial demo and more a production blueprint disguised as a course. The sequencing is the smart part: it treats search, ingestion, observability, and guardrails as the core curriculum, not optional extras.

• –The stack is refreshingly production-minded: Docker, FastAPI, OpenSearch, PostgreSQL, Airflow, Ollama, Langfuse, Redis, and LangGraph all show up in one coherent path.
• –The curriculum mirrors real failure modes, from messy ingestion to retrieval quality to tracing and caching.
• –The agentic layer is narrow and useful: query validation, document grading, and adaptive retrieval are the kinds of controls teams actually need.
• –Open-sourcing the code makes the repo useful as a reference implementation, and the traction suggests developers want this kind of full-stack RAG instruction.
• –The tradeoff is complexity, but that's the point: this is for developers who want the full system, not a weekend notebook.