RAG
Curated by @tripp
Updated Jun 7, 2026
A comprehensive course intro in RAG (Retrieval Augmented Generation).
Learning is better together
Bring a question from this course or share what you made with other learners.
Quality
Scored on six categories — citations, structure, content richness, retrieval-readiness, scaffolding, and writing quality.
How densely lessons cite external sources, and how varied those sources are.
Module balance and reasonable lesson sizing.
Code examples, diagrams, and math — the multimodal payload.
How well-sectioned lessons are for search, citations, and deep links.
Models used
Models the creator uses in this course — chat, study guides, flashcards, ingest. Updated when the listing is republished.
- opus-4.8Lesson & course chat
anthropic/opus-4.8
Syllabus
Folder tree from your library — expand modules to see lessons.
View full syllabusChangelog
- v1.22026-06-23
Subscription email test — please ignore, this is a wiring check.
- v1.12026-06-18
New Module 04 lesson: "Case study — GBrain, a hybrid + graph brain in production" — a teardown of a real system tying together hybrid search, RRF, reranking, query transformation, and a knowledge graph, with a runnable multi-signal fusion demo and 5 flashcards.
- v0.12026-06-07
Initial publish — first version of this listing.
Attribution
LearnOS is a learning workspace, not a content host. This listing curates external resources; original creators retain ownership. Learners may need to obtain materials separately where noted.