RAG
Curated by @tripp
Updated Jun 7, 2026
A comprehensive course intro in RAG (Retrieval Augmented Generation).
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.
Frontmatter, learning objectives, resources, and practice sections.
Lexical variety, sentence rhythm, and absence of filler phrases.
Scored against the LearnOS course quality rubric. How this is scored →
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.
learnos://manual/c0023967-2617-4980-8854-f58d612b5bfe