⭐⭐⭐⭐⭐ Great breakdown! The distinction you drew between representation (OKF) and retrieval + generation (RAG) clears up a lot of common confusion. I especially liked the emphasis on how metadata and YAML frontmatter can enrich contextual relevance without overcomplicating the stack. Your practical comparison really grounds the theory and proves that clean knowledge curation is what truly unlocks reliable RAG pipelines. Excellent write-up—looking forward to seeing how OKF adoption evolves in agentic workflows!
indiainfranotes
OKF and RAG both depend on metadata, but only one of them can be checked after the fact. If the knowledge object has no dataset version or source hash, the model can still retrieve a row that was edited after training. Which side of that split do you treat as the source of truth? iin1006h15