Retrieval-Augmented Generationconcept
RAG retrieves relevant context chunks for a query, assembles them into a prompt, and asks an LLM to generate an answer — fresh on every query.
RAG grounds LLM answers in external knowledge and reduces hallucination versus parametric-only generation. It is the dominant runtime-knowledge pattern SKCE contrasts itself against.
Where it appears
- Contrasted in every SKC blog post
- The 'runtime tax' the compiler eliminates
Descend
Prerequisites
Dependencies
- —
Foundations
Historical evolution
Introduced 2020; became the default enterprise LLM pattern by 2023. SKCE argues it is structurally an interpreter — re-deriving meaning every query.
Implementation details
SKCE's explorer does zero RAG at runtime; the compiled curriculum is the static alternative.
Sources
- [2026-07-11-knowledge-compiler-compiling-human-knowledge-into-static-semantic-artifacts] 2026-07-11-knowledge-compiler-compiling-human-knowledge-into-static-semantic-artifacts
- [2026-07-11-knowledge-compiler-compiling-human-knowledge-into-static-semantic-artifacts] 2026-07-11-knowledge-compiler-compiling-human-knowledge-into-static-semantic-artifacts