The clean marketing story is “we built oc-rag-forge by using oc-rag-forge.” The honest version is more useful, so here it is.
What dogfooding actually meant here
oc-rag-forge is a methodology skill — a tri-agent harness (Designer → Builder → Evaluator) plus reference docs on vector DBs, embeddings, chunking, and retrieval eval. It doesn’t ship a running RAG service; it ships the decisions and the eval discipline for building one. So “using it to build itself” can’t mean indexing a corpus and querying it. The corpus is the methodology.
Where the recursion is real:
- The decision trees came from real builds. The vector-DB tree
(
pgvectorfor small + already-on-Postgres,pineconefor managed scale,turbopufferfor object-storage economics,supabase-vectorsfor the Supabase stack) is the same one we’d walk on a client RAG app. We wrote it as the skill so we’d stop re-deriving it. - “Evaluate, don’t eyeball” is the whole point. The single most common RAG failure we’ve seen is a strong model (Claude) producing a confident answer over wrong or empty retrieved context — the generation hides the retrieval bug. oc-rag-forge makes faithfulness and context recall first-class metrics precisely because answer quality alone lies.
Where the dogfooding stops (and that’s fine)
oc-rag-forge’s own reference docs are not themselves served through a retrieval pipeline — they’re Markdown the model reads directly. We could have built a RAG index over opchain’s docs and called it “rag-forge running on rag-forge,” but it would have been theater: the docs are small enough that retrieval adds latency and failure modes for no recall benefit. The skill’s own vector-DB decision tree says don’t reach for a vector DB when a direct read wins — so honoring that is dogfooding, even though it means not using the flashy part.
The takeaway
Dogfooding is a quality signal, not a purity test. The useful version is: would you make the same call for a client? For the decision trees and the eval discipline — yes, every time. For forcing a vector DB onto a 30-file doc set — no, and the skill itself tells you why.
Build something with it: the AI recipes walk three multi-skill flows end to end, including shipping a RAG app in a week.