RAG
RAG knowledge systems that retrieve the right information, cite sources, and respect permissions — ingestion, embeddings, hybrid search, reranking, citations, permission models, and the evals that prove retrieval quality before launch.
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Hybrid Search for Production RAG: The BM25, Vector, and Rerank Rule
Use hybrid search when vector-only misses exact terms. Compare BM25, vectors, fusion, reranking, evals, and the production logging gate.
RAG Evaluation Metrics Before Launch
Use a production RAG eval gate for retrieval quality, groundedness, answer correctness, answer relevance, and regression risk.
Pgvector vs Pinecone for Production RAG
Choose pgvector when retrieval belongs in Postgres. Choose Pinecone when scale, namespaces, or managed ops justify a separate vector system.
One letter, every week. Working systems — not hot takes.
Build logs, agentic engineering decisions, agent failures, evals, and what survives real users. Sent weekly, never more.