Part 1
Designing a RAG System for 10 Million Documents
How to size, build and measure retrieval-augmented generation over 10M documents: ingestion, hybrid retrieval, reranking, ACLs, cost and evals.
Retrieval & RAG
Chunking, hybrid search, reranking and debugging retrieval-augmented generation.
Articles
Part 2
Debugging a RAG System That Gives Wrong Answers
A stage-by-stage method for localizing RAG failures: build a replayable failure set, attribute each case to a stage, fix the biggest bucket, and gate on it.
Part 3
Chunking Legal Contracts for Retrieval
Why fixed-size chunks fail on contracts, and how to chunk by clause with context headers, defined terms, cross-references and amendment lineage.
Part 4
BM25 vs Dense vs Hybrid Search: When to Use Each
How lexical, dense, learned-sparse and late-interaction retrieval fail differently, how to fuse them with RRF, and how to choose on your own traffic.
Part 5
Adding a Reranker and Proving It Helped
How to add a cross-encoder reranker to a RAG pipeline, size it, and prove the gain with paired offline evals, end-to-end checks and a guarded A/B test.