03How do you choose chunk size and decide between dense, sparse (BM25), and hybrid retrieval?▼mediumCohereGleanDatabricks2 repliesunlockedThe two knobs that make or break a RAG system, and the ones candidates hand-wave. The signal is tuning chunking against recall and knowing exactly what dense retrieval misses that BM25 catches. Here is the reasoning, not the rules of thumb.Open full answer →
25What is the difference between sparse and dense embeddings, and why does hybrid retrieval combine them?▼mediumCohereGleanMicrosoft2 replies◆ premiumDense vs sparse is the core retrieval tradeoff, and 'just use embeddings' silently loses every exact-match query. The signal is knowing what each representation captures and why production blends them. Here is the answer.Open full answer →
72How do you tune the fusion weights between lexical and vector retrieval, RRF k versus a learned alpha?▼hardCohereGleanAWS1 replies◆ premiumHybrid retrieval only beats either method if the fusion is tuned. The signal is knowing why you cannot just add BM25 and cosine scores, how RRF's k constant behaves, and when a learned weight beats rank fusion.Open full answer →
88Design an enterprise semantic search system over a company's internal documents and tools.▼hardGleanMicrosoftGoogle1 replies◆ premiumEnterprise search lives or dies on permissions, freshness, and connecting to thirty messy SaaS sources; retrieval quality is table stakes. Learn how to fan out across connectors, enforce per-user access at query time, and blend lexical with vector search for results people trust.Open full answer →
