03How do you choose chunk size and decide between dense, sparse (BM25), and hybrid retrieval?▼mediumCohereGleanDatabricks2 repliesunlockedThe two knobs that decide whether a RAG system works, and the two candidates tend to gloss over. The signal is tuning chunking against recall and knowing precisely what dense retrieval drops that BM25 recovers. 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 versus sparse is the core retrieval tradeoff, and 'just use embeddings' quietly 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 when the fusion is tuned. The signal is knowing why you cannot simply 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 wiring into 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 →
