TL;DR for operators Enterprise RAG teams often treat retrieval quality as a graph-construction problem: extract more entities, more relationships, more summaries, and hope the answer appears somewhere in the resulting machinery. Clue-RAG suggests a more useful diagnosis: the failure is often not that the graph is too small, but that the system has chosen the wrong semantic unit for the job.1 ...
TL;DR for operators Ultra-large context windows are not a ceremonial funeral for retrieval-augmented generation. They are a price renegotiation. If your task is to analyse a bounded, self-contained document set — a contract bundle, diligence folder, policy manual, code repository, or technical appendix — a long-context model may now be the cleaner first option. The main benefit is not that it “knows more”. It is that it can inspect more of the original evidence without depending on a retriever to guess which passages matter. ...