What: The "Is Grep All You Need?" study wires both a literal grep tool and a vector-search tool into the same agents and runs 116 LongMemEval questions across them — measuring how each retrieval style holds up as irrelevant context is progressively added to the prompt.
Why: Vector retrieval has been the default for agentic search for years, but it pays for an embedding pass, a vector store, and an ANN index — costs that only buy something if the semantic match is doing real work. If grep is close to as accurate and more robust to noise, a whole layer of infrastructure becomes optional.
vs prior: Earlier RAG benchmarks compared retrieval algorithms on standalone retrieval quality (recall@k against a labelled gold set); this paper measures them inside an agent loop, where tool-calling style and harness design turn out to matter more than the algorithm itself.
Think of it as
Looking up a quote — Ctrl-F in the PDF vs asking a librarian to find books that "feel similar".
