Yes technically it is RAG, but a lot of the community is associating RAG with vector search specifically.
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But realistically lots of RAG systems have LLM calls interleaved for various reasons, so what they probably mean it not doing the usual chunking + embeddings thing.
Hype. There's nothing wrong with using, e.g., full-text search for RAG.
But I do think there is a qualitative different between getting candidates and adding them to context before generating (retrieval augmented generation) vs the LLM searching for context till it is satisfied.