The description seems to invert RAG: RAG (simplified a bit) conducts a search, presents the results to an LLM, and then the LLM produces output based on the search. In GAS as described the LLM analyzes the input query to generate the search query, then a search is run, and the results of the search are presented to the user. With GAS, you always get specific authoritative (to the extent that describes the universe searched) documents, any hallucination will impact document selection not correctness of info. Wtih RAG you get an LLM analysis of potentially many authoritative (with the same caveats as before) documents, but hallucination can affect the accuracy of the presented response as well as its relevance.