Interesting! So you basically got a LM to rephrase the search phrase/keys into the style of the target documents, then used that in the RAG pipeline? Did you do an initial search first to limit the documents?
IIUC they're doing some sort of "q/a" for each chunk from documents, where they ask an LLM to "play the user role and ask a question that would be answered by this chunk". They then embed those questions, and match live user queries with those questions first, then maybe re-rank on the document chunks retrieved.