The technique of generating hypothetical answers (or documents) from the query was first described in the "HyDE (Hypothetical Document Expansion) paper". [1]

Interestingly, going both ways: generate hypothetical answers for the query, and also generate hypothetical questions for the text chunk at ingestion both increase RAG performance in my experience.

Though LLM-based query-processing is not always suitable for chat applications if inference time is a concer (like near-real time customer support RAG), so ingestion-time hypothetical answer generation is more apt there.

1. https://aclanthology.org/2023.acl-long.99/