Self-Ask Prompting

Self-ask prompting is a reasoning pattern in which the model explicitly asks itself follow-up questions before answering a composite question. The prompt instructs the model to decide whether the question needs sub-questions; if so, ask and answer them first, then compose the final answer from those sub-answers. It bridges multi-hop questions that the model might otherwise collapse into a single shallow response. Self-ask pairs well with a search or retrieval tool — each sub-question can trigger its own retrieval — producing answers that cite grounded intermediate facts rather than hallucinated leaps. It is less useful for atomic questions where sub-questioning only adds latency.