Query fan-out
An AI search system splitting one big question into several smaller searches, then combining what they find.
See it
What it is
Query fan-out is what happens when an AI search system turns one prompt into a batch of narrower searches. A request like 'best camera for hiking in rain under $1,000' can fan out into weather sealing, weight, current prices, lens availability, and comparison queries, then combine the evidence into one answer. Google uses the term itself for the background searches behind AI Mode and AI Overviews.
Reach for it when one query is too broad to retrieve good evidence in one pass. It works well for comparisons, planning, and questions with several constraints because each sub-query can retrieve a focused set of sources. For publishers, it also explains why a page can earn a citation without ranking for the user's exact wording: it answered one of the hidden sub-questions cleanly.
The gotcha is drift. If the generated searches quietly change the meaning, the final answer can be well sourced and still answer the wrong question. More queries also create duplicate results and conflicting evidence, so fan-out needs deduplication, source checking, and a final pass against the original constraints.
Ask AI for it
Build a query fan-out plan for this prompt. Extract every explicit constraint, generate 6 to 10 non-overlapping sub-queries that cover definitions, current facts, comparisons, exceptions, and primary sources, and show which original constraint each query serves. Run the searches in parallel in Google Search, deduplicate canonical URLs, and merge overlapping result lists with reciprocal rank fusion (RRF). Reject any sub-query that changes the user's scope. Return the query map, the evidence attached to each branch, unresolved contradictions, and a final answer checked line by line against the original prompt.