From a broad request to related questions
A person asking for a suitable accounting service may need to compare industry experience, price, location, software support and reporting requirements. Those are different information needs within one decision. A research worksheet should preserve them separately.
Google documents that its AI features may use a query fan-out technique, issuing multiple related searches across subtopics and data sources. That describes those features; it does not reveal the exact searches behind every generated answer or prove that other products behave identically.
Build a worksheet
- Original task: write the person’s question exactly.
- Decision dimensions: identify the facts needed to choose well.
- Related questions: write a small set for each dimension.
- Observed sources: record pages the system visibly cites or surfaces.
- Evidence gaps: note unanswered questions and unsupported claims.
Label your related questions as your own research hypotheses. Unless the product exposes its query activity, do not describe them as the system’s actual internal fan-out.
Use the worksheet to improve coverage
Look for a genuine unanswered need. A service page might explain what is included, while a guide explains how to choose and a case study shows a result with context. Those formats should exist because they help a user complete the decision. Publishing multiple thin pages for near-identical queries creates little useful coverage.
Measure the result
Choose a stable prompt bank before making a change. Record whether later answers address the missing decision dimension and whether the supporting source changes. Repeat over time and note product changes or other edits that could explain the result.
This is a research planning method, not a claim that a fan-out worksheet guarantees a recommendation. Pair it with consistent measurement and a controlled experiment.
References: Google Search: AI features and your website · LLM Mastery: the book.