Lesson 344 of 2116
Deep Research Workflows: Multi-Hop Questions Done Right
Deep research tools like GPT Deep Research and Gemini Deep Research can run 30-minute multi-hop investigations. Here's how to brief them so the output is usable.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1What 'deep research' actually means
- 2deep research
- 3multi-hop reasoning
- 4research brief
Concept cluster
Terms to connect while reading
Section 1
What 'deep research' actually means
Deep research modes use an agentic loop: the model forms a plan, spawns sub-queries, reads pages, and revises its plan as evidence accumulates. Instead of one-shot answers, you get a 5-to-30-minute investigation with citations. The output is only as good as the brief you wrote.
The brief that separates good output from generic output
- 1State the decision the research will inform — not just the topic
- 2Name the audience and their prior knowledge
- 3List 2 to 4 specific sub-questions
- 4Specify source preferences (peer-reviewed, industry, regulatory, dated after X)
- 5Declare what counts as 'enough' — 5 sources? 20? A cited timeline?
Source triangulation
A deep research report that cites one blog and one press release is not research — it's a reading list. Require the model to triangulate: every load-bearing claim must cite at least two independent sources, and those sources must not both derive from a single origin piece.
Key terms in this lesson
The big idea: deep research tools reward specific, decision-shaped briefs. Vague prompts produce plausible-sounding mush; crisp briefs produce memos you can actually forward.
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