When to use this
- Company deep dives
- Industry maps and competitive landscapes
- Earnings-season summaries across multiple names
- Policy or macro event impact
- Theme research (“who benefits from X”)
Step 1: Define the scope clearly
The single biggest lever on Deep Research quality is a well-scoped question. Tell it what to include and exclude:Step 2: Let it work, then read critically
Deep Research runs as a multi-step workflow, gathering evidence, cross-checking key figures, and assembling the brief. Important numbers are verified before they appear, and the full conclusions from each step are preserved in the final output, so nothing gets dropped on the way to the summary. When it finishes, read for evidence quality: are claims sourced, are figures cited, are the risks concrete?Step 3: Export the report
For anything long, save it:Step 4: Chain into specifics
Deep Research is often step one. Use its output to drive focused work:Common mistakes
- Vague scope. “Research AI” sprawls; “research US-listed AI data center infrastructure names and their power exposure” focuses.
- Reading only the summary. The value is in the evidence; skim the support, not just the conclusion.
- Not exporting. Long research you do not save is research you will redo.
Prompt variations
Related
- Deep Research Skill — the Skill reference
- Sector deep dive — sector-focused research
- Macro research — theme and policy research