Skip to module content
๐Ÿง AI Academy
0/91
Sign in
Module 06 ยท ~12 min

In-Depth Research With AI

The difference between asking AI a question and running AI research is the difference between a Google search and hiring an analyst for a day.

Reading progress
0/4 ยท 0%

The big idea

๐Ÿ’กKey idea
Match research depth to stakes: quick answers for curiosity, guided research for medium-stakes decisions, and Deep Research โ€” where AI autonomously searches, reads dozens of sources, and writes a cited report โ€” for high-stakes decisions. A great research brief, not a vague question, is what determines report quality, and every report still needs verification before you act on it.
Quick check
1 question ยท instant feedback
0/1
  1. Deep Research is most appropriate for:

Deep dive

4/4 open

Match the depth to the stakes. Quick answer: the model answers, maybe with one web search, taking seconds โ€” good for low stakes, curiosity, or definitions. Guided research: you direct multiple searches, ask for sources, and compare, taking 5โ€“15 minutes โ€” good for medium stakes like pricing or vendor shortlists. Deep Research: the AI autonomously plans, searches dozens of sources, reads, synthesizes, and writes a cited report, taking 5โ€“30 minutes of AI time โ€” for high stakes like market entry, competitor analysis, or major purchases.

Both ChatGPT and Claude have a Deep Research mode: you submit a brief, the AI often asks clarifying questions, then goes away and returns with a long, structured, source-linked report.

Deep Research quality is 80% brief quality. A good brief includes decision context (what decision this research informs), specific questions (3โ€“7 numbered questions you need answered), scope and constraints (geography, time period, company size, budget range), source preferences ("prioritize official/government sources; flag forum/vendor sources as lower confidence"), and output format ("executive summary, then one section per question, then a comparison table, then risks, cited inline").

Compare weak โ€” "Research the CRM market" โ€” with strong: a detailed brief naming the business (a 6-person marketing agency), listing 5 numbered questions about fit, pricing, integrations, real user complaints, and migration effort, specifying recency and output structure.

A cited report is not a verified report. Standard operating procedure: click 3โ€“5 of the citations behind claims you care most about and check the source actually says what the report claims, since AI occasionally over-summarizes or attributes wrongly.

Check source dates โ€” pricing and features from years ago are landmines in a current decision. Run a red-team prompt asking a skeptical reviewer to identify the weakest, most likely outdated, or single-source-based claims.

For big decisions, cross-model check by running the same brief in the other assistant and investigating disagreements. Finally, ask the model to segregate FACT (directly sourced), INFERENCE (reasoned), and OPINION labels for its key findings.

Competitor teardown: run a Deep Research brief per competitor, paste all reports into one chat, and build a positioning map to find the gap you can own. Meeting prep: research a company and person before a call for recent news, product changes, and three intelligent questions. Content research: extract "the 5 most surprising, citable facts" from a Deep Research topic to use as post hooks. Living research: store reports in a Project or Notion and, when a decision resurfaces, ask AI to update the report with what's changed.

Research about laws, taxes, and regulations is where AI is most useful and most dangerous โ€” rules change and jurisdiction details matter, so use AI to build the map and question list, and use a licensed professional for the final answer.

Quick check
1 question ยท instant feedback
0/1
  1. The most important part of a research brief is:

Pitfalls & takeaways

Failure modes

  • Using Deep Research for trivial questions, or a quick answer for a major decision โ€” mismatching depth to stakes
  • Writing a vague one-line research question instead of a full brief with decision context and numbered questions
  • Trusting a citation without clicking through to check it actually says what's claimed
  • Missing outdated sources โ€” pricing and features from years ago can be landmines in a current decision
  • Treating AI research on laws, taxes, or regulations as final instead of having a licensed professional sign off

Durable takeaways

  • Three depths: quick answer, guided research, Deep Research โ€” match depth to stakes
  • Brief quality determines report quality: decision context, numbered questions, scope, source rules, format
  • Verify: click citations, check dates, red-team the report, cross-model check big decisions
  • Turn research into compounding assets: teardowns, meeting prep, living reports
  • Legal/tax research: AI maps the terrain, professionals sign off
Quick check
1 question ยท instant feedback
0/1
  1. A citation in an AI report means:

Do the work

๐Ÿ‹๏ธProve you learned it

Pick a real decision you're facing. Write a full research brief covering decision context, specific numbered questions, scope and constraints, source preferences, and output format. Run it through Deep Research, and once the report arrives, click through 3-5 of the citations you care about most and run a red-team pass asking what's weakest or most likely outdated.

0 chars
Quick check
1 question ยท instant feedback
0/1
  1. For a major decision, running the same brief through a second AI model is useful because: