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Katie Academy

04

Deep research

Use ChatGPT’s research workflow deliberately: shape the objective, review the plan, provide the right inputs, and read the report critically.

Module 04 is about research orchestration rather than quick retrieval. The reader learns when deep research is worth using, how to define the task well, how to steer the plan, and how to review the finished report like an editor rather than a passive recipient.

Module summary

The value of deep research is not that it makes judgment unnecessary. It is that it can handle broader, slower, multi-source synthesis when the objective is well defined and the output is reviewed carefully. These lessons teach both setup and skepticism.

Lessons in this module

  1. search-vs-deep-research - Choose deep research only when the task genuinely needs broader synthesis than search can provide cleanly.
  2. writing-a-strong-research-objective - Give deep research a real objective so it knows what success looks like.
  3. reviewing-the-research-plan - Use the plan stage to fix scope, source strategy, and output quality before the report is written.
  4. using-files-and-apps-in-research - Use files and connected apps to improve research context without drowning the workflow in noise.
  5. reading-and-exporting-the-report - Read the report like an editor, then export it into an artifact that fits the next decision.

How to use this module

Read the lessons in order and keep the scale of the task in mind. Deep research is overkill for many small questions. Use this module when the work is broad enough that quick search starts to feel fragmented or repetitive.

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Prerequisites

  • Module 03