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When ChatGPT struggles with a complex task, make the request more specific and match the work to the right feature: use Deep research to synthesize multiple sources, file uploads to work with documents, and Data analysis to examine structured data. Then check what it covered, what it assumed, and whether the result supports your decision. Tool access and limits vary by account, plan, region, and workspace settings.
First, identify what is making the task difficult
“Complex” can mean several different things: the answer requires current information from many sources, the important details are buried in documents, the task involves calculations across a spreadsheet, or ChatGPT is being asked to do too much at once. Identify the bottleneck before changing the prompt. A quick factual lookup, a document extraction, and a multi-source investigation need different inputs and workflows.
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- Need a quick fact? Standard chat or Search may be sufficient.
- Need a researched answer combining sources? Consider Deep research.
- Need to summarize, compare, or extract from files? Upload the relevant documents and specify the job.
- Need calculations or patterns in a table? Use Data analysis and state the columns and operations.
- Need ChatGPT to take actions online? Agent mode may be relevant, but narrow the task and supervise it.
ChatGPT’s available tools and capabilities depend on subscription level and settings. See the ChatGPT Capabilities Overview for the feature overview.
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Choose the workflow that fits the work
| Workflow | Best suited to | What to provide or do | What to check |
|---|---|---|---|
| Standard chat or Search | A contained question or quick lookup | Ask the question directly; add context if the answer depends on it. | Whether the answer addresses the exact question and, for information that needs verification, whether its sources support it. |
| Deep research | Multi-step questions that require combining and analyzing multiple sources | Describe the desired report, scope, context, and relevant sources. Review the proposed plan, steer the work if needed, and check the cited report. | Whether the sources are appropriate, important angles are covered, and the citations support the conclusions. |
| File uploads | Synthesizing, transforming, comparing, or extracting information from documents | Upload the relevant files and specify which sections or information to use and what output you want. | Whether the requested passages or documents were actually covered, especially with large, complex, or image-heavy files. |
| Data analysis | Calculations, groupings, and other analysis of structured data | Provide a clear table with descriptive headers and one record per row; name the columns and operations you want. | The code, outputs, assumptions, and whether the method fits the question. |
| Agent mode | Tasks that involve taking actions on websites | Give a narrow prompt and enable only the apps needed. | Monitor its actions and stop the task if anything looks suspicious; safeguards do not eliminate all risk. |
Deep research can draw on public websites, uploaded files, and eligible connected apps. Connected-app access depends on availability, plan, region, settings, and permissions; its research uses available read actions, not app write actions. For current details, consult OpenAI’s Deep research in ChatGPT help article.
#1 Best Overall
Make the request concrete before you start
A broad instruction such as “analyze this” leaves the scope and success criteria unclear. Ask for an observable deliverable and specify what belongs in it. For example:
“Compare the attached proposals for a non-technical manager. Return a table of their costs, commitments, and unresolved questions. Use only the proposals, cite the page or section for each finding, and mark information they do not state.”
For a research report, name the question, audience, date or geographic scope if relevant, and the kind of evidence you want. For a document task, say which files or sections matter and whether you want a summary, comparison, or exact extracted passages. For a spreadsheet, identify the columns and the calculation or grouping to perform. OpenAI’s Deep research guidance specifically recommends describing the desired outcome and context; it also lets users review and steer the proposed plan.
Work with documents by assigning them a specific job
File uploads are useful for synthesis, transformation, and extraction—for example, comparing documents, summarizing papers, or locating passages. Tell ChatGPT what to do with the uploaded material rather than relying on the file alone to imply the task.
- Choose the relevant files. Upload the documents that contain the evidence needed for the answer.
- Set the scope. Name the sections, pages, or topics to focus on, if you know them.
- Specify the output. Ask for a comparison, summary, extracted list, or another defined result.
- Check coverage. Verify important claims against the original documents, particularly when the material is long, visually complex, or contains many files.
An upload completing successfully does not prove that every part of a large, complex, image-heavy, or poorly structured file was analyzed. If an answer seems incomplete, ask about particular sections or passages, or split the material into smaller files. OpenAI describes the supported file workflows in How does the new file uploads capability work?
Prepare spreadsheets and verify the analysis
Data analysis works best when the input is organized as a table: use descriptive column headers and one record per row. Tell ChatGPT which fields to use and what result you need—for example, a total by category, a comparison across groups, or a chart of a specific measure.
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- Clean up the table enough that column names and rows clearly represent the data.
- State the intended calculation, grouping, filters, and output.
- Ask to see the method when the choice of calculation matters.
- Review the generated code, results, and assumptions before relying on them.
The Python environment used for Data analysis cannot make external web requests or API calls. Supply external data yourself or use a connected source that is available to your account. Supported formats and limits vary with model, plan, workspace settings, and account capabilities; a successful upload alone does not confirm that the entire file was analyzed. See Data analysis with ChatGPT for OpenAI’s guidance.
If the answer is still incomplete, reduce the scope
Do not assume a polished response means the whole task or file was covered. Make the next request narrower and easier to verify.
- Ask about one specific sheet, section, range of rows, or set of columns.
- Split an oversized or visually complex file into smaller parts.
- Request the evidence or passages behind a conclusion.
- For multi-source research, inspect the plan and cited report; redirect the work if it is missing an important angle.
- For calculations, ask ChatGPT to show or change the method if its assumptions do not fit the question.
These steps improve the chance that the result addresses the part you need, but they do not make every answer complete or correct. Check consequential findings against the source material and your own requirements.
Keep online actions narrow and supervised
If a task involves ChatGPT acting on websites, use agent mode only with a clearly bounded goal. OpenAI recommends narrow prompts, limiting enabled apps to those needed, and stopping the task if something looks suspicious. Safeguards are not a guarantee against unintended outcomes. Availability, message limits, and workspace controls can change; consult the current in-product details and OpenAI’s ChatGPT agent guidance.
Check which features your account can use
Deep research, connected sources, other tools, and their usage limits are not necessarily the same for every user. They can depend on plan, country or territory, account, workspace controls, and permissions. If a feature or source is missing, check your account’s available tools and workspace settings rather than assuming it is available universally.
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