Source-grounded AI can be more reliable than an open-ended chatbot because the workspace is built around material you choose. It still requires careful source selection, citation checking, and judgment.
Define the Research Question
Write one decision or question the project must answer. Add scope, audience, date range, and what would count as strong evidence. This prevents a notebook from becoming an unstructured document dump.
Choose Better Sources
Prefer official documentation, peer-reviewed research, recognized institutions, original datasets, and credible reporting. Remove duplicates and low-quality summaries. Confirm you have permission to upload each file.
Build a Source Map
Label sources by type, date, authority, and viewpoint. Ask the tool to identify agreements, contradictions, missing evidence, and terms that need definition.
Ask Verifiable Questions
Request answers with inline source references. Open the cited passage and read the surrounding context. If a claim cannot be traced, do not use it.
Create the Deliverable
Draft an outline, evidence table, and unanswered-questions list. Write the final analysis in your own words and link back to primary material.
Bottom Line
A grounded notebook improves traceability, not truth by itself. The quality of the answer still depends on the quality of the sources and the care of the reviewer.
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