Research and Summarisation
This lesson shows how to move from source collection to a usable brief: extracting key facts, comparing options, and turning a long document set into an actionable summary.
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Key takeaways
- Chunk long source sets into controlled batches before asking for synthesis.
- Separate extraction, comparison, and recommendation into distinct passes when the material is dense.
- Preserve citations or source references whenever the output may inform real decisions.
Step-by-step workflow
- Collect and label the source documents so the model can distinguish background, current facts, and decisions needed.
- Run an extraction pass to pull out the key facts, constraints, and open questions from each source.
- Run a comparison pass that forces the model to lay options side by side instead of blending them together.
- Ask for a short decision brief with next actions, risks, and information gaps.
- Keep the final output anchored to the source set so updates can be handled quickly when documents change.
Companion notes
Add summary templates, comparison tables, or briefing-note formats here after the final files are prepared.
Recommended tools
- A model interface that handles long documents or structured uploads
- A spreadsheet or table workspace for comparison outputs
- A final human review pass before research-based recommendations are circulated
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