Document summarization is one of the most universally useful AI capabilities — and one of the easiest to get wrong. A hallucinated or incomplete summary can cost you more time than reading the original document. Here's how to do it right.
Why Summarization Goes Wrong
AI summarization fails in predictable ways:
- Hallucination: The model adds information that isn't in the document
- Omission: Key points are skipped because the model judged them less important
- Over-compression: The summary is so brief it loses critical nuance
- Context window overflow: For long documents, the model can only "see" part of the text
Understanding these failure modes is the first step to avoiding them.
The Right Prompt Structure for Summaries
Never just paste a document and say "summarize this." Give the model a job:
You are summarizing the following [document type: research paper / legal contract / meeting transcript / report].
My goal: [what decision or action this summary will inform]
My role: [your role and relevant background]
What I need from this summary:
- [specific thing 1, e.g., "the main argument and supporting evidence"]
- [specific thing 2, e.g., "any numbers, deadlines, or commitments"]
- [specific thing 3, e.g., "risks or caveats the author acknowledges"]
Format: [bullet points / structured sections / 3-paragraph prose]
Length: [your target length]
Do not include anything not explicitly stated in the document. If something is unclear, flag it rather than infer.
[DOCUMENT]
...
The instruction "do not include anything not explicitly stated" is particularly important — it significantly reduces hallucination.
Handling Long Documents
For documents longer than the model's context window, you have three options:
Option 1: Chunked Summarization
Divide the document into sections, summarize each separately, then summarize the summaries. This works well for documents with clear structure (chapters, sections).
Option 2: Targeted Extraction
Instead of summarizing everything, identify the sections most relevant to your question and only summarize those. "Summarize only sections 3 and 5 of this report, which cover financial projections and risk factors."
Option 3: Q&A Instead of Summarization
For very long documents, ask specific questions rather than requesting a general summary. "Based on this document, what are the three most significant risks identified?" This forces the model to search for specific information rather than trying to compress everything.
Document-Type Specific Tips
Research Papers
Ask for: abstract equivalent (1 paragraph), main methodology, key findings, limitations acknowledged by the authors, and implications for practitioners. Always verify numbers and statistics against the original.
Legal Contracts
Ask specifically for: key obligations of each party, payment terms, termination clauses, liability limits, and any unusual provisions. Always have a lawyer review any legal summary before acting on it.
Meeting Transcripts
Ask for: decisions made, action items with owners and deadlines, open questions requiring follow-up, and any significant disagreements.
Financial Reports
Ask for: headline metrics vs. prior period, management commentary on performance, forward-looking statements, and risks disclosed.
Verifying Your Summary
For any summary you plan to act on:
- Spot-check 3-5 claims against the original document
- Ask the model "what parts of the document did you find most difficult to summarize accurately?"
- For critical summaries, run the same document through two different prompts and compare outputs — discrepancies reveal uncertainty
