Stop Prompting AI Summarizers With Just “Summarize This”

Most AI summarizers have the same hidden problem:

The output is only as useful as the question you ask.

If you upload a long document and type:

Summarize this.

you'll probably get something readable.

But readable isn't necessarily useful.

A research paper, technical document, meeting recording, and tutorial shouldn't all be summarized in exactly the same way.

I've been testing this with iWeaver AI Summarizer, which can process different types of source material.

Instead of changing tools for each task, I change the instruction.

Here are five patterns I find more practical.

1. The Decision Summary

Use this when a document exists because someone needs to make a choice.

Summarize this material around:
1. the decision that needs to be made
2. available options
3. evidence for each option
4. risks or unresolved questions
5. information still missing

Now the output has a job.

It isn't simply shorter than the source.

2. The Evidence Summary

This works better for reports and research.

Identify the main claims in this document.
For each claim, show the evidence or data used to support it.
Keep limitations and uncertainty separate from conclusions.

This can make it easier to identify which sections deserve verification in the original.

3. The “What Changed?” Summary

Useful when you already understand the topic.

Assume I know the basic background.
Focus only on new findings, changes, unexpected results,
and anything that would update my current understanding.

This removes a lot of introductory material you may not need.

4. The Action Summary

For meetings and operational documents:

Extract:
- decisions
- action items
- owners mentioned
- deadlines
- unresolved questions
- follow-up items

Do not turn general discussion into an action item.

That's very different from asking for a meeting summary.

5. The Learning Summary

When I'm learning something new, I want the opposite of aggressive compression.

Explain the material in this order:
1. core idea
2. concepts I need to understand first
3. how the parts connect
4. one concrete example
5. common points of confusion

The result may actually be longer than a standard summary.

That's fine.

Summarization Is an Output-Design Problem

This is the main lesson.

People often evaluate an AI summarizer by asking:

How well does it shorten a document?

I think a better question is:

Can I get the information into the structure required by my next task?

That's why multi-format tools are interesting.

With iWeaver, the source can be text, documents, webpages, images, audio, or video, while the result can be organized into formats such as summaries, notes, bullet points, outlines, and transcripts.

The input format and output structure don't have to be the same.

That's useful.

Try Changing the Prompt Before Changing the Tool

If your AI summaries feel generic, don't immediately look for another summarizer.

Take the same source and run it three times:

Summarize the key ideas.

Then:

Extract claims and supporting evidence.

Then:

Tell me what I should investigate next.

Compare the results.

You may find that the biggest improvement doesn't come from making the model “better.”

It comes from defining what the summary is supposed to do.

You can test these patterns with iWeaver's AI summarization tool or adapt them to whatever summarization workflow you already use.