Summarizing and rewriting text

1. Summarizing and rewriting text

Hello! Welcome to this video on summarizing and rewriting text.

2. Summarization tasks

Claude shines at transforming text: turning a long report into something that can be quickly scanned,

3. Summarization tasks

taking some dense technical docs and making them readable for non-technical teams,

4. Summarization tasks

or flipping formal writing into something that sounds more friendly. Claude's got us covered for all of this, and the best part is it preserves the key message while completely changing how it's presented.

5. Summarization techniques

Let's start with summarization. The most straightforward approach is simply asking Claude to summarize text, but we can make this much more effective by being specific about our requirements. We can control the length by specifying word counts, sentence limits, or paragraph constraints. We can also direct Claude's attention to specific aspects – perhaps we want to focus on key decisions made in a meeting, or action items from a project update. In the code example, we're asking for a concise 2-3 sentence summary of a report, focusing on updates.

6. Rewriting with system messages

So far, we've used the 'user' section in the messages passed to Claude. Now we'll explore how adding a system message can give us better control over Claude's output style and tone. Think of the system message as setting the personality and guidelines that Claude will follow throughout our entire conversation. We can specify whether we want professional business language, casual conversational tone, or technical precision. System messages will stay consistent throughout the conversation: once we set the tone, every response in that conversation will maintain that style. The code example shows this in action: we create a system message that tells Claude to be a professional editor focused on clear, engaging communication, then we add it to our messages array along with our user prompt.

7. Managing output length with max_tokens

To manage output length even more specifically, we use the max_tokens parameter. Roughly speaking, one token equals about four characters in English, though this varies. So if we set max_tokens to 150, we're looking at approximately 600 characters of output, which typically gives us about a paragraph. In the code example, we're setting it to 150 tokens for a quarterly report summary, which will give us that perfect paragraph-length output.

8. Key takeaways

Let's wrap up with key takeaways: we summarise when length overwhelms, we ask to rewrite when tone must change. Clarity in prompts, testing different values for max_tokens, and quick spot‑checks keep outputs sharp and faithful.

9. Let's practice!

Let's practice with some exercises.

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