Popular Lesson
Select predefined styles for NotebookLM responses to fit different goals
Set up custom instructions to guide NotebookLM’s tone and perspective
Use sample prompts to create your own specific directions
Choose the ideal response length for summaries or detailed answers
Apply these settings for both individual and shared notebooks
Improve productivity by matching AI answers to your workflow
In this lesson, you’ll see how to adjust the way NotebookLM answers your queries using customization tools available—particularly in NotebookLM Plus. NotebookLM lets you shape your notebook’s voice by switching between preset styles such as “Analyst” for business insights or “Guide” for help centers. If those presets aren’t specific enough, you can write your own custom instructions, giving you control over the notebook’s role, tone, or output. This means you can ask for academic-level explanations, quick business summaries, or even responses as a fictional character—whatever your project calls for.
You’ll also find out how to manage the length of NotebookLM’s answers, making it simple to receive brief summaries or more in-depth content as needed. These customization features support efficient workflows across business, research, writing, or team collaboration. If you want a consistent, tailored experience that matches your purpose, learning these skills will make NotebookLM a more powerful tool in your day-to-day work.
Anyone seeking to make AI-generated notes more effective and relevant will benefit from this lesson. You’ll find these techniques helpful if you are:
Customizing the style and length of your notebook responses is a valuable step whenever you want more control over how AI serves you or your team. Use these settings when preparing board meeting materials, creating documentation, researching, or coaching. For example, a marketing manager might set the style to “Analyst” for strategic reporting and then switch to “Guide” when building a customer FAQ. Writers and educators could configure a concise response for quick feedback, or longer explanations for lessons. This flexibility ensures NotebookLM matches your workflow rather than forcing you to adapt to it.
Before customization was available, NotebookLM responses were generic and required manual editing to fit specific tasks or audiences. Now, by choosing styles or adding your own instructions, you streamline the process—saving valuable time and reducing repetitive tweaks. For instance, setting a short answer as the default provides instant summaries ready for meetings, while a custom instruction like “Act as a senior editor” ensures feedback is professional and targeted.
Workflows benefit from having AI that understands context and priorities. You don’t have to repeatedly prompt for tone or brevity; NotebookLM remembers your settings. Over time, this leads to more consistent and reliable outputs, reducing the need to reformat, expand, or shorten responses after the fact.
Try customizing a notebook for your specific needs:
Once you’ve saved your settings, ask NotebookLM a question relevant to your project. Review the response and compare it to answers from a “Default” notebook—where do you notice differences in style, focus, or length?
This lesson is a key part of learning to make NotebookLM work for your unique projects, building on your earlier understanding of gathering and organizing information. Next, you’ll look at sharing options and analytics for collaboration and tracking. Mastering response customization ensures that your notes and summaries align with your goals. Continue with the next lesson to explore how you can work with others and measure the impact of your AI-generated insights across team and organizational workflows.