2.4 – Creating Notes Inside NotebookLM Lesson

Lesson Overview

This lesson focuses on the note-taking features inside Google NotebookLM, going beyond just interacting with AI. While AI summaries and suggestions can help accelerate your research, the manual notes feature lets you capture personal insights, strategies from experience, or content not included in your uploaded sources. You are not restricted to AI answers—NotebookLM gives you the best of both worlds by letting you take, organize, and format notes right alongside AI-generated content.

This approach is helpful for researchers, students, business owners, or anyone who wants a blend of AI support and their own thinking. For example, during competitive analysis, you might want to document insights from a meeting or your observations that the AI can’t directly access. Using manual notes lets you keep these unique perspectives inside your notebook and, if needed, incorporate them into your knowledge base as sources readers and AI can reference later.

Combining manual and AI-powered notes is a unique strength of NotebookLM, supporting everything from casual research to professional report building.

Who This Is For

If you want to personalize your research and capture original insights alongside AI work, this lesson is for you.

• Students taking research notes or preparing assignments
• Researchers capturing observations, hypotheses, or interpretations
• Content creators and journalists gathering information from multiple sources
• Professionals carrying out industry or competitor research
• Analysts summarizing findings from various documents and meetings
• Anyone who wants to organize and revisit their own thoughts within NotebookLM

How This Fits in a Workflow

Creating notes in NotebookLM is typically done as you review sources, generate AI summaries, or brainstorm ideas. You might use manual note-taking to save insights during your initial research phase or add reflections after interacting with the AI. For example, after prompting the AI for a summary, you record your own takeaways or copy specific details you find valuable. Later, you can choose whether any of these notes should be promoted to a “source” for AI to use in future analyses, like when building a study guide or drafting a client brief.

This process supports an iterative, flexible workflow: start with manual notes, get AI responses, combine them, and manage what material becomes part of your searchable knowledge base.

Technical & Workflow Benefits

The traditional way of capturing insights involved juggling separate documents—notes in Google Docs, research in bookmarks, and meeting takeaways in scattered files. NotebookLM streamlines all these steps by centralizing notes and sources within a single workspace. The benefit: you can write, edit, and organize your thoughts where you’re already working, reducing context-switching and lost details.

For example, a researcher benefits by copying portions of an AI summary directly into a manual note, annotating it, and then turning this annotated note into a source AI can reference in future queries. A team lead can gather meeting points as notes and instantly weave them into the collective research base. This method saves time, keeps essential insights close at hand, and increases the overall quality and relevance of your knowledge base.

Practice Exercise

Pick a topic you’re currently researching (such as a market trend or a class subject). In your NotebookLM workspace:

1. Open your notebook and review an AI summary of your sources.
2. Add a manual note: Write your own thoughts, copy a few key points from the AI, and use at least one formatting option (like a heading or a link).
3. Decide whether this note should remain as your reference or be converted into a new source.

Finally, ask yourself: Does having your own notes alongside AI responses help you organize your work or spark new questions to explore?

Course Context Recap

This lesson builds on your ability to gather and structure research in NotebookLM, expanding your toolkit beyond AI-generated answers to include fully customized, manual notes. Previously, you learned how to save and organize insights from AI; now, you have the flexibility to merge your own knowledge into the system. Up next, you’ll explore turning those organized notes into study guides and briefing materials, bringing you closer to a practical, polished research outcome. Continue to the next lesson to see how your notes can become structured deliverables within NotebookLM.