Working with documents¶

Registering notebooks and asking questions is the starting point. To get the most out of the system, it's useful to know some strategies that leverage session management, progressive research, and the ability to query multiple notebooks.

Conversational sessions¶

When Claude queries NotebookLM for the first time on a topic, it creates a research session. This session maintains context between subsequent questions, enabling progressive conversations within the same notebook.

Sessions remain active for the entire conversation with Claude. If you switch to a completely different topic, Claude may decide to create a new session by closing the existing one. This automatic behavior maintains response precision by avoiding confusion between different contexts.

To view active sessions:

Show me the active sessions with NotebookLM

To start over on a notebook while maintaining the same session identifier:

Reset the current session with NotebookLM

Progressive research¶

Instead of asking a single generic question, the most effective approach is to proceed through successive refinements, letting each answer inform the next question.

An example with technical documentation: 1. Give me an overview of the n8n installation options 2. What are the practical differences between Docker and npm? 3. For professional use with a team of 5 people, which approach is most suitable?

Each question builds on the previous answers, and NotebookLM constructs increasingly precise responses because it maintains the conversational context. This approach is particularly useful when exploring complex documentation or trying to solve intricate technical problems.

Querying multiple notebooks¶

One of the most significant features of the integration is the ability to work with multiple notebooks in the same conversation. NotebookLM alone doesn't allow querying multiple notebooks simultaneously: with the integration, Claude acts as an orchestrator and manages the switching between different notebooks.

A concrete example — analyzing documents contained in two separate notebooks.

1. Analyze the cases in the "AI Case Law" notebook
2. Now analyze the rulings in the "AI Case Law – 2025 Update" notebook
3. Compare the recurring patterns in the documents loaded in both notebooks

Claude keeps the results of the first analysis in memory and can compare them with those from the second, producing a comparative analysis based on sources from different notebooks. This approach was concretely tested in a comparative case law analysis on AI, described in the Use cases chapter.

Human review in the process¶

When working on complex analyses, human review between phases is essential.

The recommended method for multi-phase structured work is:

1. Clearly define objectives, methodology, and expected outputs before starting
2. Verify the results of each phase before moving to the next
3. Correct any inaccuracies immediately, to prevent them from amplifying in subsequent phases
4. Use direct verification on NotebookLM (by checking the chat history) to confirm source fidelity

This human-in-the-loop approach, where artificial intelligence works and the user validates, is the most reliable way to obtain accurate results from complex document analyses.

Optimizing requests¶

Result quality depends on question specificity. NotebookLM works best with precise and contextualized questions.

Less effective:

How does Docker work?

More effective:

In the context of installing n8n on Windows 11, what are the Docker commands needed to create and start the container?

Better precision in request formulation allows NotebookLM to retrieve exactly the relevant documentation sections, while vague questions return generic information. Automatic structuring improves any question, but starting from a precise request produces better results.

Information verification¶

The system is particularly useful as a fact-checking tool when writing documentation, technical articles, or training materials:

I'm writing that n8n supports up to 200 nodes in a single workflow. What do the documents say about this?

Claude queries the notebook and returns the response with citations, confirming or refuting the claim based on the documentation. If the information is not present, it explicitly declares so.

Similarly, you can compare information found in external sources with the documentation:

I read that to install n8n on Windows it's better to use WSL2 instead of Docker Desktop. What does the official documentation say?

The response distinguishes between what is documented and what is not, allowing you to separate opinions and informal advice from official guidance.