I Almost Gave Up on Gemini Notebooks, But Then I Found This Feature

While I’ve long wanted to organize my Gemini chats and files into projects, when the feature arrived like Gemini NotebooksAt first I was disappointed.

However, after testing the feature using Gemini and NotebookLM, it is more useful than I expected.

When I envisioned a projects feature in Gemini, I wanted it to be a useful place to organize files and chats into folders. This was based on me experience with claudeespecially its own projects feature, which makes it easy to organize files and chats in a specific folder.

But when Notebooks came to Gemini, I didn’t enjoy their NotebookLM integration. It seemed like it was just a way for Google to push users to use both products instead of perfecting them separately.

The fact that your Gemini Notebooks also automatically sync with NotebookLM can be a drawback since you don’t have an unlimited number of notebooks available for your account.

After using the feature a bit more for a few days, I came to appreciate its approach to organization, even if it wasn’t exactly what I expected. However, that’s when I realized what these notebooks could do for my NotebookLM research that I really came to value the integration of the two tools.

When using Gemini Notebooks, I noticed that my AI chats were synced with NotebookLM as the source. This may seem redundant at first, since NotebookLM also has chatbot features, but it unlocks a powerful tool that NotebookLM doesn’t really have: web access.

NotebookLM relies on its sources, which means it can’t pull information from the web to add context to your answers. This is useful when trying to prevent hallucinations, but can limit the insights of the AI ​​tool.

Once I realized that my Gemini chats were syncing as NotebookLM feeds, I figured out how to use these chats to add context. NotebookLM can extract links from the web that you can use as sources, but this is a somewhat complicated process that doesn’t always show the best information.

It also requires that there is already a source available on the topic, which is harder to find when dealing with a specific context. I also discovered that it’s not always easy to find sources relevant to your local context if you don’t stay in a Western market.

But with my Gemini chats, I can now add context without needing to add a separate note or source to my notebook. I can also troubleshoot issues with Gemini and apply the solution to my NotebookLM projects.

Importantly, only chats within Gemini Notebooks sync with NotebookLM. You can also select which chats you want NotebookLM to use for a response or delete a specific chat entirely.

The first NotebookLM project where this feature was a big help was my garden care notebook. In it I store information related to the care of the plants in my garden.

With Gemini I could add the context that I live in Cape Town, South Africa. I then asked the AI ​​how often I should water a specific plant in my garden during the summer. I could use this context, including the lack of precipitation in my region during the summer, to plan a watering schedule for the plant.

I also used it to find out why another plant had yellow leaves. While most sources mentioned possible root rot, you could add context about a recent heat wave. The AI ​​concluded that heat stress was the most likely culprit based on my watering habits.

Back in NotebookLM, I was able to generate a more accurate watering schedule based on my sources and my Gemini chats. This turned out to be more in line with the real-world requirements of my plants than the context-free suggestions from the sources. I also finally got a watering schedule for my lawn, which no source was able to determine before.

My next project is to create a NotebookLM hub to explore chronic kidney disease in cats, as my cat recently went from Stage 1 to Stage 2. Gemini’s ability to easily add context will be helpful as I will be able to use information about my cat without needing to upload it separately.

While Gemini’s propensity to ask follow-up questions sometimes annoys me, it’s also helpful to see where you might have gaps in context.

The Gemini Notebooks aren’t the project feature I envisioned, but maybe that’s a good thing. After all, they offer something a little different.

The characteristic is not without its flaws, as Gemini still has a habit of making mistakes. For example, I spent about 10 minutes arguing with him about identifying a plant based on several images.

Overall, though, it provides organizational features while adding useful context to NotebookLM with little effort. However, as with any AI tool, it is still important to check the accuracy of its results.