I’ve been using NotebookLM for years. It’s an excellent tool for grasping research quickly, especially when I’m learning about a new topic like an advanced smartphone processor or changes in AI models.
Lately, I’ve been using it to teach myself the background of how AI works.
Over time, one of my favorite features has been Audio Overviews. It’s an easy way to turn hundreds of hours of reading into something I can listen to while doing chores around the house or making breakfast.
A personalized podcast for learning — what’s not to like about it?
That said, after using NotebookLM for a while, I realized that audio overviews are one of the many features that make the tool special.
The features that keep pulling me back to the platform are the ones that don’t get talked about enough.
Between the source-grounded chats and Mind Maps that have become a regular part of how I research new topics and teach myself new concepts, these two features are what I rely on more than audio overviews.
Source-grounded chats make NotebookLM indispensable
Keep my research organized and answers grounded in sources
I spend a large part of my day reading GitHub updates, product announcements, and research materials before getting down to writing about it.
Collecting information has never been a particularly big challenge, but making sense of dozens of sources without losing track certainly is.
That specific problem is what NotebookLM solves for me.
I have a range of NotebookLM notebooks set up based on topics and things that I’m researching. When I come across something interesting or relevant, I add it to that specific notebook.
But when I have hundreds of sources in a specific notebook, it’s easy to lose track of where I got a nugget of information.
This is one of the most basic problems that NotebookLM solves, but it solves them beautifully.
For one, if I ask the AI a generic question, I know I’ll get a reliable answer since it is based completely on the documents and research links that I shared.
So if I ask for details about how a specific transformer works or a certain design decision was made, NotebookLM can point me to the exact sections in my research that support the response instead of giving me a generic answer or worse, hallucinating an answer.
That source-based answering saves me an incredible amount of time when I get around to writing.
As part of my business, I work with a lot of technical documentation that I need to be rock-solid about, to get grounded answers without opening a dozen or more PDFs at the same time.
NotebookLM doesn’t replace the work involved with research, but it makes the process much easier.
Mind maps help me see the bigger picture when I’m learning something new
The easiest way to research and learn something new
But as useful as source-based conversations are, there’s one more feature I find even more helpful in my daily research. That’s mind maps.
When I’m researching something new, or I’m trying to learn something, like my recent obsession with picking up Japanese, I want to learn small nuggets of information and understand how they relate to one another.
There are many approaches to this, and sure, you can read articles or books back-to-back, but mind maps solve that problem much better for me.
NotebookLM analyzes my sources, including the books I’ve uploaded to it, and it creates a visual overview that groups related ideas and connects them together.
Instead of thinking about everything I have to learn one document at a time, I can immediately see the broader theme and how these different concepts connect to each other.
That visual organization is known to be an excellent way of learning, and NotebookLM brings it to any document or research source that you might be working with.
One interesting way I started using mind maps is to understand videos.
A lot of content these days tends to be video first, and if I’m watching a lecture, I’ll pull out the YouTube transcript and dump it in NotebookLM.
NotebookLM then generates a mind map to provide an overview of the discussion and helps me understand the overall flow and the individual elements that connect to each other.
Mind maps also serve as a great way to refresh your learning. You can come back to it after reading through your own research and make sure you’ve retained everything you’ve learned.
Mind maps and source-based chat helped make NotebookLM an integral part of my workflow
That’s not to say I don’t use audio overviews anymore. On a long drive to the gym or while doing chores around the house, audio overviews are an excellent way to catch up on your research or learn something new, but they are not the only reason.
Today, my workflow is surprisingly straightforward. I dump all my sources into a notebook and use source-based chats for question-and-answer style learning.
While mind maps make sure I know how all the dots connect to each other, NotebookLM has become my favorite way to learn new concepts, and I wish I had this back in university.
