For far too long, I’ve been navigating the ever-growing mountain of research notes and documents in a somewhat disorganized and inefficient way. I did hear about AI note-taking tools, but for one reason or another, I hesitated. That all changed when I finally decided to explore NotebookLM. The immediate clarity and efficiency that Google’s AI note-taking tool has brought to my research workflow has left me with one thought: I should have tried this sooner.
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These simple yet powerful NotebookLM tricks have transformed my workflow.
My workflow before NotebookLM
Before NotebookLM, my research process for learning new concepts was a nightmare. It involved juggling multiple browser tabs, tracking key moments in YouTube videos, and reviewing downloaded PDFs and documents.
The constant need to switch between these different source types was incredibly disruptive. I would be referring to a website, then have to jump to a specific timestamp in a video, then open a PDF, and ultimately, lose my train of thought and the overall context of the concept. My note-taking was equally chaotic. It felt like trying to piece together a puzzle with pieces from completely different sets.
I often found myself revisiting the same sources multiple times. This repetitive process was incredibly time-consuming and inefficient.
Discovering NotebookLM for the first time
I have tried dozens of note-taking tools, but NotebookLM felt entirely different from anything I have ever used. Google didn’t just create a note-taking or wiki tool and add AI on top of it. In fact, the entire tool has been built with AI from the ground up. I can’t just create a new notebook and start taking notes. This wasn’t about free-form jotting; it was about feeding the AI.
There was a slight learning curve in understanding the power of NotebookLM. But after a week, I was flying through my notebooks. I wanted to learn about Python integration in Excel. I created a new notebook called Python and started adding relevant sources like web addresses, YouTube videos, and the official Microsoft documentation.
NotebookLM quickly generated a paragraph summarizing all the sources. It gave me a quick idea about the new development in Excel. I saved it to a note to refer to it later and start asking questions like Which Python libraries does Excel support?, Can I use Python integration on Excel on Mac?, How to enable Python in Excel?, and more. NotebookLM also offered suggestions for questions at the bottom.
Overall, it felt like a personal search engine where I can control sources. At any point, I can exclude a specific source with a single click, which is quite convenient.
Integrating NotebookLM in my workflow
As I started creating more notebooks, each focused on a different concept and populated with relevant sources, the power of NotebookLM truly began to shine. I was no longer drowning in a sea of disparate information. I was quite new to self-hosting and Docker and wanted to learn more about them. I created a new notebook called Docker, added relevant sources (including multiple YouTube videos from reputed creators), and after an hour or two, I was already running Docker on my Mac with a few containers.
Similarly, I created a notebook called Home lab while building my home lab and learned crucial concepts around it. I can only imagine how it can be a game-changer for students for learning complex concepts in a few minutes. While NotebookLM provides excellent summaries, I still take targeted notes.
NotebookLM also turned out to be handy for my troubleshooting headaches. If I encountered an error, I don’t have to go through lengthy documentation to resolve the problem. I can upload relevant documents to NotebookLM and use the Chat menu to find a solution in no time.
Audio overview has been a game changer
While there are several features in NotebookLM, the audio overview stood out for my workflow. With NotebookLM’s audio overview, I can quickly grasp the main points, the different viewpoints presented, and the overall trajectory of the discussion without having to invest hours in manual note-taking.
It identifies the main topics covered, the key arguments presented by each host, and often highlights important examples or explanations they used. Last week, I wanted to learn about the history of AI. I uploaded all the relevant sources, generated an audio overview, and listened to the conversation. It allows me to quickly grasp the structured delivery of knowledge from the two hosts.
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NotebookLM is your next productivity powerhouse
Unlock smarter note-taking
Ultimately, my journey with NotebookLM has been a revelation. From now on, whenever I’m dealing with several research documents, articles, and PDF files, I create a new notebook, upload everything, and let NotebookLM do the heavy lifting. If you’re looking for a smarter way to work with your notes, give NotebookLM a try.
That being said, NotebookLM is still in early stages. You may run into performance hiccups and glitches. That being said, I can’t wait to see how Google takes it to the next level with future updates. If you are new to NotebookLM, check out these tips to get started.
