How Google’s NotebookLM Chatbot Became My New Study Assistant
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While Google’s mobile app is pretty poor , the web version of NotebookLM has become one of my most-used tools since I started experimenting with its large AI language model last spring. I’ve found countless ways to use it to improve my daily productivity, which is (far) more than I can say about other AI-powered apps I’ve tried.
Instead of (poorly) doing your work, NotebookLM acts as a true assistant, helping you organize information without being intrusive. One of the most convenient ways to interact with NotebookLM is through its familiar chat interface, which has turned the program into my new study partner and resourceful colleague.
How I Use NotebookLM’s AI Chat for Studying
I was preparing for a certification exam and uploaded my materials to NotebookLM every time I started a new chapter. From then on, I could create flashcards, mind maps, practice tests , and study podcasts with just a few clicks. The podcasts are particularly unique and helpful: two AI-generated voices discuss concepts from my notes and materials in an informative, conversational manner that sounds just like a podcast, if that podcast were a little too pedantic and intrusive. (Sometimes it even adds accents, like a raspy voice, to make it sound even more realistic.)
I usually listen to a podcast for my chapter while doing chores, like packing Poshmark items . Then I return to the notebook and have it generate flashcards or a quiz to test how well I’ve retained the information. Each card or quiz question has a link to the original material, so I can click on it and view the entire passage in the left panel.
I find this tool so useful that I’ve become something of an evangelist. A friend of mine recently returned to school, and I taught him how to upload slides, scanned chapters, PDFs, and other materials from online courses to NotebookLM. They now use the chatbot to summarize course material and create discussion plans.
Using a chatbot for planning proved helpful for a friend of mine who struggles with writing but thrives on practical thinking. He can ask the bot to generate key dates, important facts, and other specific details that he should research and use in his discussion messages, but which he himself finds difficult to extract from complex material.
The chatbot has also been useful for my own studying, but in a different way. Unlike my high school friend, I have no idea what will be on my certification test. I don’t receive a study guide. I know that I’ll be presented with a random selection of questions from 23 chapters of material, meaning I have to study everything, hoping I’ll cover the topics on my final exam well enough. So, after listening to my podcast and practicing with flashcards, I ask the bot to summarize the main idea of each chapter and suggest the five most important points. Although I know I have to read the entire chapter, this gives me a roadmap of where to start and what to focus on. In this sense, it’s similar to using traditional study methods like KWL or SQ3R to formulate questions before a critical reading session.
I also like to ask the chatbot to “talk to me” about specific topics in chapters. It’s my version of the Feynman method , where you test your knowledge of a topic by trying to teach it to someone else, though I don’t so much “teach” the bot as I talk to it. By talking to it, I learn to describe terms and ideas naturally, which is impossible if I’m not thoroughly familiar with them. If I have trouble keeping up the conversation, I know I need to study that section further.
How I use NotebookLM’s AI chat for work
In May, I published a series of articles on Lifehacker called ” Moving Made Easy .” While writing and researching nearly a dozen articles for it, I interviewed about 13 moving professionals from around the world. I ended up with a stack of interview transcripts, and the thought of rereading them all to distill the most important information and cross-checking repeated advice from different sources was daunting, to say the least. I struggled to remember who recommended what and in what context, and to determine which story each piece of advice best fits.
But then I turned to NotebookLM . I opened a new notebook and uploaded copies of all my transcripts. Because NotebookLM only pulls information from sources and materials you provide, I could ask its built-in chatbot questions without fear of it spewing out gibberish lifted from a questionable Reddit post from a decade ago. I’d ask it questions like, “What do sources recommend for moving large furniture?” and “What order should I pack in before moving?” and NotebookLM would produce simple lists of answers, each with a hyperlink to the exact transcript it was taken from.
Several professionals recommended similar things, such as putting clothes on hangers in a trash bag with a hole cut out for a hook, and NotebookLM condensed them all, emphasizing that this was an important tip I absolutely must include. At my request, each speaker’s name was listed next to the tip, so I didn’t have to search for who said what and risk misattribution. NotebookLM made summarizing, organizing, and attributing all this material much easier than if I had spent hours poring over transcripts and extracting it all myself.
Another advantage: unlike ChatGPT, I didn’t feel awkward using this chatbot, as it didn’t exploit someone else’s work or risk producing dubious results or causing full-blown hallucinations—its entire conclusion was based on my own, hard-won data. I formulated the questions myself, found the sources, and conducted the interviews. The chatbot simply helped me organize it all so I could turn quotes and information into useful, insightful stories. (Note that I never once asked the AI to help me write articles—I used it only for internal organization.)
Over the following months, whenever I had to work through a large amount of material for a task, NotebookLM became a useful tool. Sometimes I use the chat to ask it for a summary, main ideas, or an outline of my notes, but more often I use it to highlight quotes or the most notable ideas. This has helped me write much more organized and efficiently.
How I use NotebookLM in my daily life
If the tool has relevant and specific materials, you can use NotebookLM for other purposes as well. I compare it to using a single source of information (SSOT) , an old productivity method that involves storing all materials related to a specific project in a single folder on your computer. NotebookLM not only provides a place to store all your resources, but it can also organize them. Personally, I uploaded copies of my schedule and asked the tool to create a list of my travel and time commitments for the week. (Not all input needs to be files or links. There’s a plaintext option where you can simply type what you want the bot to communicate.)
But you can get much more creative. Let’s say you’re looking for a new job. You could upload a job description and ask the NotebookLM chatbot to generate 20 potential interview questions you might encounter. Or take it a step further: upload relevant news articles about a potential employer’s corporate culture, recent scandals, important development milestones, or the latest investor report and use them to build a general overview of the company. The more information you provide, the more useful the output will be—and, again, it will only pull information from these sources, meaning its summaries are trustworthy. To make sure of this, I periodically test the chatbot (because I’m a skeptic). I ask it a completely unrelated topic that I know isn’t in the materials I’ve uploaded, and so far it’s always responded that my question is “interesting,” but there are no links to it in the resources I’ve provided.
Other possible uses include summarizing meeting transcripts, finding significant themes in your recent journal entries, or creating a five-year career plan. Your possibilities are virtually limitless, limited only by the quality and volume of source materials you upload.