# NotebookLM Supercharged: The Ultimate Research Stack (With Gemini 3.0)

## Метаданные

- **Канал:** Universe of AI
- **YouTube:** https://www.youtube.com/watch?v=jQ6W1vvcLUg
- **Дата:** 25.01.2026
- **Длительность:** 9:15
- **Просмотры:** 5,439
- **Источник:** https://ekstraktznaniy.ru/video/9510

## Описание

NotebookLM isn’t just a notes app.
In this video, I show how to supercharge NotebookLM with Gemini to turn research into real apps, websites, and tools — from market research to personal workflows.

For hands-on demos, tools, workflows, and dev-focused content, check out World of AI, our channel dedicated to building with these models:  ‪‪ ⁨‪‪‪‪‪‪‪@intheworldofai 

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#NotebookLM #GeminiAI #AIResearch #AIWorkflow #AIProductivity 
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## Транскрипт

### Intro []

Most people use Notebook LM like a smarter Google doc. You upload some PDFs, ask a few questions, maybe summarize a report, and that's it. But if you connect Notebook LM with Gemini, something really interesting happens. Notebook LM becomes the brain. It does the thinking, the research, the structuring, Gemini becomes the builder. It turns that thinking into actual apps, websites, and tools. In this video, I'll show you how to use Notebook LM and Gemini together to turn research into a real website, build a custom travel app for an upcoming trip, and more. So, let's get into it. Before we get into

### Workflow Overview [0:35]

the video, we need to understand the strengths and powers of each application, and why the combination of both allows you to supercharge your Notebook LM. First thing, Notebook LM is incredible at reading a lot of documents, grounding answers and sources, and turning messy information into a clean structure. But what it doesn't do is build things. Gemini, on the other hand, is great at coding, creating interfaces, and turning instructions into working software. But Gemini needs good inputs. So the workflow is simple. Notebook LM decides what to build. Gemini figures out how to build it. And once you see this, everything starts to make sense. Let's

### Demo 1 (Web Application) [1:14]

start with the real example. Let's say I want to build a website around the AI tools marketplace. So currently I have this notebook that I have created and it has used highquality sources and has done a bunch of research. So this is kind of the brain. It has done analysis on the 2026 market and I have this powerful notebook element that has all that data. Now the problem is all this data is good. It's good to have. This is a brain, but there's not much I can do with it except for extended questions. Maybe use the studio to make some audio overview, video overview, mind map, but the limitations are obviously there. Now, I want to take all this information and create a website that summarizes my research in a beautiful manner into something that could be production ready for meetings, for personal use, for even SASbased businesses. So, let's do that. All you have to do is go to Gemini, click on this plus sign at the bottom where it says add files, select Notebook LM, and then select the one. So, we're going to select the AI tools market overview one, and I'm going to add that here. Then, I'm going to ask Gemini to build me a responsive website using this research include filtering, search, and a clean UI. And then the powerful thing about Gemini is that you get to choose what model you're using as well. If you want something quickly, just choose the fast one, thinking. And if you want something for math and code, choose this one. So we'll keep the pro one for now. And then all you have to do is press submit. So looks like Gemini is done creating the website. But before we do that, we need to understand what happened in the background. If we look at the thinking section, we know that it's analyzing the AI trends. So it's going into that notebook LM understanding the sources understanding the AI trends identifying them and then is doing the building part where it's going to take all that information outline a site architecture define a text stack so it knows that I'm going to use HTML for structure Tailwind CSS and JavaScript for dynamic content then it's going to add data fine-tune it structure the sections and populate tool cards so that's how powerful these two tools are together it takes quality research and turns it into a website. So let's now take a look at the website. So what you're looking at right now is the website that notebook LM and Gemini have created together. It is calling it the AI monitor 2026. So we have a tools directory, trends, market outlook. So if you'll go to this trend section, we can see that there's strategic trends that it has laid out like the agentic AI ship, small language model, sovereign AI intelligence directory. It has created these tool cards for every single tool that we have in our notebook LM. For example, you can search at reasoning tools, coding tools, agents, open source, all of them together. So, this is how cool it is because it was able to take all that data and turn it into something that is production ready and something that we could even display on our personal websites or even on a company website. Then you have the market pulse which is kind of the market outlook that it has summarized over here. So, it's saying that in a bare case what happens in a bull case what happens. So this is how cool it is and we know that this is high quality research and we can see that at the bottom data aggregated from industry reports Garner JP Morgan data north. So this is one of the cool features of what you can do with notebookm and supercharge your notebooks. You're also

### Demo 2 (Travel World) [4:24]

not limited to just boring examples like generating websites. Let's say you're planning a trip to Iceland and you want to learn more about Iceland. At the same time, you want to know what areas you have to visit, how much it's going to cost, but you want to do it in a fun manner. Obviously, you have notebookm is going to gather all your sources and give you a good report that if you want to read, you can, but these reports are sometimes boring. That's where Gemini comes in. You can ask Gemini. For example, I'm going to ask Gemini to create an interactive vauil world for the top five landmarks in Iceland and educate me about the location, activities I could do there, and the cost for a trip there if applicable. So then I'm just going to add my notebook LM. I'm going to select the Iceland one so it knows that it's supposed to use the data from this Iceland notebook specifically, not online sources, and create this. Then all you have to do is press submit. So I'm just going to do that. So, looks like Gemini is done generating Voxo Iceland. So, this is what it looks like. Obviously, from the get- go, this is not an amazing representation of the Blue Lagoon, but for our purposes, this does the job pretty well. For example, we have an interactive blue lagoon area. I guess this is the pool it's trying to be. And then we have education, and it's saying that, okay, this is not a natural spring, but a man-made lagoon. We also have activities. So, oh, I can click on these. If I use the mass bar, it says Cissia mud applied. That's pretty cool. swim to the bar, visit the sauna, you can do all of that. There's entrance cost. So, it's also provide us our entrance cost, how much it is, and everything like that. So, this is pretty cool. Let's look at the other locations. I guess this is trying to be a waterfall. We can walk the path. Oh, feel the spray. That's kind of cool. Photo mode. Capture a panoramic shot of the canyon and glacier. These, this is what you could do there. The education section and obviously the trip cost. That seems accurate. Entrance of parking. then the other lagoons, everything like that. We can board a boat, look at wildlife once again. Like, we can learn about a place we're traveling before we go to it in a fun manner. Obviously, the visuals could be better if I were to use maybe Nano Banana Pro instead of trying to create a voxal world, which is a hard task for models to do cuz it has to not only take the research that you have provided, but program something that's beautiful like this. So, it's a hard task for the models at the moment, but this is not bad at all. like I get an idea what I can do at each location and this I guess what it's telling me is like hey why don't you actually go to the location see for yourself so this is

### Personal Software [6:52]

pretty good so I just showed you guys two basic example but here's the part most people are completely missing this combo isn't just good for projects or trips you can use it to build a personal knowledge system that actually understands how you think imagine you upload into notebook LM books you've read podcasts you've listened to meeting notes from work research arch papers or articles you keep coming back to. Instead of asking for summaries, you can ask notebookm questions like, "What themes keep showing up across everything I've read? What ideas do I return to over and over again? How do my interests connect across different topics? " At that point, Notebook LM stops being a note-taking tool and starts acting like a reflection engine. It's not just storing information, is surfacing patterns in your thinking. Now, here's the powerful part. You take that structure, the themes, the connection, the priorities and hand it off to Gemini. And then Gemini can build a searchable personal dashboard, topic clusters that evolve over time, timelines of how your thinking has changed, even recommendations based on your interest and not the internets. Let me give you a simple example. Let's say you're a founder or a strategy person. You upload books on startups and businesses, market research decks, meeting notes from planning sessions, podcasts on leadership and tech. And that notebook element might surface something like you consistently focus on platform businesses, defensibility, and long-term modes. Now, Gemini can turn that into a dashboard that tracks ideas related to those themes, a place where new research automatically slots into the right buckets, and a system that highlights ideas you should probably double down on. That's not note takingaking. That's building software around your decision-making. Who is this perfect for? Well, this works insanely well for founders trying to clarify strategy, students managing dense material, analysts tracking industries, content creators organizing ideas and story lines. You're not just collecting information anymore. You're building a system that helps you think better over time. Make sure to subscribe to our

### Outro [8:56]

channel. We do real tests, not just headlines. Make sure you're also subscribed to the world of AI and don't forget to check out our newsletter for deeper breakdowns you won't see on YouTube. And I'm growing my Twitter following, so make sure you follow me on Twitter as well. Hope you guys enjoyed today's video and I'll see you in the next