WEBVTT 00:00:00.000 --> 00:00:04.000 Claude code might be the most powerful research agent 00:00:04.000 --> 00:00:05.360 on the planet, 00:00:05.680 --> 00:00:16.835 but you need to add this one tool to unlock it. Now most people's version of Claude code research is just telling it to use the web search tool and praying that whatever it comes back with is good enough. 00:00:17.235 --> 00:00:26.435 But we can do better. Because what if I told you with just five minutes of setup, we could create workflows inside of Cloud Code that are able to scrape any section of YouTube, 00:00:26.595 --> 00:00:27.795 pull their captions, 00:00:27.875 --> 00:00:31.555 push that information to a free robust 00:00:31.100 --> 00:00:41.420 prebuilt rag system that is able to do all the heavy lifting and analysis for us, and then take that analysis and give us deliverables like slide decks, infographics, 00:00:41.420 --> 00:00:42.220 podcasts, 00:00:42.380 --> 00:00:46.475 you name it, all while costing us virtually 0 tokens. 00:00:46.555 --> 00:00:56.395 Now if that sounds way too good to be true, you would normally be right, but not in this case. So let me introduce you to the most underrated AI tool in the game today, 00:00:56.930 --> 00:00:58.050 NotebookLM. 00:00:58.130 --> 00:01:03.810 So in today's video, I'm gonna show you how to combine the powers of ClaudeCode and NotebookLM 00:01:03.810 --> 00:01:06.610 to replace a research stack for free 00:01:06.850 --> 00:01:21.555 that would otherwise cost you hundreds of dollars a month to build and maintain. I'm really excited to show you guys this one, so let's hop into it. So let's kick this video off with a demo so you can see how we can use Claude code to harness all the features 00:01:21.715 --> 00:01:36.690 of Notebook LM without us ever leaving the terminal. Now this prompt's gonna have ClaudeCode do a number of things. First, we are gonna use our custom YouTube search skill to find the latest trending videos on ClaudeCode skills. And don't worry, I will show you all these skills and how to get them in a second. 00:01:37.375 --> 00:01:39.455 After we find the video URLs, 00:01:39.615 --> 00:01:43.135 I want Cloud Code to send those URLs over to NotebookLM 00:01:43.135 --> 00:01:45.055 using the NotebookLM skill. 00:01:45.775 --> 00:01:48.415 I then want NotebookLM to do analysis 00:01:48.575 --> 00:01:59.780 on those videos to figure out what are the top load skills, and I wanna get that analysis sent to us. Furthermore, I want a deliverable. I don't just want the text analysis. I want an infographic in a handwritten blueprint style 00:01:59.940 --> 00:02:01.300 depicting that analysis 00:02:01.700 --> 00:02:03.220 on the top skills. 00:02:03.620 --> 00:02:18.265 So with one prompt, we are going to scrape YouTube. We're going to source all of our data. We're going to essentially put it into a rag system because that's what Notebook LM is. We're gonna have Notebook LM do all the analysis and the deliverables for us off-site, 00:02:18.345 --> 00:02:21.750 which means we don't pay for that in tokens, we and get all that for free. 00:02:22.150 --> 00:02:28.870 So let's see how it works. So here's what we got. Claude code uploaded 20 YouTube sources into notebook l m for analysis. 00:02:29.030 --> 00:02:33.510 Notebook l m then came back with the top five Claude code skills that you see here 00:02:34.195 --> 00:02:44.595 as well as emerging trends for how they're used. It then created that infographic deliverable for us which automatically populated inside of our project folder. So here's a look at that infographic. 00:02:44.595 --> 00:03:35.675 Again, this is Nano Banana Pro under the hood. It's actually being called. And the text here and all the visuals, a, fit the style that we called for, which was like a handwritten blueprint type style. And secondly, and more importantly, all this content is based on the videos and the analysis of those videos. This is it isn't just making stuff up. And we can also see here inside of Cloud Code the videos it grabbed, the title, the creator, the views, the duration, and the date. And all this is reflected inside of Notebook LM itself. I can see all the sources it upload. I can see all the analysis. I can see the blueprint guide that we asked for. And while this demo might seem like a rather simplistic application of this, I cannot stress enough the value add of combining these two tools because this goes way beyond just automating the source process for Notebook LM. Everything we did here, could have done manually inside of NotebookLM. Right? I could have gone through YouTube manually. 00:03:35.835 --> 00:03:40.955 I could have found all the videos I want. I could have copy pasted them in. I could have gotten the analysis and I could have gotten the deliverable. 00:03:41.195 --> 00:03:47.370 The fact that we can automate that is nice, but it's more than that. It's the fact that I can bring all that analysis 00:03:47.450 --> 00:03:49.690 into my Cloud Code ecosystem 00:03:49.770 --> 00:03:50.730 effortlessly, 00:03:50.730 --> 00:03:52.010 and the use cases 00:03:52.250 --> 00:04:09.985 of that workflow are pretty much infinite. And the second reason why this combination of tools is so powerful has everything to do with the straight up power of Notebook LM. If you try to recreate what Notebook LM does, which is like a scraping system into a rag system, into an analysis system, into a deliverable 00:04:10.305 --> 00:04:40.000 system, right, with the infographics, the slide deck, all of that, it would be a gigantic pain in the butt to do. As someone who has tried it, at least on the research side with things like NADN, it's not a simple process. Furthermore, it costs money, and this whole thing is free, which is in large part why I'm so excited to share it with And another reason you should be pumped is because how simple it is to set this whole thing up, which is what we're going to cover now. So when it comes to setting this up, you're probably thinking, hey, Chase, how do we actually connect NotebookLM to Cloud Code? Considering the fact that NotebookLM 00:04:40.000 --> 00:04:52.505 does not have a public API. But luckily for us, there's people much smarter than you or I who have already solved this problem. In this case, it is Tang Ling, and we will be standing on his shoulders today as we use the NotebookLM 00:04:52.505 --> 00:04:58.985 dash py GitHub repo to essentially act as an unofficial Python API for NotebookLM. 00:04:58.985 --> 00:05:00.745 But before we set up NotebookLM, 00:05:00.745 --> 00:05:06.260 we need to solve the first part of our pipeline, which is actually the YouTube search and the sourcing 00:05:06.420 --> 00:06:55.015 of the data we want NotebookLM to do analysis on. And for that, I have a custom YouTube search skill for ClaudeCode that does all of this for you. It uses a Python script that relies on the y t dash d o p dependency to scrape YouTube's metadata for us. So when I ask it for, hey, Claude code skills, it's just like us going on YouTube and searching in Claude code skills. It grabs title, views, author, all that important stuff. And this skill you see right here inside of Claude code teaches Claude code how to best use this script. Now there's two ways to get this skill and this script up and running. The first is rather simple. You just go inside a Claude code and explain that you wanted to build this custom skill for you, that you wanna use the y t d l p dependency to create a custom YouTube scraper. Or if you want this entire YouTube search skill setup m d file, and you can just download it and hand it to ClotCode, you can do that too. And you can get it by heading to my free school community, which you can find a description for. Now speaking of my school communities inside of Chase AI plus, you can also find my Claude code master class, which I just released a few days ago. So if you're someone who is kind of in the beginning of their AI journey and is trying to figure out how can I best leverage Claude code even if I'm not technical, I really wanna master what is definitely the most powerful AI tool in the game, well, that's the place for you? And if you're interested in that, just check the link in the pinned comment. So once you download the YouTube search skill setup file, just give it the Claude code and tell it to go to work or you can just manually prompt Claude code to build it for you. Now let's head back here and set up the notebook l m connection. So I'll put a link to this down in the description as well, and the install is pretty simple. So to install this, we are just going to copy these commands, paste it inside of our terminal, which means, hey, if you're looking at Claude code, you're wrong. You need to open a second terminal that looks like this and paste in those commands. 00:06:55.255 --> 00:07:03.740 After you run these initial installation commands, what you wanna do is scroll down here, and we're gonna have to run one more command in the CLI, that's the notebook lm login command. 00:07:04.140 --> 00:07:34.100 Same thing as before, head into another terminal, paste this in there. That's going to open a new window in Chrome. All you have to do is log in. You just have to do it once and you're all set. Now after you authenticate with the Notebook LM login, there's one more thing you have to do and we need to do the skill. So to do the skill inside of Claude code, right, you can either run this command in the terminal or just tell Claude code to do it. So understand also what we've done. We've done two things on the Notebook LM side. You have the skill, and then you have, like, the actual 00:07:34.340 --> 00:07:42.745 API of the program. Remember, skills are just prompts. It's just text telling Claude code how to do something in a specific manner. So 00:07:43.065 --> 00:07:54.585 all this information you see here about, hey. Here's how we generate content. Here's how we create the notebook. This skill is teaching Cloud Code how to do that. So once it's installed, you just need to tell Cloud Code, hey. I want you to use NotebookLM to 00:07:54.850 --> 00:07:55.570 create 00:07:55.810 --> 00:08:08.050 flashcards or an infographic or slide deck. It's that easy. Everything's just in plain language. And if you're wondering what exactly you can do with this program, well, it's all here inside of the GitHub. Anything you can do in Notebook LM manually, you can do with the API 00:08:08.370 --> 00:08:15.425 and some. As you can see here beyond the web UI, we can also do batch downloads, export the quiz and flashcards, 00:08:15.425 --> 00:08:18.545 etcetera etcetera. So we actually get more functionality 00:08:18.705 --> 00:08:49.705 using this program than you would do just loading up NotebookLM yourself. Let's So actually go through it one step at a time so you understand how it's working. So the first thing is that YouTube search skill. So like any skill, we can either use it as a slash command or you can just use plain language. But if I do y t dash search, you see we have query and then the count. So what are we looking for? Hey. We're looking for Claude code skills. And so while in the demo, we did everything at once. I think it's useful to break it up sometimes so you can first get eyes on what your sources are actually going to be. 00:08:50.370 --> 00:09:26.310 So here's the results it comes back with right at any time. We can also check the YouTube links ourselves. And what's nice with this skill is it will also give you some insight about what's actually going on with what it brought back. So if you're happy with the sources, now we can push it into NotebookLM. So again, you can just use plain language. Create a new notebook in Notebook LM titled chase demo with these sources we just pulled. And we can see it created the notebook, now it's gonna be populating it with its sources. So after a couple minutes, all 20 sources are loaded, and you're limited to 50 sources with Notebook LM. At this point, you can have Notebook do whatever you want. So we can say based on those videos, what does Notebook LM believe is the number one Cloud Code skill? 00:09:26.550 --> 00:09:29.990 Now, again, the cool thing with this is all this analysis 00:09:30.310 --> 00:09:31.190 is offloaded. 00:09:31.825 --> 00:09:45.745 Cloud Code isn't doing this analysis. Cloud Code isn't spending tokens. It's only spending a small amount of tokens to send that request to NotebookLM and bring it back. But all the thinking is done by Google, and they're paying for it. So Cloud Code grabbed NotebookLM's 00:09:45.745 --> 00:09:46.145 analysis, 00:09:46.960 --> 00:10:03.485 and we can see that reflected here inside of notebook l m itself. So you can always double check and click inside of notebook l m if you want to see like what captions it's referencing to. And this cadence also applies for all the deliverables. So right, if you want the audio overview, the mind map, flashcards, the infographics, anything you see over here on the right, 00:10:03.885 --> 00:10:08.685 just prompt Claude code and it will do it for you. It's that easy. 00:10:08.845 --> 00:10:37.685 So how you end up leveraging this research workflow is ultimately up to you, but I really can't stress enough how wild this thing is. It seems pretty simple on the surface, but I'm telling you, if you've tried to deal with anything like this, especially with the YouTube video stuff and actually trying to create some, like, corpus of knowledge from these videos in a way that Claude code or some other agentic coder can interact with it, it's pretty difficult. Right? And it's very time consuming, and it can be rather brittle. Yet all of this is abstracted away for free 00:10:38.165 --> 00:10:39.205 with Notebook LM. 00:10:39.840 --> 00:10:48.160 So I think this is an awesome tool. I hope you can get some use out of it. As always, like I said before, all the resources can be found in my school communities. 00:10:48.320 --> 00:11:07.425 If you need the MD file for the, uh, skill, for the YouTube search skill, make sure you see that in the free one. And, if you're a little more serious about this stuff and you're like, I really just wanna have, like, a Cloud Code master class that gets me from, like, zero to AI dev, make sure to check out Chase AI plus. So let me know what you thought of this in the comments. And as always, I'll see you around.