Why Is No One Talking About This INSANE NotebookLM Use Case?

I'm about to show you the Notebook LM use case that no one is talking about, but it absolutely changes everything. And that is not an overstatement because in this video, I'm going to be showing you step by step how to upload your entire chat history from Chat GPT and Claude AI into Notebook LM. We're talking about three years of data, three years of conversations, three years of memories, three years of frameworks and where you can pull up memories that you forgot, search for different items, and even start creating things and other assets from all of those conversations instead of just letting it sit there dead and dormant. If you didn't know, you can request a copy of your data from OpenAI and Claw and they will send it to you. But what a lot of people don't know is those files are massive. They're too big to upload to Notebook LM directly and so we have to break them up. Now, the first time I did this, I went a very complicated route and I didn't know there was a much simpler and easier way, but I went ahead and took the time to work out all the kinks and now I have a very simple copy paste method that you're going to be able to use by the end of this video to just copy and paste this one command and have your files broken up for you. And so the first

thing you want to do is go to my YouTube channel and find probably this latest video right here or even this video right here and click on it. Then come down to the description and click on this link right here that's going to take you to a Google form. After you fill out the Google form, you're going to get a link to my Google Drive where you're going to find these two documents. This is the Notebook LM Compound Intelligence Prompt Pack. And this notebook has everything you need to understand about this video. It starts off with simple instructions for how to actually get your files ready for Notebook LM, but it also has some very interesting prompts that you can run once you have your Chat GPT account uploaded to Notebook LM. One quick note, don't try to copy the code from here because there's some hidden characters and it's not going to run correctly. That's why I've also provided this second document. And all you have to do is come down to where it says oneshot terminal command. Highlight and then stop right here where you see the py and the dotted lines. Now we want to copy that. And just a quick note, I'm on a

Mac. I'm not on Windows. So if you're running on Windows, then I can't help you with support for that. If you're having problems finding terminal, I would suggest looking on YouTube for videos for how to open terminal on Windows or command prompt, which I believe it may be named now. I'm not sure. And from that point forward, everything in this video should work just the same. But if for some reason you paste this command and you run it and it doesn't do what it's supposed to do, then all you have to do is copy everything in the terminal, both the command and the message that you received back. Paste it in the chat GPT and ask why it didn't work. It works on Mac, but it's not working on my Windows. And chat GPT is more than capable of solving it for you in one to two turns. But now that we got that out of the way, the next thing you want to do is head over to OpenAI. Then you want to click on your name in the bottom lefthand corner. You want to go to settings. Then data controls. And then you want to click on export data at the very bottom. And then confirm export. Next, we want to head over to claw. Click on our name in the bottom lefthand corner. Click on settings. Go to privacy and then export data. Claw gives you a little more control over what you export, but I recommend just exporting everything. and click export. This is what your email from Claude is going to look like. All you have to do is click download data. And after 24 hours, this is what you're going to see, an expired link. And the same thing is true for OpenAI. You have 24 hours to actually download this data because after that invalid signature or expired URL. I'm going to zoom in right here for

you. So once you get your data back, you're going to see a folder that looks like this that says data 202610213. And if you come over here to the right, you can see that the conversations is 54. 1 megabytes. That is too big to upload directly to Notebook LM. But because of Notebook LM's file size limit, this can be tricky. So with Notebook LM, the file cannot be larger than 20 megabytes, but it also can't be larger than 500,000 words, whichever comes first. What we're going to do is use the terminal command to break up every file that is in this folder into something that is 450,000 words or less. But before you run the terminal command, this is very important. I want you to rightclick on this file and then click rename it. And you're going to rename it to chatgpt data, no spaces. Put it in the same caps because this is the way the command is set up already. And if you just change the file name, then you don't have to worry about changing the command, which would be far more difficult. So just rightclick, change the file for the chat GPT data and name it like this here. And don't worry, we're going to come back to this claw data in just a minute. I'm going to open up terminal on my Mac and I'm going to paste in the command. And then I'm going to press enter or return. Wait for a few moments and you can see that it says done. Input. This is the downloads chatgpt data conversations. json. That's the file that came in. output users Cory Mlan downloads and it created a folder notebook LM ready. And now when we come back to finder, here's the notebook LM ready folder. Let's double click and open it. And I want you to look over here at the timestamps. It says today at 8:08 p. m. I'm going to go up to the top of my Mac. So you can see that it is Sunday, January 4th, 8:10 p. m. So these were just created. And the second thing I want you to look at is the file size. So everything is around 3. 2 two three megabytes. And that's how we know that these files have been chunked the proper way because 450,000 words should just be the same file size across the board, right? So, all of them are pretty close to that. So, we're good to go there. The next thing I want you to look at is the kind of files they are. They are markdown text files. That means that they are human readable. And so, just to show you, I'm going to open number 24. And so if I scroll through this, you can see that this is a full conversation taking place right here. And so this is exactly what we want because not only is this machine readable, but this is also notebook LM readable because one of the problems with the files you get back from OpenAI and probably even claw is that there is just so much metadata. But not only does this Python script chunk everything down to 450,000 words or less, it also strips out all of the metadata and throws it away so that the only thing that is left are the labels between you and the chatbot going backwards and forward. And so now this is the claw data right here. And now we want to batch this. And so all you want to do is grab this folder, drop it inside of the chat GPT folder. I'm going to take this notebook LM folder and move it to the trash. Then I'm going to take the chat GPT conversations and I'm going to move that to the trash as well. Then I'm going to take my clawed conversations and I'm going to drag it out. I'm going back to terminal. I'm at the bottom. I'm going to paste the command again and run it one more time. And if you look at the bottom, users Corey McLean downloads chatgpt data conversations. json and then the output the notebook lm ready folder. The main thing you need to remember about this whenever you're using this script to chunk any data is that you want to move the data into that chat GPT folder and just make sure that the name is conversations. json and it'll find that file and then chunk it. It'll parse it. Now we're back in my finder and you can see the notebook LM ready folder right here. And so this time it only gave me one of them. So let's close this up. I don't know why, but the oneshot command that I had for chat GPT that was working for claw yesterday did not work today during the recording of this video. And so I had to come to chat GPT and troubleshoot it. And that's literally all you want to do whenever these things don't work. And eventually ChatGpt rewrote the command. So now I have one that works for both ChatGpt and Claw. And what I did was I told ChatGpt to give me a downloadable link right here, the text file that I could upload to my Google Drive. So when you download the notebook LM compound intelligence prompt pack, and you get the link to my Google Drive, not only are you going to have this PDF right here, you're also going to see one that says works for chat GPT, and then this claw and chat GPT. So if you use the first one and it doesn't work, then try the second one. But everything is still the same. You're gonna parse or chunk your chat GPT data. And then if you have clawed data, just move the chat GPT data out of the folder and then move the claw data in the folder. Make sure it's named conversations. json. Run it again and it's going to find it

and parse it. And this is the part we've all been waiting for. You want to come over to Notebook LM and click on create a new notebook. Click choose file. Then you want to navigate to where your files are. So these are the clawed files right here. I already have them uploaded as you probably noticed on my screen a second ago. And now we're inside of my chat GPT notebook and you can see the label right here from 2022 to 2025. And if you look on the lefth hand side, you can see that there are 82 different files. And I can click on either one of these and notebook LM is going to open it up. Now once we start scrolling down, you can see how detailed this file is by how little this margin right here moves. Now that you uploaded your chat GPT and your claw data to notebook LM, we can do some very creative things that we just haven't been able to do with notebook LM or chat GPT or claw for that matter. Now

I can ask Notebook LM to act as a system analyst and go through three years of chat GPT conversations and find the frameworks that I've used the most often or the ones that I've had the most success with or that I lean on the most. Or if you want to be creative, instead of dropping this in the chat, just take your prompts and automatically run them over here in the AI studio. So for instance, you might go to reports, create your own, paste your prompt, and then click generate. Glancing over this, I can see how it's giving me a very highle view of everything that I've been using chat GPT for. And I can see at least two frameworks that it surfaced. one of them in particular that I didn't get to finish actually developing that I actually want to come back to, but another one right here. So, what I want to do is copy those frameworks and now I'm going to create a slide deck that asked Notebook LM presentation to remind me about those frameworks because I don't remember what they were. I remember the five eyes vaguely, but I don't remember Rapid at all. Generating digital assets inside of Notebook LM based on my three years conversation history with chat GPT is just the beginning of what I'm able to do because I'm also able to come over here to Gemini, click on the plus button to add files. I can choose notebook LM and then I can choose my chat GPT conversations and clawed AI conversations. I can add them both to the chat and then I can run the same prompt here in the chat. But instead of asking Gemini to create a slide deck, I might say, well, you know what? I'm going to load Nano Banana Pro, create a I don't know, a punk rock synth wave vibe uh notebook LM image that explains to me what these two frameworks actually mean in as few words as possible. Paste in the frameworks. Press enter. And now let's let Nano Banana Pro actually create an image that explains both of these frameworks using chat GPT and Claude if I consulted with Claude about it, which I probably didn't. And just like that, we have a detailed image. And so the five I system framework is about imagine, instruct, implement, inspect, inaugurate, sealing the work, rapid system, rally, emotion, angle, controversy, production, originality, interaction, velocity, delivery, algorithm. I believe this is about content design for rapid audience growth. Facebook reels addresses. Ah, I remember this. Ah, I think it's coming to me now. I'm getting a little bit more clearer on this. But these are both some great frameworks that I never finished fully developing. So if I wanted to go back to those, I can definitely pull this stuff up with Notebook LM and Gemini. And if we come back over here to Notebook, we can see that there is a full report that's been generated. Master Frameworks and Systems Index. Suffice it to say that this is a very wellput together document. And if you look in this AI studio for chat GPT, you can see that there are so many other assets that I've created to help me capitalize on my three years with ChatGpt and make 2026 a better year. Create a vision board image that captures what you believe my 2026 is going to look like. Be brutally honest. If you think that based on my conversation, success lies in my future or failure. Just show me what you think is going to look like based on the trajectory of my conversations and the things that have happened recently that you can ascertain. Brutally honest trajectory. Success is possible. Failure learning retry. This was very modest. Future trajectory. So it didn't give me a straightforward answer which is cool. I just want you to see what's possible. So if you made it this far in the video and you want to upload your data from chat GPT or claw to notebook LM. so that you can start inspecting, researching, and discovering a lot of new things about yourself, about the frameworks, about solutions that you've discovered and forgot about. Then make sure you go to the description and click on the Google form link right here. And once you click on that link, you're going to see a form like this. Fill out this form. Just make sure it says Notebook LM Compound Intelligence Prompt Pack at the top and you're good to go. Once you complete that form, you're going to see a thank you message with a link to this Google Drive folder. If you can't click on the link, copy it and paste it in the browser and you're going to see these three files. This is the Compound Intelligence prompt pack. It's going to have 16 prompts inside that are going to give you some unique ways to start using this data, but again, there are no right and wrong ways. So, you can start creating any type of assets you want. Number two, there are going to be two different oneshot terminals. So, if you only have ChatGpt data, feel free to just use the one that works for Chat GPT. And if you also have clawed data, make sure you use this one for the clawed data after you move the claw files into the chat GPT folder just like we discussed at the beginning of the video. And one more thing, sometimes this stuff just doesn't work. And I can't tell you why. But one thing I can tell you is if you paste your terminal messages inside of chat GPT or if you take a screenshot and drop it inside of chat GPT and just tell it in plain language what you're trying to do. Just give it as much data as possible. Tell it everything and then ask it to fix the problem. It's going to fix it. So if you got value out of this video, make sure you hit the like button and if you want to help the channel grow, hit the hype button as well and give it some hype points. And think about subscribing to the channel. And as always, take care. Have a good day. And if you want to see some more interesting use cases about how I'm using my chat GBT data with Gemini, then make sure you check out this video right