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Chapter 1: What inspired Gavriel Cohen to create NanoClaw?
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Chapter 2: How did NanoClaw go from a side project to a viral sensation?
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Chapter 3: What problems did OpenClaw face that NanoClaw aims to solve?
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Chapter 4: What is the significance of the Docker partnership for NanoClaw?
Not available in all states or situations. It has been an absolutely crazy six weeks for the creator of NanoClaw by Gavriel Cohen. He created this tool basically in 48 hours on his couch, and it has now led six weeks later to going completely viral and creating and having a deal with Docker. So today on the podcast, I want to break down his story, how he built this product, what it does.
It's basically an open source version of OpenClaw.
Chapter 5: How does NanoClaw ensure user data security compared to OpenClaw?
which is the viral tool used to create AI agents that everyone is talking about and using. I want to break down the story of this company because I think it is a phenomenal meteoric rise of a really incredible tool that a lot of people have fallen in love with. So let's get into the podcast.
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Chapter 6: What are the future business plans for NanoCo?
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Chapter 7: How does NanoClaw plan to monetize its open-source model?
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Chapter 8: What lessons can entrepreneurs learn from NanoClaw's rapid growth?
This is a really small open source alternative to OpenClaw. And he built this basically in, you know, I think 48 hours straight, he said he sat down and just cranked this thing out.
uh it eventually you know this thing snowballed quite big but it was originally just started as a small side project a few weeks later after he made you know a post um andrew carpathy of course the famous ai researcher was saying you know like hey this thing's pretty cool it went super viral when he did that he posted on x and this basically put it in front of thousands of developers and from all the attention that that got it got more than 22 000 github stars it had 4 600 forks and
dozens and dozens of contributions and collaborations on like new features that people wanted to add to it. And that's the cool thing with open sources, you put it out there, if people find it useful, you're going to get a ton of help building it up and making it, you know, a really useful, great product. I think that's when things started to get really serious after that kind of initial wave.
So last week, Cohen actually shut down the AI marketing startup that he launched with his brother Lazar. And he is focusing exclusively on nano cloth. So he had something a going, realized this thing had so much momentum, he shut that down. Right now, both of them are building a company around the project called NanoCo. And this is usually how these open source projects go, right?
Because technically, open source means they're giving the code away. Anyone can use it for free or kind of with a license. I mean, there's different ways you can do open source. But, you know, you really are trying to give this away for other people to use. But you typically will create a company around it where you host it on your own server and usually have an API.
And if people don't want to kind of run it on their own hardware, they can still get access to it through you. So on Friday after, I guess they hit another milestone, Cohen announced that Docker was who is, of course, the company behind all of the container technology.
It's used by millions of developers around the world, just partnered with NanoClaw, and they're going to integrate Docker sandboxes directly into their platform. And for a project, I think that began, you know, this is basically a weekend experiment six weeks ago. This is moving very fast. One thing that I do think is interesting here is kind of the idea of NanoClaw, how it came out.
There was a real world problem that they were trying to solve. Cohen and both, I think him and his brother have been running an AI native marketing agency. They use AI agents to do a lot of different tasks, right? Like these things like market research, blog writing, you know, GDM analysis.
They were doing all of that and the model was working well, but they already, and they already had like a bunch of big customers. They were on track to reach a million dollars in annual recurring revenue. And he said, I'm a big believer in AI native service companies. They can operate with the margins of software companies while still delivering service.
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