Making $$$ with OpenClaw

How can you make money from OpenClaw? Like how can you spin up these OpenClaw instances, these sub agents, these digital employees that can go out and make you money while you sleep? Is it even possible? Well, in today's episode, I brought on Nick and he shows a tactical tutorial for how to spin up multiple OpenClaw machines in a virtual instance, how you can be automating tasks on Upwork and these boring business automations and how you can actually make money from OpenClaw. If this doesn't get your creative juices flowing for the future of SAS, how people are going to make money and how to actually use OpenClaw from not just a cute little use cases but actually money making opportunities then I don't know what will. I had such a good chat with Nick. It got my creative juices flowing. They think it will yours too. And this is, I think, one of Nick's first podcasts. So give him a like and comment to juice him up because he shared that sauce. [MUSIC] I couldn't be more excited to have Nick on the pod. He's one of my go-to people when I have questions about OpenClaw. Nick, by the end of this episode, what are people going to learn? Yeah, people are going to learn that OpenClaw is more than just a personal assistant. You can actually deploy this into businesses. You could drive the actual business outcomes, generate revenue off of OpenClaw as an opportunity. And yeah, we're seeing it on X, like people who are deploying OpenClaw for kind of executives or individuals who are super busy. They're making thousands of dollars, you know, setting OpenClaw up, getting it up and running for these people and managing it for them. So I think there's a huge opportunity here. And yeah, just excited to jump in. Cool. And before we get going, I need you to make a commitment to me and to the person listening or watching, which is, I need you not to hold back any sauce. I don't want to know just about the opportunity. I want to know how are people doing it tactically and by the end of this episode, what I want is for people to take away, like I want people to know how they can actually make a dollar from this. And is that a commitment, Nick, that you are willing to make to us? Absolutely. Absolutely. I'm not going to hold back anything. I'm, in fact, I think OpenClaw is a tool that allows us to be able to do the things that we have always been able to make money from like automation with AI, but do it even better. And I'm going to show you how to get it all set up so you can do that and the wedge to get going. So let's do it. Yeah. So I guess jumping right in, as far as like getting set up with OpenClaw, you can see here, you know, this is Orgo, this is our startup. You don't have to use Orgo to get started with OpenClaw. There's full disclaimer. This is what I'm using. And what I'm going to do is I have a project here. You can see I have a couple projects and I have Greg. I set you up a project. I hope you enjoy your, you know, five computers. And so you can imagine, Greg, let's say you're a business owner and you have a busy life, you know. You got all the podcasts going on. You have all these businesses you're running, the agency, the idea of browser, all this stuff. And you need, you need help automating some stuff. So what I'm going to do is I'm going to come in. I'm scrappy Nick. I'm going to come in and I'm going to help automate some things in your, in your business, in your life. You know, as a busy executive. And I'm going to get you set up with OpenClaw. So when you open up a computer here, you can see I have it open. This is the the CloudBot one computer I made for you. If I actually just type in OpenClaw to UI, this will open up OpenClaw in the terminal. And you can see I actually already started like, Hey, I'm Greg Eisenberg. And it's all ready to get set up. And so actually what I could do is I could invite you to this project. And then you'd be able to do this as well. Like in your terminal, you'd be able to spin this up. And now you're talking to OpenClaw. So super easy to get set up. Once again, you don't have to use Orgo. You can use whatever you want. You could use I know Manus just dropped their own version of like one click deployment OpenClaw. Also, Kimi launched their version as well. X is down right now. So we can't actually pull it up on Twitter or anything. But Kimi launched their version. And so there's all these options as far as getting started. You could use a Mac Mini, whatever. So the key here Greg with OpenClaw and actually creating money from it is to have the wedge to know what is the specific use case. In a person's business that we're going to automate like first. Because when you see OpenClaw on Twitter, it's very much a personal assistant. It's exciting. It's fun. But all the demos that go viral, including me, I get it. I'm guilty of this too. All the demos that go viral are a little bit, you know, kind of toy-ish. They're a little flashy. But the real power is in finding the thing that actually drives business outcomes saves time for a business, finding that and building the automation around that. So I have something running here. This is my OpenClaw doing looking up products for a business that I deployed for this is a promotional distributorship. And what this is doing is it's looking up products and actually downloading all the product information. And then like parsing all that information, there's all these reports that needs to download. And then uploading that into a Zoho CRM. So it can essentially create a central source of truth for this client. So this is a perfect example here of like actually creating an agent that OpenClaw deploys to be able to automate something end to end. So just to recap, are we all good so far? Yeah, so a few things I just want to talk about. So one thing is when you showed that Orgo screen, you had like five machines running. So what's interesting is, you know, I've got my Mac mini going, you know, I've got one instance. So using something like this is cool because you can have multiple instances going, right? And you can see them all in one screen and in one view. So that's really cool. That was sort of an aha moment for me. Yeah, absolutely. It's like everyone, you know, as far as where you deploy your your main OpenClaw, you can see here, I like I starred in the main one. And so that's like you could have that wherever. But what people don't realize is OpenClaw can spawn sub agents. And I think this is going to be huge for people who start like right right now we're at the phase of what having one OpenClaw. It's going to happen quickly. You're already seeing on it on Twitter memes about like, oh, what if you have a 10 Mac mini is there all the Mac studios are being bought out. So this is happening faster. You're going to want 10 OpenClaws, you know, 100 OpenClaws. Right now you could have one OpenClaw and just have it spawn up to I think eight sub agents. And each sub agent could have its own computer. And you can do this like this is why this is like kind of where orgo shines is you can spend up multiple computers for, you know, each individual sub agent of your OpenClaw. And in this case here, I had it looking on Upwork for actual things that we could automate with OpenClaws is like a little hack here as far as like, well, I want to make money with OpenClaw. Well, oh, I don't know any any business that I can reach out to that could automate stuff for. A great place to start is Upwork because there's jobs on Upwork that are literally posted. They're they're asking you they're like, I want to pay 500,000, 1500, 3000, 20,000 dollars for this AI workload. And you can I spawn to sub it. It went viral into it. I've spawned sub agents to go find all these jobs and then build out little demos for each of them. And then we picked the best one. And okay, let's let's apply for that proposal with that. So that's a little tidbit there on on Upwork and all of that. So which is just kind of hilarious because I mean Upwork, you know, is designed for human beings to complete work, right? It's not designed for machines, let alone multiple machines to complete work. But I mean, as long as the quality of work is good, you know, customers can be happy, right? Yeah. And I think like it's good to you know, it's good to treat it as the as a starting point. Like, you know, if you can save time preparing a proposal for a job on Upwork, it's like, what is that worth? You know, and if you could do just a hundred X volume, what is that worth? So there's a couple things on that of like the parallelization of work with OpenCloss. So there's like, could you have 10 OpenCloss working on a given task and it breaks up that task into 10 sub tasks. And so each OpenCloss does one of those sub tasks. That's one way of having parallelization. But another way is to have 10 OpenCloss working on the same task, just 10 different instances of it. And that was kind of like what I was doing here is, you know, four different instances of the one OpenCloss, you know, or four different OpenCloss doing the same thing of looking up different jobs and upwork that they can apply to. So that's kind of an interesting topic there. But yeah, so like as far as OpenCloss goes, it's it's a huge opportunity. I just want to like throw this in here. And recent Horowitz talks about computer use agents, I view OpenCloss a computer use agent, you know, you're giving an agent a computer and it's able to do it's able to use that computer. It's like it's a computer use agent. But that's half the story. The other half of the story is for it to be able to like click around, actually operate a graphical user interface on like legacy softwares and systems. And so you can imagine like, you know, in here this this automation I built, this is navigating a legacy platform for this client that doesn't have any clean APIs and it's able to click in download reports and actually, you know, be the universal API to be able to solve problems that you couldn't previously solve without computer use agents. So I think there's a huge opportunity here in Andreessen Horowitz, they talk about it and they say we believe that the properly to properly verticalize computer use agents and assist companies and adopting it will be a major area of exploration for startups. And this is like this to me, this screen's OpenCloss, you know, can you create a vertical use case for OpenCloss for a business and actually assist that company in adopting it? I think that's that's the huge opportunity here. So going back to this like workspace we have set up for you, you know, with with with all the people sending up OpenCloss, you could set it up as easy as, you know, I invite Greg to this workspace. I create him a new computer. We could just do it now. I hope OpenCloss 2. I select how much RAM let's do. Let's do 8 gigs, launch that. Open that up and then all we need now to get you set up is to get the, let me get the the curl command for OpenCloss. I copy that from their website and then as this computer loads, we'll be able to then literally just paste it into the terminal. And once I see the interface pop up, boom, okay. So now I'm going to hit enter. And now we're off to the races installing OpenCloss. So like, it's as easy as that. And I think there's this this in and of itself is like a workspace where you can invite people and get them set up with OpenCloss or Cloud Code. I think it's like a huge a huge opportunity as well of like just there are executives right now that are like reaching out to me, like law firms, insurance companies. They're like, can you can I just like pay you to teach me how to use this stuff? So that's its own whole thing as well as far as like if you're savvy enough to even know how to install OpenCloss and get it set up in the first place. I just think there's a huge opportunity around like just helping executives businesses adopt it. So yeah, you can see it's easiest is to get set up. And then as far as like what specific things can we can we automate with OpenCloss, there's a couple it takes a little bit of a design thinking approach. So when you go into a business, let's say you find a project on Upwork and you want to you want to automate that with OpenCloss. Let's say you go into a business and you're talking to the executive, the decision maker, and it's clear that they have things that need to be automated. Well, as far as like design thinking goes like you need to have a clear way of like first mapping like all the different possibilities you can see here, this is something I did in the past of like there's all these different things that you can automate and you want to map them off to very simple metrics. What is the value that we can create by automating this thing and what's the relative effort cost and time. And so we ultimately want to start with, okay, we want to automate things with OpenCloss that are high value and low effort cost and time. And that's like your low hanging fruit. And so you start there. And so like for this client, this was like, this was that. This was like, okay, we're looking at products on this website, we're downloading them, we're parsing all the information, that's the low hanging fruit. So start with the design thinking approach of like, okay, simplest, fastest to deploy. And then you need to map out like the systems design around how is this thing going to be automated, right? So for this client, she's like, okay, I send an email to a client of hers, right? She sends an email to a client and she has a presentation link with all these products. Okay. And all those products, she needs to look at all of them up and get all the information on them and upload them into Zoho. So then your next step after identifying the opportunity is to literally like map this out, I use Figma, you can use whatever, but map out the actual workflow process of like, okay, step one, step two, step three, what is this automation going to look like tip to tail so that we can do the whole thing? Because with OpenCloss on computer use, now is now you can do that. You can do things from tip to tail. It's not like, you know, it used to be where you'd have to like go into a website and click a button and then you'd be able to do some 50% of the whole thing, but then you'd have to copy that and paste that somewhere else and do it on your own. Like we can do it tip to tail. So quick recap, install OpenCloss through computer, identify the next, identify the, the low-hanging fruit opportunities, the highest value opportunities, and then begin to map out what that even looks like to begin with. Couldn't you, you know, sort of, this is meta, but couldn't you use OpenCloss to actually do some of the prior to prioritization on the automation and actually, I mean, you as a human being did the Figma, but couldn't you actually just use the OpenCloss or Cloud Code or something like that to help you with that. So for example, like if you go back to the Figma, like you could walk into a business and basically say, hey, I want to figure out what we can automate here and you do customer interviews with different people on the team. You record those customer interviews, you get the transcripts, you upload the transcripts and then you say, hey, based on that, then you're like, you can actually say, you know, you give this as a reference image. Basically say like, hey, I want to figure out which automation opportunities have the highest amount of value, low cement for cost and time, give me the top three and then create, you know, Figma. And I think there's like a Figma MCP even that you can use and you can say like, hey, like, can you map this thing out based on these customer transcripts? Does that make sense or am I? Oh, absolutely. Yeah. No, that's that's that's the way to do it. Like I whenever I do any kind of call with a client or cut like potential customer, oh my gosh, Gemini for for Google Meet is amazing. You just have it take take all the notes. And then actually that's that's how I even got because I don't know about, I don't know what you Greg, but sometimes when you're in these calls, you kind of for, you know, this this industry, you know, you're in a new industry, you're helping this customer, you don't understand their domain expertise, the the lingo. And so you got to go back and like, okay, like what was it that they said? And so half the granola or Gemini notes or whatever. And then literally ask it to like, okay, what's the step by step workflow and then map it out? It just helps me to map it out visually. But you could literally ask it. Yeah, like you said, based on this transcript, what is the the automation workflow look like? You know, stuff like that. And if you don't want to use, you know, Figma, you can also even say, you know, do output in mermaid code. And then you can use the mermaid code and insert that into an Excalibur or a TL draw or something like that. So a little pro tip there. Nice. Nice. Yeah. And the Figma MCP is pretty cool too. Yeah. Definitely check that out. So yeah. So then once you figure out what the workflow is, right? This is where like you have to actually be able to know, okay, how much how much can I really ask like, how much can I just say like to open call right now, hey, like build this like, hey, build this thing. And you just describe the workflow versus genuinely using something like cloud code to build out like what that workflow would look like with, you know, Python APIs, a genuine automation pipeline and process that your open claw can actually just trigger upon whenever it's like, can actually relevant. So for instance, this this whole pipeline here of like going to these websites, looking at this product information, downloading the information parsing it uploading it to Zoho, the trigger of all of that is, you know, the open claw being cc didn't email and it's seeing that email. It has a link that is relevant for this type of workflow to be triggered. So that that is like the thing that's like the listening event that open clock can do with like a crime job that sets up to just like, okay, listen for this trigger. And then once that trigger starts, it can then activate the whole Python script workflow automation, everything that you would need downstream of that. So you're not relying too much on open clause like, um, abilities in and of itself, you're more of so creating specialized AI workers under each, uh, underneath the open claw that it can call individually, if that makes sense. You know, you talked earlier about sub agents. I think a lot of people are confused about what is a sub agent versus a task and stuff like that. Can you just clearly explain that? Yeah. Um, so sub agents are, um, I, I, there's a couple of ways to view them, right? So like in the context of, because there, the reason I say there's a couple ways to view them is because there's a couple ways of using them. So in the context of like open claw, you can ask it to spin up five research sub agents that I'll go and research some given task. And, and like, and, you know, like I said earlier, you could, you could have it parallelize that task across, you know, splitting it up across each sub agent or having each sub agent to actually go and do the same task, you know, across five different instances. But the next thing around sub agents is that you can actually, like you said, um, maybe think of them in terms of skills. So if you're familiar with anthropic skills, um, you can have like these specialized instructions and rules along with actual code that you can provide to your agent for it to be able to go and do a given task. And this is really nice, um, because it, you know, it gives you a very more, uh, a very more powerful general purpose agent that can do many of your specific nuance tasks, um, across various domains. But the thing is it's like, I want my general agent to be freed up and, uh, to more so just be the orchestrator. And what if the general agent, this one, right, the, the one I have start here can just call a sub agent, like worker number four here to do a given skill that you have created. So if your skill is that it goes on Twitter and finds the most viral ideas and it bookmarks them, um, rather than having your main agent do that. And now you can't talk to your main agent for the next 20 minutes because it's working on that. Can it call that skill into a sub agent and have the sub agent do that? That I think is where things get really interesting. And, and in terms of the context of like deploying open clause for businesses, I would think of everything that you have in terms of an AI automation opportunity around workflows, skills, tasks, et cetera. I would actually just create that as its own, like, specific sub agent with its own skill that your open clock can then call. If that does that make sense? It does. It does. Nice. It's, it's, it's, you know, I think the basic idea is like, you know, in layman terms, it's as soon as you have your, um, your open clause, since, you know, do something, they're busy, you know, it's like they got a, they've got a mug of hot coffee. And so, and your, your job is you want to leverage this as much as possible. So you don't want, you know, your agent to have a hold a hot coffee. So if you ask it to do, to move this desk into this area, you know, it says, no, I'm holding a cup of hot coffee. I can't do that. So what sub agents do is it basically creates leverage for your open clause. And it basically says, like, okay, I'm, you're going to create a set of sub agents who are going to be good at x, y, z thing. And that way it frees up your, your main agent to, to, you know, as you say, orchestrate to basically be the manager of the sub agents. Uh, and, you know, what that can mean is, uh, like looking at, um, quality of work, it can mean, uh, checking for certain things and stuff like that. Exactly. Exactly. I think that's going to be huge, you know, when, when you start working with these businesses and, and customers who want things to be automated, once you show them what's possible, their eyes light up, they get all these ideas themselves. These are high agency people, you know, they, they come up with creative ideas that they want to start implementing. And, and then what you realize is there's just a huge, a huge list of of things that can be automated and they're excited about that. And so actually, like, the ability to, okay, first solve a vertical specific workflow for a customer and then that opening up their mind and then then being like, oh, I wonder if I could, could I text this thing and it does this? This is kind of where, like, the whole open-clone moment is really powerful. It's the assistant-like capability. It's the, you know, I have it here. It's like, a lot of people might get confused about, why is it that open-close so special? It's, it's the ability that has its own computer. It's running 24/7. You can text it and you can schedule tasks and really if, if we just removed open-cloth from this card here and you just called this a really good employee, it would just make sense. It'd be like, oh, works 24/7, can code, can schedule tasks, I can text it and they have their own computer. So I think that's like kind of why open-cloth is exciting for a lot of people. And if it's not, you know, if some people think it's overhyped, you have to kind of look at the whole picture, I think. And then you're able to really gauge it. So I'm certainly bought in on this idea that, you know, it could be a really good employee. I think there's also cases where people are in setting up their open-cloth in the right way where it ends up being a bad employee. And I think, you know, that's sort of like the issue with that is, you know, sometimes you have a bad employee because the manager, the coach essentially, is not doing a good job at giving the right context at the right time. So I think, you know, do you have any tips and tricks around besides spinning up sub-agents, like how could people listening to this, if they want to go after this opportunity of essentially verticalize, you know, open-cloths and automating some of these flows. How could people actually, you know, take their open-cloth from a bad employee to a good employee? Yeah, I think it comes down to, let's maybe we should walk through. So I know you have, I was actually looking at this. So I do a browser. So for everyone, if you don't know, Greg has this amazing product, idea browser. And I love this trend to this idea today. Take talk trend tool that catches viral waves before they peak. So I was actually looking at this this morning. I was like, wow, this is actually something that you can maybe turn into a skill for an open-cloth to create a specialized skill around this. So let's just do a live, let's see, I generally don't know how far can we get, can we build this out now? Let's see, if I copy all of that, and now I'm here in the open-cloth that we set up for you. And you can see it just got set up. I just told it, hey, I'm Greg Eisenberg. So we're getting started. That's it. And let's just say I want to build a specialized skill to be able to do the following. And I'm just going to paste that entire idea browser idea. And I'm going to ask it as far as like creating these automations, creating workflows or doing anything with open-cloth. My number one tip is always ask you to ask you questions. So what do you need from me to be able to build this out? Let's create a plan. And so a lot of people need to remember open-cloth is like a, almost a little bit of a wrapper around like cloud code in a way. So let's see, okay, cool. This is a big vision Greg. I like it. Let's break down a realistic build as an open-cloth skill. So now it's saying, okay, I need data access. I need the scope. I need the niche focus. That'll shape what we build a lean skill. So the first thing that we can maybe do is here in like, or go, we have this playground mode. And you can ask the playground agent here to do things in this computer and this computer environment. So one thing I might test first is like, can we get this agent to even just spin up TikTok and just scroll TikTok and identify what is on the four-year page TikTok. So let's like maybe start there. Does that sound good? Yeah, absolutely. Let's do that. Open Firefox, go to TikTok, scroll. I'm going to say scroll TikTok looking for what the most common videos are on the four-year page. Give me a summary. So let's see how it's able to do this. So this is using our playground mode and boom, opens up Firefox. It's going to go to TikTok. And for those listening, I'm just going to talk through a little bit about what this agent in our playground is doing. It's visually interacting with the screen. It's clicking into Firefox. It's opening up the browser. Now it's typing in TikTok.com. It's going there. And let's see. This is always such a magical experience. It's just watching a computer navigate the web like a human being. It's amazing. You know, this is, yeah, there it is. It's on the homepage. And now it's going to actually scroll TikTok. It's going to probably take a screenshot of this. Get the context of, based off that screenshot of what the video is about. You can even see it. It has hashtags, movie, hashtag for you page. It's going to be able to infer a lot of things. Boom, it scrolls. It scrolls. It's going to pop up. It's going to close out the pop up. But on your point, Greg, Darryl and Tomahday, the CEO of Anthropic, he just had a podcast with Door Cache. And it came out a couple of days ago. And you know what's really interesting, what he said in that, in that, in that podcast. He said, he said this idea of his around this data center full of brilliance, you know, scientists and Nobel Prize winners, essentially his concept of what AGI will be like. He says, the constraint to getting there is computer use agents. The ability to have an AI that can operate a computer like you and I can, but better, you know, interact with the visual interface. Also, be able to do things under the hood, kind of like cloud code. This is the constraint, he said. And I mean, it makes perfect sense. If they can do anything that you and I can do on a computer, that seems like it can go pretty far. Open clause, like a chat GBT moment, I think, for this kind of idea of computer use. And as far as like building these computer use agents out, you can see, this is clearly working. So we know this is possible. You can build a lot of people might get confused with Orgo when they come to our site. They see computers for agents. And like, what does that mean? Well, I think they get it now. It's like, okay, you want your codbot to have its own computer. But also we provide, and I'll show this, we provide the dot in our docs. Like we're actually provide the programmatic APIs so that you can create custom computer use agents that do a given task very well. So you can bring any model. You can get kimi 2.5 is like the super cheap, you know, Chinese model. It's very good at computers. And you can give it the ability to click, drag, scroll, type in the keyboard, spin up a computer. And you could create specialized, really fast, performance, low cost computer use agents, using our docs. And I just say that to say, like as far as, you know, this, this thing that we're doing here, creating a skill around scrolling tick talk. I think that's how we can, we can actually give it a shot. Let's just, we see this is working now. Let me just grab the or go docs and let's start building the skill out. If you didn't see here, I'm at the or go docs. I click this thing called lm s full dot txt. This is like all the instructions for the lm to be able to build on top of or go. And what I'm going to do is, I'm going to wait for, I have to probably, I'm going to wait for this to finish this it's task and then I'll be able to tell it. But while this goes Greg, you have any thoughts? Well, just, you know, sort of a thing I was thinking about is it sounds like when whenever you're trying to, you know, do a new automation, you start by thinking about what is a lightweight skill that I should create. Is that correct? Right. Exactly. What's the MVP? Yeah. So you start with like a lightweight skill. You test it. And then from there, you're probably like, Hey, here's what went wrong. Here's what could be better. That sort of thing. Right. Exactly. Just fine tuning, you know, debug. Like, I think the design thinking process around all of this is super important of like, okay, if I want to build a car, maybe the first thing I do isn't to build the frame of the car or, you know, to build, um, you know, the whole body of the car. That's not the first thing. The first thing I should do if I want to build a car, well, why do I want to build a car? Well, I want to build a car to go to from point A to point B. Oh, okay. So really, maybe I should start by building a skateboard. How can we accomplish the task to get the, get the dream out, the dream outcome? And, um, and sometimes that means like starting with something that's completely different than the end state. Um, so this is done here. I think it interrupted itself probably a context thing, but now we can actually what we can do. This is all live. So you're seeing this in real time. You can literally, there's a couple ways to go about this. You can actually install Cloud Code into this computer and have it build out, uh, the automation in here, or we can just ask this agent to do it for us. So let's see, um, I want to build a computer use agent that does this exact thing, uh, but more programmatically using the org. O API docs. And I paste that here. What do we need to get started? And we send that off. All right. Here we go. So we need an org API key. Here's the architecture of what we'll build. Okay. This looks good. Um, org. O key and throttbit key. It has all the code here. Cool. Um, you're looking at a TikTok video extract the username, video description, the category, the appropriate like count. Boom, boom, boom. Okay. Cool. So I have all these things already. And don't worry. I'm going to delete these keys. I'm not worried about leaking or anything. I'm going to copy my org API key. I'm going to paste it in there. And I'm going to say, org API key. I also have my and throttbit key. Let me grab that. I'm going to paste that here. Can we build this out? And so now we're going to have our, our playground mode build out this computer use agent to be able to go do this thing that we just tested out. We know it works. We know we can do it. Let's turn it into something that could be more programmatic, kind of like a skill. Now let's give it to cloud bots. So it always has access to it. The dream. It's literally any idea you have, you can just build it. And that's sort of the arbitrage opportunity, right? Especially like in our world, of course, like we're so used to this now, even though it's only been like two months. But the opportunity is the vast majority of people on this planet and businesses would love to have better automation and would love to have computer use agents working for them. AK, really good employees working for them. But they don't know how. And so I think which is cool that you're showing us like some of the best practices and how to do it. Exactly. And I think this is also like I can imagine, you know, the whole audience of this podcast, we're all pretty tech savvy. We know how to do things like vibe code and, and, and, you know, play around with cloud code and be able to do these things. And we take it for granted in terms of what that value is worth. As far as like open claw and the opportunity around that, I mean, open claw started going viral on Twitter around two to three weeks ago. Only now is it starting, am I'm starting to see it's starting to go viral on TikTok, a little more mainstream. So, um, yeah, I just mean, you know, people are catching on. And a lot of people still need help with getting, you know, up and running on this type of stuff. And what you might think is, oh, I mean, I have a basic understanding of open claw and clawed bot and clawed code. And you might under underwrite that. A lot of people find that valuable. So, I'm being able to help businesses adopt it or just people in general. I think it's super good opportunity. Yeah. I think my only advice for people would be to focus, like don't be everything to everyone. Like, don't, don't help any every business help real estate agents, for example, or like pick a vertical that maybe you have some unfair advantage for some particular reason. And that unfair advantage doesn't necessarily mean you have 20 years of experience. It might mean just that, you know, you want to build something for real estate agents because your mom was a real, real estate agent. So you know, you know the customer, right? So I think that's the way to do this. Absolutely. It's whatever you know, that's your advantage. And I mean, I guess as far as like some maybe this doesn't apply to everyone. Obviously, if you're in this industry, then go for it. But like, you know, probably things to avoid. Things that I have a lot of like red tape, like healthcare finance, you know, I recommend maybe starting something. Yeah, like you said, you know, you could do even manufacturing or there's a lot of distributors ships out there who you know, they distribute merchandise. Just like the demo I was showing earlier of that computer usage agent working. So yeah, I think as far as, you know, doing what you know, and starting there, and then the market will tell you, you know, the market will pull you into specific verticals. You'll start seeing ways that as you build these specific, this is a great point. As you build out these specific workflows around these verticals of like, let's say you do, you know, let's say you do the manufacturing thing and you do manufacturing for doors. Over time, you're going to have a workflow for almost like every kind of thing you could imagine in that industry. And if you have the agents all built out, can you imagine you have a workspace and you invite, you know, some new company into this workspace that for for automations for manufacturing for doors, like luxury doors, and you invite them and they have all these AI employees in the workspace and orggo set up ready to go. You just see them all here and they're all ready to go. It's like, you feel like you just hired not a person, but a team. I think that's a very near future. In fact, I don't think there's anything stopping us from having that right now. It's all about just, you know, who's going to go out there and put in the work to actually do that. And if you do, I think it's, I mean, it's pretty clear. Yeah, I mean, and that's that's why I truly believe that, you know, agents are the new SaaS, like, you know what I mean. So, I agree with the like the vision you painted, I think that, you know, in the past, you know, we created software that we would sell to these businesses. And then they would have people actually, you know, press the buttons, touch the knobs to make it useful. Now, you don't, you're not going to create software and invite them to the software. You're going to create agents and you're going to invite them to the agents. And then the agents are going to do work that creates value for these companies. So that's the mindset shift. And, you know, it's only recently actually that people have been, you know, I think over the last like two weeks, I would say two, three weeks that people have been like on X talking about this, how agents are the new SaaS. But I do think that, like over, you're going to see over the next two to three months, like some really big winners. And you're going to start to see it work. So I'm excited for people listening because I think that this is the type of audience that will act on some of this stuff. And it'll be interesting to see what what happens. Yeah. Yeah. I think it was it was it Sam Altman that just said, you know, every company is turning into an API company. Yeah. And that's interesting because interfaces are in a sense, dying in that way of like, you know, you won't interact like the ultimate interface for whatever reason seems to be chat and text message. And it's happened twice now of like, okay, the chat GVT moment was a chat box. And now it's the open claw moment, which is like a text message or telegram. So it's like, okay, chat has happened twice. And that just means, okay, so we just want to wait for our agents to be able to use all the tools that we use. And we don't really care about how it does it. It just needs to be able to do it. And it runs in the background. And does it under the hood. So here, okay, I started. I built, you can see that this agent in the playground built out the tick tock agents.py inside the computer. So now I asked open claw, hey, I built a tick tock agent.py in your desktop. Can you take a look? And it's re it says, okay, I've read it. Here's what I see. There's a skeleton for, you know, using or go plus Anthropics API. Go ahead Greg. No, you keep going. And it was, and it was, you know, all the actual tick tock logic, trend detection, all this stuff. It's like, okay, maybe we should build that out. And it's like, oh, you got the API keys, hard code, et cetera, et cetera. So let's just say, let's use this script build on top of it or whatever you need to do. And let's spin up a or go VM inside of the Greg Eisenberg workspace. So accomplish this automation with tick tock. Let's demo it just working. We can spawn a sub agent and VM in this workspace. And let me just give it a API key just in case it needs that. What really blows my mind about this whole thing is that, you know, I was going to say, we're we're building a business in a very short amount of time. But it's really like we're building an asset. Like the amount of assets that people are going to be building using tools like this is going to be crazy. Yeah. It's insane. Honestly, it comes down to like, honestly, like, it comes down to taste now. Good ideas. If you have a good idea, you could just, you just build it. And yeah, there's there's going to be like, oh my goodness, what's going to happen with all of these assets? Like you said, that people are just going to build and build and build. There's going to be so many assets. I think is this what is this what we mean when we talk about the the abundance that AI will bring, you know, of solving all these problems? Yeah. Well, I think what ends up happening is, you know, unfortunately, there are going to be more and more layoffs as AI helps with productivity. At the same time, I think there's going to be a renaissance, the golden age of entrepreneurship and people creating assets, products like this, one person businesses. And that's how I see it playing out. Yeah. Even even and maybe we don't know officially, but maybe it's already happened with Peter Steinberger, the creator of OpenClaw. You know, he just officially announced he's joining OpenAI. Like, I think it was just him who built OpenClaw. How much did he get, you know, aqua hired for? I think it was a lot. So that's that's, I mean, that's that's cool. I think this is the best time to be a builder/tinkerer to get creative. I'm excited to see what people build with OpenClaw and computer use agents in general of like, is there so many things, you know, whether it's a super fast chess computer use agent or if it's something that's genuinely driving and outcoming your business. Like, I just think there's so many things that can be built. Playing around with these tools, getting familiar, learning how to leverage them. Yes, AI is going to be replacing a lot of jobs. But also, it's going to enable a lot of people to do things, you know, that they've never been able to build before and now they can do it. So, yeah, I'm just, oh, here it is. Okay, so you can see it spun up this computer, TikTok trend hunter. My screen's just refreshing. Let me just click into it. And, and I could just tab back and forth a little bit to see, okay, the M is up. It's opening Firefox. Let me wait for the agent loop to start. Here we go. So it's spun up its own computer. This is insane. It's spun up its own computer. Openclotted. And now it's, it's using its own Python script that it just made just now. We took it from my D. App browser. And now it's going to go do this thing that we just built out. I don't know how long this took last like 10 minutes. Kind of just, you know, in between we're talking and having a coffee. This is insane. I don't know. It kind of, it makes me, it gets me giddy. It's like, and it's going to figure this out. It's like, you know, it's going to debug. Okay. What's going on? Why am I on the ads.tiktok.com? Let me reroute myself. I'm sure it's going to figure all this out. But it's just cooking, you know. Crazy dude. Crazy. Anything else you want to cover before we head out? Yeah. I think as far as other things to cover, I mean, I just want people to start thinking about these tools. You know, yes, they're, once again, they're great personal assistants. But if you start thinking of Openclotted as an in-aid in or you start thinking of it as a, you know, like a Lindy AI of like, you know, people, there are real businesses right now. Like we can go to Upwork right now and find jobs that are being posted around, you know, things like this is what you do. You just go to Upwork. Upwork's great because you get to see what the market's asking for. And you just type in robotic process automation. You know, this old outdated way of programmatically automating tasks that it's like clunky and it breaks and it's not intelligent. If the button isn't in the exact UI space that you just delegated it to, it won't work. And you go here like posted yesterday, Android RPA automation posted yesterday, automation pipeline for client upload. You go here, you could just do let's find $500, $1,000, $5,000. Let's look at all these projects. Okay. This one, boom right here, $1,000 budget. I'm looking for experienced automation engineer to build desktop automation, computers for my software business. We sell a specialized dynamic PDF. You take all this context, give it to OpenClaw, give it to CloudCode. How much of it can you build out as a demo based off of this context alone? Send a proposal. You have your first customer right here, $1,000. Get some case studies, leverage that, maybe go deeper into this industry that this person's in, start building out specialized workplaces in CloudBot OpenClaw for all the different vertical use cases in that. Create a workspace of it. I think that's where we're at right now and I'm excited by this. So yeah, I guess we'll just see where it goes and yeah, okay, this needs a little debugging. As to be expected, we spent 10 minutes on it. But I think you get the gist. And yeah, I'm excited to see what everyone builds. From your lips to God's ears, baby. I think your approach makes complete sense. It's the exact approach I would use, totally recommended. People get your hands dirty, get tinkering. I'm excited for what you build. Nick doesn't do a lot of podcasts. I think I was only able to find him do one live stream before. So show him some love in the comment section. Like the video. Show him some love. And Nick, I hope you come back on, share more use cases. I'm going to be sharing more use cases that I'm using that might, you know, I haven't done too many publicly. I'm going to be sharing more my use cases both on virtual machines and on my own Mac mini for my OpenClaw stuff. So get ready for that folks. And Nick, wait, is there anything? Is there anything else before before we go that you want that you want to share? I just want to share with you, Greg. You don't know this. But I've been a long time follower. This is my YouTube rewind 2025 top point five percent. So if you're watching this and you love Greg's podcast, you love his videos. You get building on top of it. You put cool stuff out there. You join your top YouTube channel on your rewinds of the year. I love it. I love it. Nick, you're a legend. You got to come back on. You're one of us. You're one of us. So appreciate that. Thank you, Greg. Thank you for having me.