I Made $250K In 30 Days: The FASTEST Way To Make Money & Build Automations (Claude Code)

0:00When you build something in Claude Code, it's incredibly easy. You don't have to be technical at all. I said right here to Claude, I want leads. Go get them now. And it does it. And this ran in under 10 minutes. There are 50 leads in here just like I asked for. And then what it does over here is it creates me a personalized email subject and email body. You start using AI within a year

0:19or two if it's doing $250,000 a month. What are the opportunities that you're even seeing? I think the advice that I would give myself would would be to pursue a service-based business in AI. Someone pulls up the desktop app with Claude Code. What are the first few things that they should even be doing? There are a few things that you want to

0:38do right away. Before we get into the episode, I have to say that it's pretty surreal to me that I get to do this and record this show for you guys. and so many of you tune in and leave comments and likes on the content. The reason why I do this show and I record every single week is that I want to show that anything is possible. Any dream, any delusion that you have in your mind right now, you can bring it to reality. One of my goals at the moment is that I have this crazy delusional dream that this time next year will reach a million subscribers on

1:14this channel. And so if you click that subscribe button, the promise that I'll make to you is that we're going to improve this show every single week. And so I want to take you on that journey with me. So hit that subscribe button and let's get into the show. This morning I was watching one of your videos, actually your uh course on

1:32claude code. Okay. And right in the beginning, you said something that stuck with me. So I wanted to give it back to you. You said, "I don't have a technical background, but I but I've been able to do some pretty incredible things with Claude code. I've got multiple businesses, content, education, events, consulting, and all of it is powered by a small team that's just effective at using AI." And so Nate, I think about the person that's listening to this at home that's curious about AI and Claude code, but even when they hear that, they feel like it's too complicated for them. It goes over their head. This is for technical people like

2:13coders. If someone has clicked on this video with that feeling before we even get into the detail and the weeds of it, what would you want them to know? I would want them to know that getting results out of AI at this point is just about communicating clearly what you want. And I think as humans, we're very good at knowing what we want. And we kind of get in our own way. And I think it's really interesting. You even hear these people Boris Churnney, Sam Alman, these people that are making these foundational models are giving advice like give AI a task that you wouldn't expect it to be able to do and

2:53just see what happens because it can really do some incredible stuff. And like I said, it's really just about communicating clearly what you want and communicating clearly what good looks like. And I think those are just the two most important things. So yeah, you don't have to be technical at all. Yeah. You know, you know, I think it's such a a big thing because I think a lot of what holds people back is like this intimidation factor. And it's interesting because you and I, we were having a conversation a few weeks ago,

3:18even in the planning of this episode. You said something that was interesting to me. You said there's a model that's so strong that the government took it away. You're talking about Claude uh Fable. But then you said on the other side, we have people that haven't even opened Chat GPT ever. And that gap is ginormous. I'm just curious because you come across so many people with your consulting with what the educational

3:44things that you do with your content. It almost sounds like there's like two worlds when it comes to AI and there's like the power user and then there's the person that's really not fully engaged with it yet. Can you talk about what you meant at the be what you meant in that quote when you said that gap is

4:02ginormous. It really does feel like there's two different worlds. It really feels like me and all of my buddies in the AI space and everyone in my community is, it feels like we're living in this this AI bubble and we're trying to all keep up with this new cycle and there's so many different things coming out every day and we're seeing all these crazy things that people are doing with AI like what happened with that model being so strong that it got taken away. But then on the other side, you know, whether it's because people aren't interested or whether it's because they don't have access to the right tools. Like for

4:33example, some of my friends that I graduated college with at their jobs, they're maybe only allowed to use something like C-pilot. And so their experience of using AI is it doesn't really give me the right answers or it puts the wrong formulas in my Excel sheet. So h AI is is hype. It it's I haven't felt the ROI myself. So how could I ever like be convinced of this ROI? And I think that's the the moment people need to have is where they enter in one prompt and they get something back that isn't just an output that they have to fix, but it's an output that's

5:02like, "Wow, that would have taken me an hour to do and I got this in 2 minutes." And once you have that moment yourself rather than just like seeing a demo or seeing a LinkedIn post, I think that's when it's just like it opens your eyes up completely and now you're in then you've entered the AI bubble. Yeah. You know what's so good is that I think there's Nate there's going to be people that listen to this conversation until the end and they have that moment like after listening to this that moment [laughter] and so you said something which is interesting which you talk about the

5:34people that use like AI in the workplace and they use co-pilot and it's like not really this great experience and I think for that person because I've been there you then hear like terms like clawed code and even if you see people and like the value and what able people are able to build. It just sounds technical and I think it's because it has code in the

5:54word. Yeah. Like it just sounds like okay you need to kind of be a coder a software engineer to get this. Can you just make it clear for people maybe those people that have used co-pilot or they use chat GPT here and there? What could be the impact in their lives if they're able to internalize some of the things that we show them in this conversation and actually get started using clawed code in some of the

6:19ways that you're going to demonstrate? What was going to be the impact the significance of that? I think what they're what you're going to feel immediately is that you now have a system that you aren't having to repeat yourself to. So if you are a frequent Claude or Chatbt user, you're probably feeling a lot of value already because you're generating docs quickly or you're generating presentations quickly, you're doing research quickly, but you probably are having this moment where you're thinking, I have to reexlain my priorities. I have to reexlain what my team looks like or what we're driving towards or like my brand guidelines. But when you build something

6:53in cloud code or codeex, you're building a system that has memory. And and I joke with my team now like if you want to get an answer from me, you're better off reaching out to my AI operating system than me because it's going to respond faster and it's going to have a better memory than I do. So, not only are you creating something that compounds, it feels less like a co-orker, it feels more like a co-founder, you're also getting things that can instead of having to do the copy and paste, oh, copy this from chatbt into my email or copy this and you know, put it over

7:22here. it just has the hands to actually take action as well and it can then start to do things while you sleep and you wake up and you're already like you know halfway through the day. So I think overall what you're going to feel is if right now one unit of effort let's call it is getting you three units of output once you've adopted this sort of new way of working one unit of effort is going to get you 10 units of output and that's just going to become the new baseline. M like it just makes you way more

7:50productive. Way more productive. It's uh it's interesting, Nate. I got excited in the leadup to this conversation because specifically for like non-technical people because a few years ago, like you were that person like you were the person that was starting to use some of these tools. You you were non-technical. You're actually like an intern at Goldman Sachs. And then in just the last couple of years, you've gone from that to you're running multiple businesses to the point you even you're a successful creator as well to the point where you even had an agency where you're making hundreds of thousands of dollars a month at one point. Can you just high level just map

8:36it out for people cuz it sounds almost like unbelievable when you hear it like just the speed of it. How were you able to go from a couple of years ago working a pretty like an entry-level job at Goldman to then being where you are now? Like how does that even happen? It has happened very quick. I've always been in the the business of let's help small teams be empowered to do more rather than let's scale without ever hiring humans and let's fire a bunch of humans. That's always been the way I think about it. But ultimately before I brought on the team, you know, we were I

9:10was at some pretty significant milestones and was growing very fast. The channel was growing very fast. The communities, so was my my freelancing business. And I think one thing before I even talk about like the AI systems I used, it all was very cohesive. But then from there, I was able to build a bunch of systems because I I identified repeatable and just like kind of boring processes in my own workflows. You're

9:35not asking your agents to do things. They're just taking action proactively. And when you get into that sort of world, it really opens up a new opportunity for you. I started the business in November. In December, I got really, really sick. Ended up going to the hospital. And during that month when I couldn't really do anything, my business, if you look at the revenue, if you look at the views, nothing really took a hit because it was still just me at that point. But I had the right things in place where I was able to just kind of not be the core constraint. And so even if I wasn't sitting down working

10:09every day, my agents were still letting me know what not what needed to be sent or reaching out to the clients and letting them know that we had this this bottleneck or whatever it may be. Um, and that's when I realized how much you can really do as as one person. Yeah. You know, one of the things and it's uh it's crazy for me, Nate, like sitting in this chair and getting to speak to people like yourself because and and we'll get into it in a few minutes. You'll share your screen and you'll like show these workflows and it opens up my mind because I was like, I

10:42didn't even know that that was possible using AI. Like I didn't know that it could actually do this. And it's funny because we always hear about this reality where like uh people used to talk about it even a year ago, 18 months ago, but it seemed like this distant reality where we'd have like AI

10:58employees that do tasks on our behalf. And so I think about that story and that image of like unfortunately you being in hospital or like what happens all the time for us in work. There's sometimes where we can't work because of unexpected circumstances, but then it's like these systems and these workflows were able to take over for you. And you know what, Nate, here's where I want to go because we're going to specifically go into Claude code and it's interesting. I had a conversation with this creator named Olia a few weeks ago and he showed and it was like this stunning moment for him where he showed

11:39how he was able to build this website and like digital membership platform um using Claude code and in the first week that it was live he made $20,000 for it and it was like I built this in a weekend using Claude code. Can you just share for people before we go into the workflows and everything that you have? What was kind of your first moment with Claude code specifically where you were like it's kind of unbelievable to me that I can even build this and it actually led to like this downstream effect and like impact for you either in the form of like saving time or helping you even

12:20generate revenue in your business. like what was that first almost spark moment with claude code for you? I see you smiling even. Okay, so what I found is that one of the easiest ways to use AI to be more productive and save time is to connect your favorite tools to the AI model that you're using. But sometimes what you'll find is that your favorite tool won't actually be available as a connector with inside Claude or Chat GPT. And that's when you'll want to use

12:45the Zapia MCP inside Claude or Chat GPT. For example, the other day I wanted to connect YouTube to Claude so that I could do some research on thumbnails and titles that are working in my niche. So, I went to the connectors tab looking to find the YouTube connector, but I couldn't find it. And it was this really frustrating experience. But after asking Claude for help, I found out about the Zapia MCP and how it could help me connect YouTube to Claude. All I had to do was go to Zapia MCP. Search up Claude here, click on it, click add apps here, and then just search up YouTube, click

13:21on it, and then click select all tools, hit connect, and then hit connect again. I then typed in my API key, and then once YouTube was connected, I click on connect right here. And so you can follow this simple two-step process to connect Zappia to Claude. And then after that process is complete, I can come in here and tell Claude that it's connected to YouTube through the Zapia MCP. And I can ask it something like, "Please go find the thumbnail and title formats that are hot right now in the business podcast space." And it went ahead and did it for me. And so if you ever run

13:54into the same issue where you can't connect Claude or Chachi PT to your favorite tool, go to the link in the description and use Zapia much in the same way that I just did and you will get your app connected. Okay, so a lot of you watching this episode might be struggling to get bigger customers for your business or maybe even struggling to scale your business. And it might be because you don't have a way to prove that you're trustworthy. Even testimonials aren't enough in this new

14:18era of AI where anything can be faked. And so potential customers want to see proof that you're secure. And one of the easiest ways you can do that is by using Vanta. Vanta is the marketleading agentic trust platform that gets you compliant fast with in demand frameworks like sock 2 ISO27001 and HIPPA and keeps you there and so when you show these frameworks to potential clients they immediately trust you more than other companies that don't have these frameworks take Hyperbound a Y combinatorbacked startup they used Vanter to get compliant proactively they proved to enterprise buyers that they took security seriously ly and they unlocked the Fortune 100 in less than a

15:01year and generated $1.5 million in under 3 months. And now the cool part is you can access the Vanta agent within other tools that you use on a daily basis like Claude, which is why Vanter is trusted by more than 16,000 companies like Ramp, Harvey, and Writer. And so if you want potential customers to trust you more, hit that link in the description to get

15:24$1,000 off at vanta.com/calum. Yeah, cuz I I remember it. I remember literally feeling like a kid on Christmas when I discovered what I could do. And at this point, I had been running my YouTube channel for a little over a year. I because I only really dove into Cloud Code about 6 months ago, honestly, maybe a little bit, seven

15:44months ago in like January of this year. So, I had kind of built my whole brand around NAN, which was a automation building platform. It's kind of like make.com or Zapier. And that's kind of I was like the NAND guy. And when I first picked up cloud code, what I went to right away was, okay, let's see if I can use cloud code to help me build an NAND

16:03workflow. And I'm pretty solid at NADN. I could build automations in Nen, you know, a pretty complicated system in maybe 30 minutes to an hour that might take the average person a couple hours, right? And I started talking to Claude Code about, hey, could could you connect to my Nident account? Yeah, of course I

16:22can. Just give me this credential. Cool. I gave it the credential. Can you see my workflows? Yeah, I can see all of them. I can see you've got these in production. I can see these have run this many times today. Okay. Could you build me one? Yeah. What do you want me to build? And so I basically just sit there. I I yap into my microphone for 2 minutes and it says, "Okay." 5 minutes later I come back and there's a workflow done and I go into edit end and this thing is like almost done. It wasn't perfect, but it was almost done. And all I had to do was I remember mapping a few

16:48variables and putting in some test data and hitting run and it ran all the way through. gave me the output I was looking for and I was like that just took me 10 minutes and I went off and like I grabbed a snack, got more water, came back and it was done. And that would have taken me like probably 30 to 45 minutes of like sit down focused work and it was just done. And all I did was talk for 2 minutes. Then from there I just started pushing it as hard as I could to see what was possible. But that was the moment where I was like this is

17:16going to change everything about how I work. Yeah. You know, I think about that visual of like everything you asked it if it could do. It was just like, "Yeah, I can do it." Yeah. And it's um even just that visual of you like talking into the mic and then like a few minutes later it's like there's actually something built. It it sounds

17:35almost like science fiction, you know? And one of the things that I wanted to ask you is because what you described sounds very simple and I think because I also put myself into this category where like I've historically kind of avoided procrastinated away from using clawed code and much of the reason why was the terminal was like this term like I'm I'm non-technical. I'm not a coder and the terminal just looks I don't feel like you get more technical looking than the

18:03terminal. Yeah, it's ugly. So, like I guess my my question to you because the way that you describe it, yapping into the mic, it doesn't sound like you even needed the terminal. Can you just clear that up of like for someone getting started? Do you even need a terminal to get started? How easy is it to get started? It's incredibly easy. And now they have a desktop app that's pretty solid. The

18:23desktop app looks almost the exact same. It looks almost identical as clawed in the web that you're probably used to. So when we pull it up later, you'll see that you don't need to ever look at the terminal if you don't want to. Um, but yeah, I mean I wish like they have cloud co-work and cloud co-work's really good at automation, but cloud code is just the most powerful. But I do wish they didn't even call it cloud code because I think that word like you said earlier does scare a lot of people away from

18:49opening it up. Yeah. You know, uh, Nate, I just think about what you mentioned earlier with like the impact that this technology has had in your life and so I just want to get into it for people. So, can you share your screen and just show us high level some of these different workflows that you've been able to build using Claude Code that have helped you save time or even generate money, revenue for your business? Kind of give people that

19:17picture. So, this is what we're looking at right now. This is the Cloud Code desktop app. And as you can see, you've got a chat down here. You have a few little options here that's like it's choosing a pro a project to work in essentially. But you know, if you're over here in chat, this is really all it is. You have all your chats on the left. You can switch here between chat and co-work. You can switch between the different models and you just talk to it. And that's the exact same way you should approach using cloud code. You know, I think a big part of

19:46working with AI is so mental. It's all about mindset. And I actually wrote an entire book. It's like it's right up there. I wrote this book called Becoming AI Native. And the whole book is just about changing your mindset. It's about what do you reach for first and how do you talk to the thing and how do you have the thing prove to you that it is done and that it did good work. It's so much just about being a good like manager. If you if you're someone who has had people work for you and you set expectations and you tell them this is what good looks like, then all of

20:17those skills transfer really over really well over to just like managing agents. And I think that's a a big kind of like thing for people to realize from the people that you've interacted with and the conversations that you've had. What do you typically see as the biggest mindset shift? I think there are two big moments that I always think of. The first one is exactly kind of what I told you earlier in my story where just be curious. Just

20:44ask, is this something that's possible? Can you do this? And you'll you'll realize that it's it's not a binary question. You know, it's not can AI do this? Yes or no? It's to what extent can AI do this? So, that's kind of the first piece. The second piece that I think that is really cool, and I'll I'll I'll show this off later, is

21:02what normally happens when you use AI. you get some sort of output and then you're like, "Okay, I'm the human. I have to verify that this is good." You know, I have to check this. I have to test it. But you can also have AI test it for you. So that way you're not getting the first output. You're getting like the eighth output because the AI agents or maybe like teams of agents have reviewed it, have discussed it, iterated on it, they've proven to you that it's good before they even give it to you. So now instead of AI getting you 70% of the way there, you're getting

21:32something that's like it really just needs a quick review and it's already good because you've set the standard of this is what good looks like. Don't stop until you've hit this metric. You know what I mean? I I believe that I heard you say it. It's like um AI prove your work. It was like the this this process and we're going to show it cuz I thought it was so good. we're going to show it later of there's this actual process that like steps that you build into your process where the AI actually proves its work and there's like things that you're doing like tactical things that you're

22:02doing to add that in. Um 100%. But yeah, let's let's show some of these workflows. Cool. So yeah, there's four things that I wanted to show off today. Um for some of these I have the the original prompt and you guys will see it's just one prompt and then some of the other ones I just have like the final output to show you. Let me start off with this one, which I think is always pretty cool to show. So, I said right here to Claude, I said, I need you to use my Clay, so like you know the software, use Clay inside of my project to help me find 50

22:30enriched and optimal leads for my business that I can reach out to today with personalized outreach messages and give this to me as a Google sheet. And so, what's really interesting about this prompt is I didn't instruct it here, what are optimal leads? you know, I I didn't have to tell it about my business because it can look through my project and it can figure out who is Nate trying to sell to and who would his, you know, ICP be. And then it goes ahead and I'm like basically what happens is it starts to go through tools, right? Like it will call things. It will think, it will

23:02reason. And that's what you call the agentic loop is basically like thinking, taking action, inspecting, thinking, taking action, inspecting. And it just keeps looping through. And you'll see it does a lot of things. And then all the way down at the bottom, it basically says, "Okay, cool. Here is your deliverable." So, just super quick, Nate, what is Clay? Clay is a software that has a bunch of B2B leads. It's got B2B leads and then inside of Clay, there's also like automations you can build. So, it's been around for a long time. But what I really like, the way I like to think about Cloud Code or Codeex or whatever

23:36tool you're using is I don't really want to learn a new interface. You know, I don't want to learn a new tool. I don't want to learn a new UI. But all I had to do was give Claude my API key. So essentially my password to Clay and it went to Clay and it figured out how to use the entire system. So all I say is I want leads. Go get them now. And it does

23:54it and I don't have to learn a new tool. So that was the value prop here for me with with Clay. You interact with Claude Code. Claude Code figures out how to get what you want from whatever the tool is. Clay. Exactly. Exactly. That that's what I think makes it so cool is you can a really good quote that I that I always quote is you can outsource the thinking but you cannot outsource the understanding. So you have to understand why are you asking claude to do this and when it comes back with data what does the data mean and how do you use it but

24:27you can outsource as much thinking as you want. Go figure out how this tool works and then explain it to me. Go research all of this stuff and then bring it back to me. Everything everything that I learn, everything that I make a YouTube video about, I have Claude teach me. It does the research. It tests things and then it comes back and says, "Hey, here's what you need to know." So, let me show you this output that it gave me. And this ran in under 10 minutes. So, now I have this Google sheet. You can see that there are 50 leads in here just like I asked for. And

24:57all of these, if you look at the title, president, owner, company, owner, business owner, co-owner, coowner, general manager, owner, president, business owner, company, like founder, president. These are all people that have decision-making authority. What I did is I have this demo project where I have a fake business in there and all of these people, you can see all of these leads fit into one specific category. And it didn't just find leads for me, it enriched them, it did research on them. You can see that we have like information about their reviews. We can see what they're getting on Google on Google Maps. We can see if

25:30they're, you know, advertising 24/7, if they have online booking. We can see all this information. And then what it does over here is it creates me a personalized email subject and email body. And so now all I I could basically just say, "Hey, can you plug this into Clay?" Because Clay can also do email

25:46campaigns for you. And say, "Okay, cool. I've read through those. I approve them. Go send them off for me or go schedule all of them." And so now I've been able to just kind of build the system where whenever I want to send off more cold outreach, I can just ask for it. So that is one quick example that I think is is really really cool. You can see it comes through and it it verifies all this and it does all the research and then what you guys didn't see is in the process it didn't stop working until it had 50 enriched leads. So it probably got like

26:1650 initially and then it realized, okay, I I I reran this and I checked through and some of these weren't good. So, I scraped 10 more and it just kept doing that what I called the verification loop until it knew that what it was going to give me was good. And and to be clear, Nate, that verification loop, is that because of something that you've set up with your clawed code or is that just natively like out of the box, it just will do that? The harness cloud code is a harness wrapped around the model and the harness will do few checks and I I'm I'm

26:52assuming every single month when they push out updates it will get better and better at verifying on its own. But that is something that I bake into my instructions and my skills and my prompts that it should basically never give me something that's a first pass. And real quick before we move on to the next one, I wanted to show you guys this. So in this run, it was nine research agents that fetched all the company data and found the hooks and everything. wrote all 50 emails and then right here you can see two adversarial verifiers fact checked every claim against the recorded site facts and they

27:23caught five real problems and all five are fixed. So if I didn't have this verification I would have had to catch those problems and I might not have even caught those and then maybe I'm sending out data that's wrong or I'm emailing the wrong people. So it found those and fixed those and then it gave that to me

27:39which is obviously huge. Yeah. You know, you know what I love, Nate? Even as we just do the the next workflow, and this is why I got when we spoke about this before, it's why I got excited. I think that the reason why I think there's a group of people that start using clawed code or like a codeex or a program like this and they get super excited, they, you know, they start yapping into it similar to what you did. And then the first output that they get is just not good or it's like mediocre at best. and it like punts them off and they're like, "Okay, this thing

28:12was just all hype." Like it was all a hype cycle. And so the idea I feel like what you demonstrated de like displays it so clearly. It's like, oh, you saw the first output, but you can actually build it into the process where you're not seeing the first output. You're seeing the one where it, you know, it checked itself and it iterated by itself before

28:33then actually giving you a good output. And I think that would just change the experience of so many people is being able to see that. Absolutely. Absolutely. Yeah. I I talk about that a lot and I call it the the bike method. just kind of the understanding that the first time you start building this stuff or or building a skill or a workflow or whatever it is, you have to kind of think about it the same way you would teach a kid to ride a bike, you know, cuz I think a lot of people jump into an AI chat and it and they start talking and then it's like it's like

29:04they put a kid on a bike and then just kind of walked away. That's just not going to work. You know, you have to kind of be there. You have to watch. You have to guide. You have to say, "Hey, you know, you're leaning too far to the left. Why don't you kind of center out a little bit?" you have to give it a little bit of feedback and iterate. And it's only that way that you can then start to, you know, then you put on the training wheels and you can step back and then you take off the training wheels, but they're still wearing a

29:25helmet. Like you're still being safe about it. But just the understanding that this is going to take a little time, but once you get there now, the kid can go off and and ride the bike, you know, 20 m hour down the road, and you won't even worry at a certain point. But I I I'm really glad you called that out because it's it's super important because that's the worst thing is when you see someone try it, they're not

29:43impressed. and they give up. Yeah, the bike method. So good. Absolutely. So, this second um use case I wanted to show you guys. You can see right here what I said. I said, I need you to pull me a report on my YouTube analytics through 2026 so far. So, I want a Q1 report, a Q2, and a Q3 up to today because we're only about twothirds through Q3. And what I did here is I gave it my motivation because if you just said this, that's also a pretty vague prompt. And this is still pretty vague, but the more specific you can be and the more context you can give it

30:16about why you're doing something, it's able to then use that context to give you something a little bit more tailored. So I said, my motivation here is just to see the trends, see what's been working and identify what type of content I should be focusing on making in Q4. And I asked for it as a Google sheet. It could have made this as an

30:32Excel. It could have made a PowerPoint. It could have made a video, but I wanted a Google sheet. So that's all I said. It goes through my project. I don't have to give it a new API key. I don't have to give it new data. It knows my audience. It knows me. It knows how to get to my YouTube analytics. And it just goes

30:48ahead, you can see, and it just reasons. It does the agentic loop. And then it comes all the way back and it gives me a Google sheet. And so, similarly as the Clay output, we get a Google sheet that I can open up. I can go ahead and share with my team, whatever I need to do. And this one is a lot more data. You can see already at the bottom there are six tabs. We've got the overview which shows things like each quarter we can see the views, views per day, watch hours, view duration, subs gained. We can see all of these statistics here. We can see the

31:15monthly trends. So each month we can see these same statistics. And then when we really want to get into these next sections, I'm assuming these these are all going to be very similar. But just think about how much time this would have taken me to do myself to format the sheet. That's one thing. But to go through, I don't know, um I would say at least 200 videos so far this year. Well, maybe not 200, but definitely in the hundreds, right? 150 videos maybe. To go through and pull each statistic from all of those videos, find the averages,

31:46format the sheet, throw them in here. That would take me probably, I'd say, at least three or four hours of manual work. And this was one prompt. Went to the bathroom, came back, and it was done in about 10 minutes. And this is like useful real data from straight from my YouTube dashboard. Yeah, I I need to do this. You know, I I'm I'm curious, Nate, once you get an output like this, like you get a report like this YouTube report, and obviously you're someone that creates content prolifically, what is it that you do next? Like what how did you then go and use this? Did

32:20you even And in that and in those next steps, did you even use AI or was it more so like now you're just analyzing the data yourself? Yeah. Well, for the most part, this is good to keep context in my system. So now it always knows, okay, we just pulled this report. If I ever need to look, I can go here. Um, but if you go back to what I said about you can outsource the thinking but not the understanding. Normally at this point, I like to look at the data myself. I like to try to form a story out of it, but I still use cloud code as a thought

32:51partner here. I ask it, oh, why do you think this happened? You know, can you do any research on Q3 and see why did we have the spike or why did these videos do better? And it can pull in other data. The other really, really um helpful thing here, which I didn't show off in this specific example, was that it can go grab all the comments and it can look through 100,000 comments in, you know, 5 minutes and it can give you common themes. So, I do have automations that are constantly every week saying, "Hey, this week you had 300 comments and

33:20here are the three big pain points. These are probably things you should make videos on." Same thing with my school community. Every week it goes through and it looks through all of the tech support questions, all of the business related questions. Here's our here things you should probably make videos on. So like ideation is not really an issue anymore because now it can get primary data from my sources but it can also look at you know competitors or it can constantly be scraping X for news and I just have all of this this aggregation of data being brought to me but then I'm the one who ultimately

33:47wants to be able to make the decision from that data. Yeah. You know it's so good I I keep going back to that quote that you mentioned earlier that you can outsource the thinking but you can't outsource the understanding. And on that point, I think the reason part of the reason and I'm even just thinking about the person that's listening to this at home cuz it's what I'm thinking seeing it. Part of the reason that you're able to get so much value from claude code and it feels from what you're showing like it's very seamless within your processes is that claude your claude code has access to a

34:20lot of the the tools and like login and credentials that it needs to pull this information. Can you kind of just take us behind the scenes for a second? I know you mentioned it with like the API key with Clay or like I'm even curious here like how it even has access to your YouTube analytics. Can you just describe high level? Is this something that you almost did in the beginning of using clawed code was like setting up these accesses and like how easy was that to do? Cuz I can see that being a stumbling block for a lot of people is like their clawed code just doesn't have the access

34:59to get into some of these accounts and credentials that would then give them this information so seamlessly. 100%. Yeah. And I'll go ahead and share this tab real quick. So the way I use cloud code or codeex, any of my AI tools, I call it an AIOS. So it's a term that's going around right now. It basically just stands for AI operating system. So what I did is I put myself basically through this challenge where everything I do on my computer, instead of opening up Chrome, instead of opening up these different apps, let me just do it only through cloud code. And the reason I wanted to bring this up is

35:33because there's four main pieces. I call this the four C's of an AIOS. The first C is for context. This basically means, can your AI system have all of the context about you, your business, your priorities, and your goals? And once you get all that business context in there, that's where you get to the point where you're not repeating yourself. That's kind of like stage one. Then you have connections, which means, can your AI touch things that you need to touch every day? Your email, your calendar,

36:02your Slack, your school, your YouTube. And over time, you just build up these connections. And then these last C's are basically about capabilities and cadence. Meaning capabilities, you build automations, you build skills. And then cadence means you turn those on so that they're not only triggered by you, but they're also triggered by actions. So that when you're sleeping, when you're on vacation, when you're at lunch, things are still going on. And so once you set up all four of these things, you know, you're constantly adding more. You

36:28know, every day I add more context. Every day I add more connections and capabilities. But you've got a really really good foundation that you can just keep building on top of and and then you know you just you just move so fast. Yeah, you're really good, Nate. The way the way you [laughter] just explained

36:44that you're you're very clear. Thank you. I appreciate that. That's what I've tried to do. Yeah, you you've mastered it. So this next one I've got two um two pieces of this that I'm going to share. So right here I said, "Hey, so I'm about to jump on Callum Johnson's podcast." And I gave it the brief for the episode. So I gave it just, you know, this Google doc and I said, "I want you to create me a quick 10 to 15 second animation thanking him for the opportunity and tailor this towards what we're going to be talking about today and hoping that

37:13the audience will get value out of it." I told it to do this with hyperframes, which is just basically a um it's a little open source project that anyone can use that helps you create motion graphics. So, I said it should be modern, clean, liquid glass, motion graphics that tell a story, not just text. And so, it loaded up my Hyperframes project. It looked at any of the Hyperframe skills that I've built in the past. And then it go it went ahead and created this 15-second video, which

37:36I can just sort of play right in here. So, kind of like what we had talked about what agents can do for you. Analytics report websitely clone the first output as a starting point. And Callum, thanks for having me. Hope you guys get a ton of value. So, that obviously wasn't a crazy output, right? But if anyone in this audience has ever animated stuff, like a 15-second clip that you're animating with motion graphics and and key frames and everything could take you an hour to animate. And a lot of the things that I'm doing in some of my video editing and some of our courses, it's a full

38:09pipeline now where I just drop in a raw file and I say, "Hey, can you like, you know, cut out the mistakes, throw in some motion graphics, and then, you know, let me know when it's done." And it it can do a lot of that. I also just because that that wasn't a super impressive one, I want to show you this example of a YouTube video that I actually uploaded. And in this example, let me just pull this up and then I'll share it. I basically recorded a raw file. It was like 15 minutes and I threw it in this pipeline and said, "Eedit this for YouTube." And then it created

38:39this for me, which was it ended up being about a 10-minute video. But you see here, I've got these motion graphics. I'm going to just go ahead and mute this so I can play it while we're talking. But it creates these motion graphics where it kind of like created this open loop. Oops, there we go. So now we have this open loop where we see what's going on. I get into like these flowcharts. So I'm explaining these different processes and then what it does is it kind of keeps this spatial awareness

39:07if you know what I mean. when it when it goes to the second use case, this was like use case one, it puts it back here and it knows to create this open loop where now the audience is, okay, oh, I want to see what number two, three, and four are. And it consistently does this throughout all of them. So, if I go to the end of number two, you can see as it transitions from two to number three, it does the exact same thing where it puts it back there and then we jump into number three. And as I'm explaining these different automations, it's it's animating it as

39:34like a flowchart. you know, all of this stuff would have taken me so long to animate, you know, myself. But if you see all of these things that are going on now, this was all because I had built out a pipeline for me be to literally be able to drop in a raw file and it cuts it up. It puts all the stuff in here and it does the whole verification loop. So like something like this could take up to six 10 hours. So sometimes I'll run this before I go to bed, but I come back in the morning and I've got a video now

39:59that I'm ready to post on YouTube. Yeah, that's crazy. So, so in that example, it's actually like editing the video. So, even when it goes from like the animation back back to showing your camera, that's the that's clawed code. That's the AI making that decision like of shift from like the animation moving here to like then show his camera on like a split screen like those editing decisions which would be made by an

40:27editor. The AI was handling that. Yeah. Yeah. It it transcribes it. It tries to contextualize what I'm talking about and then it and a few other agents debate on what would be good animations to show during, you know, those 10 seconds or those 20 seconds and then it creates the hyperframe animation. It renders it in a browser and then what I have it do is I have it go through and screenshot like every 3 seconds and then it basically watches back the whole video and it says, "Oh, you know, this element was out of bounds or this feels a bit, you know, off-brand." And it will

40:58go through. So, that one that you just saw, um, actually this might be kind of cool to show if I share this real quick again. The output that you saw there was essentially it created this in this folder. So, what you see is it created an intro and a V1 and a V2 and it took photos and it came down and what I ended

41:18up showing you just there was the V8. So, that was the eight version of the actual animation that it made. And so like this was the full project that I was it was creating in it created assets, compositions, the script, it had an index, it had QA which means it went through and it screenshotted everything. So this was a big project. It created a ton of files from it. But the ultimate render that we got was version 8, version 8 master. And you know that was obviously a lot of iteration had to go into this whole skill and this whole pipeline. But um the cool thing is every

41:52single time I use it, it gets better because after I did this one, I was able to say, "I really liked what you did here and I really didn't like what you did here." So update the skills so that next time you do more of this and you do less of that. It's just about constant feedback on the good side and the bad side. And then you literally get in this cool place where every time you use it,

42:12it gets better. Yeah. So, I understand that you've like optimized this and even proved it and you you even just have this verification like process which we're going to show people in a second, but for you, I guess, how autonomous did it feel to make that video? Now, I'm able to do something called a a goal prompt. So, a goal prompt exists in

42:34Cloud Code and Hermes Agent and Codeex. So, pretty much every AI harness now is working in goals. But basically, when you set a goal, you tell it the job and you say, "This is what I want." And essentially, it won't stop until it hits that goal. Like, I'm setting the stakes. I'm giving it something to work towards. But you do have a good point. If you don't have earlier, we talked about the the connections. If you don't have some of those connections and permissions set up right, then it probably will get roadblocked and say, "Hey, I need you to allow this." But now, I literally say,

43:07"Hey, SLGO, edit this video. I go to bed and in the morning it's done. This is just it's it's native to the tool. So right here I just go /goal and it says set a goal. Keep working until the condition is met. And it's as simple as that. It'll tell you the goal is active. It'll tell you how long it's run. So you know sometimes I'll run a goal and it will take 10 minutes. Sometimes I've I've ran goals that have taken 6 days and it's literally just ran for six days straight building things. Um, if we want to hop into the next one and I can show you

43:34guys real quick the calendarly clone that I built, that was a big/goal prompt that ran for it was 4 and a half days I believe. So I can I can switch over to that real quick and show what that looks like. And so I've been so curious to like see where you're at in that process, Nate.

43:50Yeah, let's let's do it. Let's do it. This is what we've got now. It's called Snag Time. And what I think is really interesting is like I said, I don't come from a technical background. I've never built software products, but what I did is I gave a slashgoal prompt here and I basically said, I want to make a clone of Calendarly that my team can use. It's going to be free. So, what I need you to do is research Kalanly, figure out all of the best features, and then plan out the build, build it, test it, and and give it to me when it's done. So the point I'm trying to make

44:28there is let's say you didn't even know what Calendarly was. You could still instruct it to do that because it went ahead and found out everything Calendarly can do so that it could essentially clone it. So now I have this little app. You know, it obviously has some authentication. I can go in ahead

44:43and come in here and log in real quick. Let me just go ahead and get my um the the example login that I had here. So now I log in here and you can see that I have this interface. Like it's not designed super beautifully. It's just a proof of concept. But what I have here is an overview. I can see upcoming bookings. I can see how many I had this month, how many hours. I can create new

45:10event types. So this is a a test one. This is a paid scoping session. So someone would actually have to pay. I connected Stripe. We have a free strategy call. We can set our availability. So, this is all basically the exact same way that all of those calendar booking um you know, platforms work. I connected my Google calendar, connected um a sandbox of Stripe. So, this isn't real Stripe yet, but I guess let's just go through a quick flow. So, if I copy, let's do this um free strategy call and I come into here to this tab. This

45:44is what the user would essentially see. They would get this ability to book in a strategy call with Up AI. We can obviously add a description here if we wanted. We can choose the time. And if I go through here, you can see that it's actually syncing to my live calendar. So, if we're looking at Friday, we only

45:59have 2:30 to 4:30. And this is the calendar that's looking through Friday. We're, you know, we're basically booked until 2:30 and beyond. So, this is synced to my live calendar. If I added a event right here 3:00 and we go back into this form and I give it a refresh, this should now be showing that that slot has been taken. So this is real live syncing. I could go ahead and make an event right here for 4:30

46:24and you know put in some information. It basically is Calendarly. Exactly. Yeah, it's missing some of the automation features that Calendarly has, but for the bare minimum of being able to send people links to book in your calendar, you really, if you want to, like don't have to be paying for that subscription. So, confirming the booking here, what this is going to do is it sends um a notification to you if you're the account owner, and then it also sends an email to the person who just booked in. If I go back to the calendar, you can see that this just popped up, which wasn't there before, which is our

47:00strategy call with Nate with this is the email that I just put in. Um, so that essentially works. And this was exactly when we hopped on that pre-all. This was what I said had been cooking for about four and a half, 5 days. And then it finished and I came in and I I was able to see that it tested everything. So if it didn't test everything, there would have been certainly a ton of bugs in this environment. There would have been things that were off. there would have been bugs with the way that the the UI clicked the buttons. Um, you know, you can even come in here and you can

47:32set up your workspace. You can put a logo. There would have been bugs. That's just what happens. And there probably are still tons of bugs. But what happened is I had at least 50 agents create fake accounts, create fake bookings, um, click through the UI as an admin, change the logo. they they came in here and stress tested every button and almost every edge case they could they could think of so that I didn't have to come in here or I didn't have to have my beta users experience those bugs and then send me feedback you know so that's the way I think about all these

48:01automation software building websites just have a bunch of agents do the work that you would normally have to do anyways because they can access a computer they can click around they can take screenshots they can you know submit things way quicker than you can really really cool when You just have that mindset shift, right? Because all of us in the world are possible. Like all of us could possibly say, "Can you

48:24go spin up 50 agents to test the app?" There's no one on this earth that couldn't instruct an AI to do that. It's just how many people would think to do that. Yeah. You know, I'm I'm so curious, Nate, with like where you think this goes, especially given your background. Do you like I'm thinking about the ability of companies, but even more so individuals to basically be able to do what you've just done, which is like build like custom software. And I'm so curious like if you were talking to the Nate Herk that was like just coming out of college and was like, you know, you

49:01kind of had this like love and this hunger for like business and building things. I'm so curious what you would be doing like what are the opportunities that you're even seeing right now because this thing of like building custom software feels pretty crazy to me. What I would the advice that I would still give to myself coming out of college if I wanted to you know turn this sort of AI knowledge into a business I think the advice that I would give myself would would be to pursue a service-based business in AI helping small businesses upscale. So essentially the agency that we were running, the consulting firm that we were running, I

49:37still think that going service-based, there's a lot of value in that because I mean there's a huge gap that needs to be filled and people are looking for experts to help them fill that gap and you know start to automate roles and and businesses or processes in their business, things like that. But I think what a lot of people are doing is we all don't really know exactly where it's going. I think that humans are ultimately really bad at making predictions, especially in a space that moves so fast. And so what I'm trying to do and me and my community are like what we can do is we can stay close to it and

50:09we can all learn together so that when we need to pivot, we can pivot fast. And when you work with companies, you get to hear what are their concerns and what are their roadblocks. And with different industries, what are they interested in, what are their pain points? And that can help you figure out a lane to go down because right now there's this huge I guess kind of buzzword AI consultant and it's working really well. AI consultants are getting good business and they're in high demand. But ultimately what's going to happen is these roles that have an AI prefix, the prefix is going to get dropped and

50:42it's just going to be consultants. And if consultants don't use AI, then they're not going to be a very good consultant. You know, it's the same thing like I think about when the internet came around, we had like a bunch of internet marketers or digital marketers, but that's just marketing now. You know, if you don't have an internet presence in some form, then you really don't have marketing. So, it's just going to become the new normal. And that's why I think if you were, for example, educating businesses, going in there, you know, I know some people that not anymore, but they were printing like $10,000 a month plus just teaching

51:12businesses how to use Chachib, you know, in the early days of of Chachib. And now they're just teaching businesses how to use cloud co-work or something like that. And they're just helping people upskill because it is kind of an intimidating topic and um change management is very tough. But what I've learned through educating people in businesses is I've recognized a bunch of patterns and I've been able to get a better sense of what I think like where where the true value sits. And if I ever wanted to go off and build like, you know, some software products and stuff like that, you need to be able to

51:46recognize, you know, pain. You need to be able to recognize how does your service or product solve that pain and for what very specific type of person is feeling that pain and would want you to solve it for them. Yeah. If someone's watching this and they want to like succeed and just win in kind of like this new world that we're going into where AI is at the heart of a lot of things. What for you is actually the correct and very doable like first step? Like they're at a point now where they're non-technical. They've never even really used Claude code but they're kind of like okay cool. I like

52:26the idea of like in the future potentially being able to run this service-based business. What for you is the right doable first step? You know, I felt like when I got started actually working with businesses, one of my big jobs that I didn't expect was to manage overwhelm. So, I think that if you're in a position where you're going through learning how to use this stuff and learning how to use it effectively, take advantage of being in that headsp space of not knowing what you don't know and understanding these are the questions I have. These are the concerns I have. let me write all these down and

53:10I'm going to learn these and answer them because now I can sort of like hopefully proactively address concerns and issues and areas of overwhelm that most businesses and most people who are starting to learn, starting to enter this world will probably have. And I think that um you from there what I would do is I would

53:29start to try to teach people you trust. You know, try to see if your parents want to learn, try to see if your your best friends want to learn and just try to teach them because if you can teach them confidently, then you'll have a lot more confidence going into teaching someone you don't know. But I think it's just important that you are getting out of the world of practice, practice, practice. And at a certain point, you are putting yourself out there and doing it in a way where it protects your brand reputation, right? Like doing free work until you feel like you can really deliver value, I think, is something

54:01that is really important. You know, prioritize experience over the cash because I think right now everyone is kind of starting at the same starting line. A lot of the times the best person to learn from is only like one step ahead, right? So like we put all of this value on like the expert or the person that's been doing the thing for like 10 like decades or years and years, but the person that's like the most relatable and the easiest to learn from is probably actually only like one or two steps ahead of where you are. I want us to kick off this process for people of,

54:37you know, they see some of these use cases and some of the opportunities that we've even spoken about that you're seeing right now. They get excited. a open claude code. Like I I I want to just close the gap for them and I even want to like read out something you said where you spoke about it earlier. You use this thing called the bike method with Claude code and you actually say like I call it the bike method. That's your framework and then you say that's how you build with clawed code. Can we just start right at the beginning of like someone pulls up the desktop app

55:14with clawed code for the first time? What is it that they need to understand or even what are the first few things that they should even be doing that's going to make that experience that first experience a good one? So Claude code works in your local environment, meaning it can it works out of a local folder and it can touch things locally. And locally just means, you know, in your file explorer or in your finder depending on, you know, what OS you're on. So it can move around things in your downloads folder. It can rename them. It can organize them. And so what happens when you create a new Cloud Code chat,

55:54you have to choose the project you're working in. So you guys have seen throughout this one, I've been in this one called Herk 2, which is what I consider my AIOS. I'm just going to say hi real quick because this basically what happens when you shoot off a prompt inside of this project. Right away, what it will do is it will read through

56:12something called a claw.md if it exists. The first thing you should do is have Claude help you create a claw.md. This is essentially a system prompt. So, if I, for example, let me just actually show this. If I go to my Herk 2 and I open up my cloud MD, I know there's a lot of stuff in here. It's a little overwhelming, but [snorts] this is my cloud MD. It says, "You are Nate Herk's AI operating system. Your job is to help him spend less time on operations, people management, and admin so he can focus on learning AI tools, and making YouTube videos. That is the number one

56:42priority. Everything else supports it." And what you'll notice here is my cloudmd. It sets up the context, but then it just routes. It says, "Hey, if you want business strategy or OTAAS, you look in his wiki. If you need corporate structure, you look here. If you need his voice and style, you look here." So immediately when I say hi to Herk 2, it basically says, "Hey, what do you want help with?" I know exactly where to look, exactly where to touch, exactly what to do. So, you kind of want to set something up like this. And this is a file you don't have to know all that

57:11right away. It's going to change every like every day. it's going to change because you're going to find out new things or make new files. So the first thing you should do in here is you want to create the claw.mmd file and you can just do that by asking. So if I say, "Hey Claude, this is a new project called Hercules Advisory. This is for kind of just a demonstration. Just pretend that you are or not pretend

57:34Hercules Advisory is a consulting firm. So what I want to do is I want you to help me sort of like just build some automations and stuff in here. All you need to know right now is that what's in this project are some logos and brand guidelines and that my name is Nate and

57:48I run Hercules Advisory. So it's going to create a very very simple cloudmd file for us and that's kind of going to be the foundation where everything important will go in there. So for example, what we could work in there is every time you're creating a deliverable, make sure you verify it two times before you give it back to Nate. And so if you work that into your cloudmd like under like a rules section or something, it will always do something like that. So that's kind of

58:15the first thing to do. It sounds like you set up this claw MD file, you set up this context and it actually makes you take a bit of time to do this in the beginning and it makes everything like way faster and smoother nearer the end. like it it saves you a lot of time in the long run because it's operating off of this instruction manual

58:36essentially. Yes. And I just realized I didn't even ask it to make it so I just had to tell it real quick. But what it did is it also it added that to the memory. You can see it created um a markdown file for advisory for our brand and it also created a memory file for it to look at. But now it's going to create the claw

58:52that I'm deep. One thing, Nate, because you said this before and I think this mindset, it's been so helpful to me, but I also just think it'll be really helpful for people that are listening. And you actually said this when we spoke earlier. You said the way that you think about AI and using Claude code is as if it's like a AI employee. And so you said all it really takes is you're managing an AI the same way you would manage a human, which is you give them the job. You tell

59:19them very clearly what you're expecting. What does good look like? And it reminds me of like when I first started working and you're like sitting next to your manager for like the first few weeks like in the office and they probably would have given you like a a job description. They'd share with you like certain onboarding documents so you kind of knew what you were doing and like the expectations of the company and just like context on the projects that you're working on. And it feels like a very

59:48similar process and mindset. Like once I started to see it in that way, it kind of clicked to me how I needed to also interact with the AI is almost coaching it as if you know I'm the manager and it's the new employee and I'm like onboarding it. Exactly. I think that is the best way to

1:00:07think about it. You're onboarding it. You're teaching it about you. Um, the most important thing when you're working with these systems is how do you get what's in your brain into the AI's brain? You know, because once it knows what you know, it saves that and it won't forget it. But I think that you're exactly right. And you can see

1:00:29here what it did. It created this claw. MD file. It says Hercules Advisory is a consulting firm run by Nate. It provides strategy operations blah blah blah. Um, and then it it basically marks what the files are. So these are the only four files we put in there and it knows what they are now. Guidelines, logos, we have this is brand rules. We have our colors, we have typography, it has my voice, it has other things. And I could just go in here right now and edit this. So like if I came in here and this when I say MD that just means markdown. Markdown is

1:00:59this format where you can have bullet points and you can have headings and then it kind of like renders like this. You can have tables. So it just means markdown. basically natural language though. And I could come in here myself and just add in a section right here called rules and I could say whenever you are creating an output make sure you are doing a verification pass before you give it to Nate. So if you're building anything visually take screenshots and show Nate the screenshots to prove that you have already verified. So that's

1:01:29just one method of verification. Screenshots is one type. Factchecking is one type. Um clicking around is one type. There's lots of types, but I just wanted to put that quick example in there so you guys could see that. And you can see how when we kind of like prompt it to do these next things, hopefully it should be able to read that and acknowledge that. So, this is kind of what I would now start to describe as like the bike method. What I want to do here is I want to ask it for a report. I want to ask it for just like a a market

1:01:58census report on consulting for SMBs. And I want to make sure that it's like branded, but I'm not going to tell it that stuff. And I just want to see how it comes through. And we're probably, once again, this is the assumption, we're putting the kid on the bike. We're going to have to guide it a little bit. And every time we give it a little bit more feedback, it gets better and better at riding this particular bike. And what

1:02:17we're building here is called a skill. Essentially, a skill is a repeatable recipe. So, I have like a LinkedIn writing skill. And now, every time I ask for a LinkedIn post, it knows to follow like this format and this hook structure. Essentially, you know, the same way if you're making chocolate chip pancakes, you don't just want to guess every time. If you made them really really good one time, you'd probably save that recipe so you can make them really really good every time. So that's what I'm going to do real quick with a a

1:02:41very simple prompt. I need you to create a skill called market analysis and I just want you to do a quick research report for me. Create an HTML document of um kind of like the consulting market for SMBs right now. So, what you'll notice here is I didn't ask this thing to um use my brand guidelines or verify itself. So, we'll

1:03:08have to see if it actually does that. And it might be able to read the cloudmd because we just created it in this chat. Um sometimes if you're working in the same thread, it doesn't fully refresh. So, it might not. But the point I'm trying to make here is it's really important to watch what they do because this is where people tend to just like

1:03:25shoot off a prompt and switch windows. But when you're watching the kid ride the bike, you know how to steer it. We can see right here, I'll do this in two parts. I'm going to build the skill first and then I'll run it. So, what it's doing, if we click in, we can see that it's creating a skill. So, it's creating the skill and now it's creating different agents. And you can basically just watch what it's doing in natural

1:03:45language. It's running commands. And this is where we're able to course correct it if we notice that it's doing something that's just like really wrong. Yeah, I actually really like that visual of like the bike method. And it's funny, it's I haven't thought about this in years, but I think about my dad actually teaching me how to ride a bike. And it wasn't, you know, like they kind of get you on the bike, but without the stabilizers. I don't know if you guys call it the same thing here. We call the training wheels. That's what we call

1:04:10it. Yeah, the training wheels. [laughter] And it's like you're not on the training wheels anymore. And he pushes you off and he's like just pedal, pedal, pedal. And I feel like what you described, what most people do is the equivalent of like if you pushed the kid and then immediately just go went and did something and like just let them go down the hill. But like exactly what most parents do is that they'll actually stay like right there with their child in case they look like they're about to like fall so that they can actually catch it. And that's actually it it the bike method actually

1:04:43very nicely crystallizes kind of like the approach and the method that you're displaying. Totally. Yeah. Well, I'm glad it resonates. I'm glad it resonates cuz yeah, I mean that that is way too common. You would never you would never put your kid on the bike and then go in the kitchen and take a nap or I don't know, might not nap in the kitchen, but you get the point. So, I'm glad that resonates. [laughter] So, you can see it literally did all these searches, right? It searched for SMB consulting market. It searched for um management consulting industry trends, pain points, fractional executive CFO studies and stats. It said

1:05:17research is done. Now I'm going to build the report embedding the logo. So the HTML is self-contained. So it looks like it's going to understand that it should kind of build this with our brand guidelines in mind. And now it's creating the actual HTML. So this might take a few minutes. You can see it's

1:05:32taken 2 minutes and 30 seconds so far. But there's a lot of value in just reading what it's doing because I think you've heard this term blackbox. You know, we don't exactly know what the AI is doing. You know, claude code is a is a harness wrapped around the AI model. So, Fable 5 is the model which powers it, but the harness the analogy is basically like Fable 5 is the engine of the car, but the actual car is the harness, you know, and you can switch out the the engine within the car. So, I think that there's so much value. The the way that I learned Claude Code, I

1:06:06didn't watch YouTube videos. I I just got in here, I asked questions, and I just watched. And I remember doing that for a couple days straight until I felt like I really understood how it thought. I'm so curious cuz I actually think that's really good advice. Take us behind the scenes of that process for a second of you hit the pro like you click enter and then you just watch. What exactly was it that you were even

1:06:28looking out for? like what would make you jump in? But kind of just almost describe like what did you find was the most valuable way of actually like learning from just watching Claude code work. Yeah. Well, when I first got in and they've cleaned up some of this language, but it used to just say like bash, glob, gp, like it would say all these random words that sound like a different language, but those are just like they're they're, you know, terminal commands. They're searching for things or they're executing commands. And you can see that this research report just popped up and it looks pretty branded which is solid. Um, and so we'll dig

1:07:02into this in a sec. But essentially what I was doing is I was trying to understand what it was doing and why. You can see it's taking screenshots right now. It's proving to me that this is is good. You see these are screenshots it put back in the chat. But what happened was um I would watch every line and I would basically like highlight something and paste it back in and say what did you do here? Why did

1:07:23you do this bash or what is this glob? Why did you do a glob? And I just wanted to understand, you know, and this was, I think, just me being genuinely curious about how it works and trying to figure out why it does does things. But I felt like I was able to once I understood a little bit better what it did. I felt like I was able to reverse engineer that into understanding

1:07:44how to instruct it better. So now this is done. It has two deliverables for us. The first one is a skill called market analysis. And this skill can be invoked with a slash command. Meaning I could come down here and say market analysis. Or Claude will automatically run the skill if it thinks that it's applicable to my prompt. So if I said, "Hey, can you just like do some research on um this this news announcement I just saw? Like how is that going to affect my business?" It would probably run the skill because it knows what type of deliverable I'm looking for. And then it also created

1:08:20this actual HTML report. Um, and you can see I showed you guys like how it took all these screenshots. It was basically verifying that it looked branded and that it was all good. But what you'll notice is it didn't do any other type of verification. So, for example, it shows me these sources. It pulled 16 sources. If I clicked on these links, it would take us to the actual source. But one other thing that I would probably want to do here is I would want to make sure that all of these claims don't conflict with each other and that they are verified sources. But for a first pass,

1:08:48it's branded. We have the date. We have, you know, like executive summary, market size, and growth. And it created this as an HTML that you could once again like send to the team. But this is the part where, you know, if you actually read through this, you'd probably have some feedback. You probably wouldn't like how certain things were structured or like I said, maybe you'd want to make sure that

1:09:06all of the claims are actually checked. So then all I would do is I'd be like, "Hey, this looks good for first pass. Um, I think that I would like a little bit more information about the market size and growth. That is really important to me. And every time I ask for a report like this, I want you to really focus on that element. And when you you did a good job with the screenshot verification, but I want you to also always have a source verification. So, just doing a double check with a different agent that every single fact that you pulled is verified and it's correct and it's not like

1:09:39outdated. because if you're pulling, you know, sources that were two years ago, that's going to be not relevant for right now. So, go ahead and make those changes and then update the skill. And that's really all it is, you know, it's it's telling the kid, hey, you know, you you weren't pedaling fast enough and you were leaning too much to the right, so let's try again and next time just remember that. And that's kind of the whole loop. There there's something very subtle that you did, but I actually think it's really important, which is that instruction of like you gave it the feedback and then you said moving

1:10:08forward or every time that you do this from this point, do X or update the skill. And I think it's one of the things that I've learned recently, which is if you don't do that step, it's like the next time you're generating a report, it's the same thing. And that's when you actually start to lose time. Mhm. you know like the time is money kind of thing like you start to it starts to just cost you time is in actually repeating it. So actually going back and being like update the initial skill and that's when you actually start getting to this place where it like gives you these outputs

1:10:44that consistently like hit the mark and you're like okay this is perfect like you you'll start iteratively getting to that point where it's like this is perfect. Totally. And I think that one thing that kind of just turns people away is that I think humans will default to what's comfortable. And let's say you were given this task to write this report and create like a

1:11:10little HTML. You already know how to do it. And so the idea of doing this, even though you know, okay, this is probably going to take me 30 minutes, but you know exactly how to do it. So you're just going to do it. But then you also think about if I built this automation, there's a short-term cost that you have to bear. Whenever you're building things, typically you lose a little bit of productivity during the build, but the idea is that the

1:11:34long-term gains from it are exponential. You know, it's worth that short-term dip to experience that the value that it actually creates in the long run. But I think that that dip is what causes a lot of people to procrastinate building the automation or procrastinate learning because they don't want to feel that, you know, the two hours it took that day to learn and to build when they could have just spent 30 minutes just doing it

1:11:58the way that they always do it. Yeah. It's like one of the first lessons that I learned in in business and just building stuff is like it's like sometimes you have to go one step backwards to actually go steps forward and you're not actually the the ironic thing is you're not actually going backwards but it feels like you're going backwards because you're not getting the thing right away but like it actually takes more time in the upfront setting this system up learning how to use clawed code but down the line like I think about what you meion mentioned right in the beginning of this conversation 7 months ago you

1:12:32weren't even using claude code and it's like look at what you're doing now with it like some of the workflows that you've demonstrated but you to your point you had to go one step backwards like you had to take the time to learn it and teach it and build the OS and all this stuff so that you could be where you are now 100% yeah and I just wanted to call out what's happening right now you can see that I told it to expand the market size section And if we go up, you can see it's significantly larger now. It's got more data in there. It went ahead and it took

1:13:08screenshots. You can see that it made sure that that new section rendered cleanly. But what's happening right now is it says one running task. And this is right here. It says now the source verification. I'm spawning a separate agent to fact check every figure while I update the skill. And what's cool about that is if I click into this running task,

1:13:26we can see right here what's going on. We can see this agent is verifying report facts and sources. And we can click into this and this is essentially agent one on the left that we're talking to. Agent one sent off this prompt to agent 2. This is called a sub agent. So it said, "Hey,

1:13:45you are a fact checker for this report. Your job is to verify each claim. You know, confirmed, outdated, unsupported, and here are all the claims you need to verify." So, this is a a main agent that just created out of thin air a sub agent and now the sub agent is working for this main agent. Yeah. Okay. You know what? Cuz I think this is so valuable. And even when we were talking before this, Nate, I was like, I've actually never heard someone describe this process in the way that you have. So, congrats on that first of

1:14:14all. Thank you. Um, but you know, you you talk about the checks and there's three things that I've heard in terms of how you're actually getting the AI to check its own work. So the first one was like the screenshotting method and you you showed us how you directly inputed that into uh the Claude MD file, right? So that was the first one. The second one was it spinning up like sub aents to check certain components. The third one that I actually don't think that you've mentioned, but I know that you said it to me was uh like browser use like you give it you give it access to use

1:14:54browser use so that it can actually check its work. Can you just quickly for those three things kind of just share what's the use case for each one? like is there a specific use case where you use the screenshot method versus the sub agents versus the browser use can you just explain that and then also very high level I guess for the browser use what that even is and yeah what that

1:15:24even meant. So the screenshot is whenever I need something visual. So editing videos, I have it screenshot the frames. Making sure that these HTML reports or PDF reports are formatted correctly. You know, don't have any elements that are off the screen or out of bounds. When I'm building websites, I make sure that the text is visible, right? Like there's if there's white text against a light

1:15:48background, it probably won't look good. But when the AI is coding that in hex code, it probably doesn't even think about that. But when it screenshots it, it realizes, oh, the text isn't visible. Let me just add like a little overlay behind. So that's whenever I need something visual. I have it fact check and verify anything that's going to be going out. You can even see here it said that 18 of the 21 original claims were confirmed. One of them was outdated. Two had problems. So if we wouldn't have worked in that verification, it would have been putting out some false information, which is why it's so important that we're doing the

1:16:18whole bike method. And then on the browser use or computer use that just literally means that cloud code will open up a Chrome or whatever you know you want to use and it will click and that's a combination of vision and AI reasoning because it has to look at the screen and figure out where to click and it can also type. So in the calendarly thing the final phase was that it had a bunch of agents open up the actual app that we built and it tested the UI you know it tried to book an event it tried to change the logo. tried to do those

1:16:49things because it literally had 50 different browsers open doing it and then they would all come back and say, "Hey, there was a bug when this happened. This, you know, this was laggy." And then my my agent would fix it all and then send off those 50 agents again. So, we just got that constant verification loop. Um, and now you can see here the output is the section was expanded, the source verification fixed

1:17:11things, and then the skill is updated. So if I actually open up the skill real quick, you can see that this is our market analysis report. It has the steps which are to scope, do research, write the report, brand the HTML, write in a calm voice. You verify the source. This is mandatory. And then you do a visual verification. So now I could give you this skill which is just a markdown file. You could give this skill to your claude and you could say create me a market analysis report. And it would already have all of that verification and all of this information baked in because it would just read the skill and

1:17:43just execute. And then of course every time you run the skill you can you can give feedback and say update the skill and it just will constantly do that. Yeah, Nate, I think it's it's so good. And one of the things and it really clicked when I heard you say this, you mentioned it in a video. It really clicked just the value of that verification process that you have is you mentioned that uh take away all the verification on a first pass. Claude code would probably give you like 60% of what you want. I think what what you said you said on a first pass you're

1:18:17maybe getting uh somewhere around 60% of the way there and then after you give it feedback and these like you add on also these verification checks that's what actually is going to get you to the 100%. And so when people use claw code or like one of these programs like codeex even for the first time and they get the poor or the mediocre output or

1:18:40the AI slop as people call it, right? It's because you're looking at the 60%. Like it didn't you haven't elevated it to that point. So yeah, it's just such a this is like uh it's mind-blowing in a lot of ways like what it's even capable of right now. 100%. Yeah. And I think it's it's also all about aligning expectations. You know, if you can be more specific about what does good look like, then it can actually work harder to get you to that good. But, you know, something like, "Hey, create me a market analysis is is very vague. It's very open-ended. So, it's going to it's going to get

1:19:16creative. It's going to give you what it thinks you want. But, if you tell it ex exactly what you want and what you consider good and what's important to you, what your motivation is, then it will give you something on the first pass." That's a lot better. Yeah. You know what, Nate? Something that I said earlier in this conversation, and I truly mean it, and if anything, as we've spoken more and more, I've just believed it more and more the case, believe that it's more and more the case, which is there's going to be someone that listens to this conversation, and it's not just that they implement some of the stuff

1:19:49that you've shown, they they play around with Claude code, it's going to make them way more productive in their life. And then there's going to be some people that take that even further and some of the opportunities and some of the things that they learn how to do with Claude code actually allows them to start a business which creates like an additional income for them. Like I think that's going to be the case. Just to warn you in the next 3 months, 6 months, 12 months of people that watch this

1:20:14conversation that we've just had. But Nate, one of the things that I'm so cognizant of is until you start taking like action and you start that first step and you start building momentum, it's like that's never going to happen. Like that potential reality will never be here. And so my question to you, someone's watched this conversation up until this point and they've been inspired and they've thought of all these use cases and things that they want to do. And let's just say that going into the weekend, maybe they have like a free Saturday afternoon or maybe it's like the Sunday evening right before they get to work, they just have

1:20:53some time, like a few hours to spend with this. What are you telling them that they should immediately go and do in that time, that right first step, so that 3 months, 6 months, 12 months from now, they're in that point, that that new reality that I described earlier. What are you telling them to go and do on their free Saturday afternoon or Sunday

1:21:19evening? I think the first thing you need to do is when you open up this tool, do what's called a grill me session. So, there's actually a skill which I can I can give to you Callum if you want to like link it for your audience, but it's it's it's a it's called a grill me skill. And so essentially what that does is it relentlessly interviews you until it understands everything about the

1:21:47topic you want it to understand. So what I would do is I would open up a fresh claw. There's probably nothing in there. And I would put in the grill me skill and say I want you to essentially be like my personal life coach. I want you to know everything about me, my background, what my motivations are, what's important to me, and where I want to go, so that you can just help me get there, and you can help me be more productive. And this thing will it will be relentless. It might ask you 50 questions and just take that time, take a couple hours, and just

1:22:20brain dump everything about you and about your motivations and your goals. And I think once that interview is done, your system is going to feel it. It it might even feel like you're talking to someone that you've known for your whole life already because it has all that context and it's going to save all that context and then every time in the future you open up a chat. You want to build something. You want to see if an idea is good. It's going to have all that context and it's going to help you just move a lot faster because I think that's the most frustrating thing is

1:22:51when you have to repeat yourself or when you have to drag things over and you feel like your systems aren't sinking together, you know? But now I have my my AI operating system that I use every day and I can use it in Cloud Code, Codeex, Hermes Agent, OpenClaw, Crockbot, any other new AI tool that I ever have, ever or ever use. I just plug it into this directory and it knows everything about

1:23:14me. And that is my that's all of my IP. That's like the most valuable thing I have right now is all those files and folders. Yeah. So, so first of all, on on the grill me skill point, it'd be great to link that and we will link that in the description. But secondly, and even more

1:23:30importantly, Nate, just thank you, man. Like, I just think that uh it's funny. I go into every conversation that we have on the show with like I just want to overd deliver especially for like that non-technical person that person that kind of like you and I starting out of like we're not the coder we don't work on Silicon Valley we're not a software engineer but like we're just hearing about AI all the time and it's like okay what could that mean for me and so I just always want to overd deliver for that human being and we did that in this conversation and you were just like such a huge part

1:24:07of it obviously. So, thank you Nate. I appreciate it. Awesome. Yeah. Well, I really appreciate that. That means a lot to me. I wanted to come in here and make sure that we could provide everyone with a bunch of value. So, I I really hope we did and yeah, I had a lot of fun on this on this session. So, thank you so much for

1:24:21having me. So, if you enjoyed this conversation and you want to hear even more stories like this, then just click here. And also, my team is going to put some more videos that you can watch here. Thank you.