Build & Sell with Codex (5+ Hour Course) transcript

I'm about to take you from a complete beginner to a pro AI builder with Codeex. And you don't have to have a technical background at all. My name is Nate. I have no technical background. And I started using AI about two years ago. And in that time, I had an AI consultancy that we scaled to over $100,000 a month. And then I exited that business. And now across my different business units, we generate an average of over $400,000 per month because we all use AI so well.

And none of us are actually like coders or anything like that. So in this course, I'm going to show you guys how to install Codex. I'm going to talk about the core concepts. I'm going to talk about how you turn it into your AI operating system and your second brain. We're going to go over things like skills. We're going to build some together. We're going to go over how you create deliverables that are branded and feel like it's coming from you and feel like it's coming from your company.

We'll go over images. We'll go over design websites using the browser using Codex to edit videos, using codeex to build automations. We'll even address the whole codeex versus cloud code debate. And by the end, not only will you be a pro AI builder, but you'll also know exactly how you could go off and sell this kind of stuff to clients. So, there are going to be timestamps down below. Feel free to skip around to what interests you.

Save this video so you can come back to it for later. And now, let's not waste any time and just get straight into this one. All right, so we're going to go ahead and get started with installation. You're going to open up Google and you're going to type in cloud code. Wait a minute. That was so 3 months ago. No, I'm just kidding. But it is funny how Chad GBT also pops up right here. So, you're going to type in Chadbt or Codeex.

I'll show you what that looks like. I will just type in codeex install. And then you see right here, ChadBt Codeex because Codex is a product of OpenAI and Chad GBT. So, this is what it looks like. What you're going to want to do is just download this for your operating system. So right here I would click on download for Windows and then I would go through the installer to get the codeex desktop app. Now this actually will be called the chatbt desktop app but we're going to be using codec.

Now if you do use VS code already or you use cursor or something like that and you'd rather run codec through the IDE extension or through the CLI then you certainly can do that. But I love the desktop app. I think that they're bringing it in really really nicely with their browser use and their sites and routines and everything like that. And the rest of this course we're going to be using the Codeex desktop app. So, if you want it to all look the same, then just go ahead and download the app real quick.

Now, once you're inside here, it's going to look like this. You're going to have two different tabs up top right away. You'll see chat and work, but then on the lefth hand side, you will switch over here from chatbt, which is chat and work to codeex. And if you do have a chatbt subscription already, like you're paying 20 bucks a month or 100 or 200, that's the same exact subscription. So, you won't have to make a new account, but if you are currently on a completely free account for OpenAI or for Chatbt, then I would at least get on the $20 a month plan right now.

And if you start to blow through your usage, then just go ahead and upgrade. Because the way that this works is you can see in the bottom left, you can see that I have 94% left and I'm currently on the $200 a month plan for Codex. And so if I use this up within the week, then I would just basically have to wait till it resets. Or I could pay per usage API billing, which is just a little bit more expensive than being on the subscription.

The subscription of Codeex actually gets you about $14,000 of inference if you use the entire subscription. So, it's it's really really cheap for being on the subscription, paying $200 a month, and I'm getting about $14,000 of usage out of it. And I know that 200 bucks a month or 100 bucks a month may seem expensive relative to subscriptions, but we're not paying for Netflix here. We're not paying for entertainment. We're paying for productivity.

We're essentially treating this as the cheapest hire you will ever make. $200 a month for the output that multiple hires would give you if you start to use it right, which is why you're investing time in this course right here. Anyways, before we get into this, I wanted to address one question, which is okay, why would I use codeex over something like work? Because work is kind of marketed as like for knowledge work for nontechnical people, blah blah blah.

I think it's good that they're doing that, but ultimately it's one of those things where codecs can do everything that work can do and it can do more. So, why would you not just invest the time learning codecs because it's basically the same, but then one day you might need some of the extended functionality that Codeex has and you can just do it right there because you've already learned Codex. I'm not technical at all.

I don't know how to write code, but I've been able to do some very, very incredible things with codecs and with cloud code and tools like that, all with my natural language. And this entire course, you're going to see it's literally just natural language. There's just a few things that you need to understand in order to get the most out of it. So, if you're just starting or if you've been using work for a while, just trust me, go ahead and switch over to Codeex.

You're going to thank yourself one day. And trust me, it's not anything more difficult or intimidating at all compared to work. You're just getting more power. Awesome. So, now that that's out of the way, there's a lot of things that we're going to be looking at in this app. And I don't want to just run you through in a really boring way and click on every single thing and explain what it means. I'm going to basically be doing that throughout this entire course as we get familiar with everything.

So the first thing that I actually want to do is kind of start with like a 30,000 foot view of everything that's possible in Codeex and how simple it all is when we really bring it together. So we're going to start with me explaining to you all of the core concepts that you actually need to know in order to use Codex and in order to understand what it can do. And I'm going to explain the stuff extremely simply with some examples.

So let's hop into this next segment. Today I'm going over the 18 core Codeex concepts that you actually need to know in order to start using it right away and getting value from it. It doesn't matter if you're not technical at all or you've never used Codex before. By the end of this video you'll understand exactly how this thing actually works so that you can start using it right away. So let's not waste any time and just get straight into this one.

All right, so I've split these 18 core concepts into four different parts and they get cooler as we continue to go on. So part one we're going to start off here is foundations. So we're going to kick off with concept number one which is projects. Now, a lot of you guys, I'm assuming, have used chat GBT or cloud in the web before where you can talk to an LLM and it can, you know, give you an answer. But the problem you face is that every time you're talking to it or you start a new chat, you have to kind of familiarize it with you and your business and what you're working on that week or that quarter.

So, with projects, you can basically keep everything organized into one project so that as you keep working inside of it, it only gets smarter about knowing who you are. So, right here on the lefth hand side, you can see that I've got a few projects going on. I've got Herk 2, I've got Hyperframes, I've got Trading Challenge, I've got AIS demo, and I typically am always just working inside of my Herk 2 project. My Herk 2 project is basically what I call my AI operating system.

And what a project is is actually very simple. It is just a collection of folders and files. So right here, this is inside of my file explorer on my computer and it's called Herk 2. And this is exactly the project that I have open in Codeex. When I say right here, I'm inside of Codex, right? This is the file path that I'm working in, which is if I open this up, my Herk 2 project. So what that means is this project has rules about me.

It has, you know, credentials. It has all my projects. It has all my YouTube videos. This thing has so much knowledge about me. So now when I come into the chat and I say, "Hey, can you just give me a rundown of what we've been working on this past month?" This thing basically gets familiarized with my project. And then it looks at everything that we've been working on together. It even looks through all of my previous chats that I've had with Codeex.

So here you can see that it looked back from the past month and it said, "Here's what we've worked on. We've been improving your Herk 2 and your AISOs. We've been working on YouTube content and strategy, AI model testing and demos, apps and product experiments, websites, branding, business operations. So, this is no longer just an AI chatbot. This is now a co-founder. This is a personal assistant. Which brings us on really nicely into concept number two, which is something called an agents.md.

And don't let that MD intimidate you here. If I go over to the right hand side and I open up my files, you'll notice if I scroll down, I have something right here called an agents.mmd. And when I open this up, it's literally just a markdown file. That's what the MD means. And it's just rules. Like this is a very simple thing that you all can read and it's not technical at all. So this is basically like the rules for your project.

So you remember inside of my Herk 2 project, I have this agent on MD. Well, if I was inside of my hyperframes editor project, there would be a different agents.md. So this thing basically just sets the ground rules for the project that you're working in. So right here you can see that this one says, "Hey, you are Nate Herk's AI operating system. Your job is to help him spend less time on operations so he can focus on making YouTube videos." And then I give it things like core operating rules for how to work with me.

I give it some stuff about how to be safe on my desktop. And then the real bulk of my agent MD is what I call routing. So this is a routing map. It basically means Okay, so yeah, Nate's project is huge. There are hundreds, probably thousands of files and folders inside of this project. So let me just explain to you how this actually works. If you need business stuff, you go to the wiki. If you need corporate structure, you go to the corporate structure section inside the wiki.

If you need his voice, you go here. If you need course knowledge, you go here. If you want active projects, you go here. So everything that I'm doing, we're routing it back somewhere so that my agents.mmd file tells this project where everything is so that every time I open up a new chat, like I said, I don't have to reexlain things. And basically the way that this works, if we picture this being a chat thread, you know, you come over here and you say, "Hey, you say, "Hey, Codex, I need you to help me do this." And before Codex actually even like reads this message, what it does is it first reads the agents.mmd.

So I'm just going to put a here and that stands for agents.mmd. But codeex will basically read this and then it will read your message and then it will respond with something like, you know, hey, how can I help you today? So the kind of stuff that you want to put inside your agents.mmd is the type of stuff that you want codeex to know about you every single time you're talking to it in that project. And now moving on to concept number three, we have something called the agent loop.

So you'll hear about something like codecs or claude code or Hermes agent. These are all called agent harnesses. And these harnesses have their own agent loops. And real quick, if you're wondering about codecs versus like work chatbt work, I always use codecs. The majority of my work is not building products or building software, but I only use codecs because it's just the most powerful. And once you get through this video, you'll realize how easy it is to use.

But anyways, the reason why this is called a harness is because they have this thing called the agentic loop, which at the highest level basically just means when you ask the agent a question, it has a bunch of tools at its disposal and it basically thinks and it reasons and it uses tools and then it responds to you and then it thinks and then it reasons and it takes action. It uses tools, responds to you and that's basically the agent loop.

And what's really awesome about that is you can see it in action. So right here you can see that this said worked for 25 seconds. And if I open this up, we can basically see what it did, right? Right? So like it hid this response and it gave us our output, but it had a reasoning loop inside. It first said, "Okay, I'll check our recent tasks and project nodes, then I'll pull together the main themes from the past month." And when it did that, it ran all these commands.

It ran this, which you don't have to know what this means, but basically what this did is it looked inside something right here called a memory.md. So very similar to the agents.md, but this is about memories rather than just like rules. It then looked at other chats. And so we can basically watch it do things. So, to show you guys a real example of this, hey, could you just check my most recent YouTube video that I uploaded and give me three comments that you thought were funny from that video.

Now, as I shoot this off, what I want you guys to pay attention to is what we're watching. So, first it said thinking. Now, it says, "I'll find your latest upload, read through the comments, and pick three that made me laugh." And now we can see what it's doing. So, it's looking through the memory. It's looking at these things. It's running these commands. And these commands are basically right here. It's reading, you know, files to get established and to get oriented with what it needs to do.

And so, you can actually learn a lot about how codeex works and how to best work with it by when you ask it a question, you just kind of watch what it does. So, you can see what it had to do was it had to run a command in order to actually go talk to YouTube, look at the data, and pull it back. And now we can see three comments. We have this one, never seen anyone so excited to lose money. Trading with AI is very easy.

I just prompt Claude only take profitable trades. And if I want to lose money, I can do it myself faster and better. And what you'll notice is how quick that all happened. Now, I do have my Astra on fast mode, but I will talk about that later because that is a core concept that's coming up. By the way, guys, I've got this completely free SOP for you about getting your first Am. It's going to go over the exact steps that has been proven for hundreds of our AIS Plus members to get their first paid gigs.

It goes over the one sentence service pitch that can get you started today. Why your first client should cost you money. The five-minute video that answers, can this person actually deliver before you've actually received any money, what to do when you have zero case studies. There's so many good things in here that are going to help you out. Even if you already do have clients, I would recommend grabbing this because like I said, it's yours completely free.

So, if you want to grab this, there's a link for it down in the description. Let's get back to the video. All right, and moving on to the last concept of part one. It's a slash goal. And this is honestly one of my favorite things about AI ever. It's the ability to do something called a slashgoal. And right here you can see that that says set a goal to keep pursuing. Now AI agents are super goal oriented which is super cool.

So let's say you have Mr. AI agent right here. And you basically say hey here is your goal. You know this is what you need to do and you give it this objective goal. What happens is it will basically just keep working and keep working and keep working until it actually hits that goal. And it's cool because even if you kind of like give them a roadblock, they are going to be so goal-oriented that they're going to keep retrying different things and they're going to just basically keep going until they're able to succeed and hit that goal for you.

Now, obviously the more objective a goal, the easier it is to prove that. So, if you say, "Hey, can you, you know, work on this until you've pulled in 257 sources and then write the report, that's an objective goal, right? 257 sources and written report." But you can also set goals that are a little bit more emotional. Like your goal could maybe be more like, you know, until you're fully satisfied or until you've, you know, verified this over and over and you feel good about it.

And in that case, you're still going to, you know, get there and it will still decide when it's done. But as you get more objective with your goal, the goal prompts are just more effective. But let me show you one goal that I actually did that you guys have already been witnessing in this specific example is I went to my Hyperframes project. And hyperframes basically lets your coding agents build HTML and then render it as video.

So essentially it creates video. But what I did here is I shot it off a/goal prompt. You can see this one says sent as goal. So basically what I did is I said I need you to help me create some motion graphics for a YouTube video. So all the motion graphics you've seen so far were from this exact prompt right here. I'm going over 18 different Codex concepts. I want, you know, an intro. I want transition cards. I want all this.

So I basically defined that I wanted one intro scene and that I wanted 18 cards. And then you can see that it said I finished and I visually checked. meaning it actually took screenshots to make sure everything looked good before it decided to be done. And now we have all these animations. But what's cool about the goal prompts is that models nowadays are getting so good, the AI models are getting so good that it's actually better to give them a goal and then step out of their way.

If you really just try to like micromanage them, you're kind of just like muzzling their capabilities. So if the situation isn't super super risky, give them a goal and you can get out of the way. Now, there's one quick thing that I felt the need to address, which is basically the question, "But Nate, what if we've been using cloud code for a long time?" Well, I'm really glad that you asked. It's actually really simple.

Really, the main difference is the agents.mmd, thecodex, and the aagents. Because in cloud code, you basically have like your cloud. MD, and you have your cloud. So, when I first started switching over from claude code to codex, all I did was I said, "Hey, codeex, take a look at this herku project. I've been building this up using cloud code for the past couple months. I need you to help me get this codeex ready." And basically what that means is I made a copy of my cloud.mmd and called it agents.mmd.

So I have two of those now. One one aent.mmd one claude but they're basically the same file. And then I made a copy of all my cloud skills and put them in the agents folder and I made a copy of all of my like claude settings files and I put them in my agents. And the cool thing is you don't have to do any of that manually. You literally just say hey codeex look at the documentation analyze my project and make this codeex accessible.

Make it codeex ready. So anyways, if you were feeling a little bit of doubt about all that kind of stuff, that's the way I did it. And now you have a bunch of local files and folders that you can use on any agent harness whenever. It's very flexible. It's very tool agnostic, and that's what you want to be building at the end of the day. So anyways, had to address that real quick. Let's get back to the video. All right, awesome.

So let's move on to part two of these core concepts, which is environments. So the first piece of environments is number five, which is local versus cloud. So there's a couple things to talk about here. The first thing is if someone says, "Oh, is this running locally or are these local files?" All that means is does that exist only on the machine that you're currently using? Whether you're on a MacBook right now or you're on a desktop PC like I am right now.

When you say local, it just means it's only accessible by you. So right here, if I open up my files, these are basically local files. Now, they're syncing with one drive when I want them to. So that would kind of push them into the cloud, but otherwise it's completely local. So like if you're working on a word doc on your computer and you forgot to save it and then email it to yourself on so you could work on it on a different laptop that was a problem because it was locally on that other machine.

But something like Google Drive is always in the cloud obviously. But this also goes beyond just files. This goes to like things that are produced. So right here you can see that it actually created me this little site for all these motion graphics. So if I open up this site you can see that I can view all of these videos. I can click into the different ones and it threw this together for me really nice and it served this to me on a local host.

So right here you can see that this URL is 127.0.0.1 and the port of this local host is 8008. Now realistically that's not super important. You don't really need to understand what exactly this means. But this is just a local host. But this is a little confusing because it looks like this is a web address that if I, you know, emailed to you, you could open this up and have the site. But what would happen is this would show on your screen or it would show on your computer as nothing actually lives here.

So like if I copied this and I pasted this into a new browser but I changed the number to 7. I don't think I have anything running on port 8087 on my local machine even though you might. So nothing actually loads up. And it's quite funny. I remember seeing these these tweets where I think it was a joke but it was like uh someone was pretending they're a beginner and they were like wow cloud code and codeex it's so cool.

Look what I built in one day. and then they, you know, attached a bunch of local host addresses and obviously no one else could open that up because they're not on that local device. So anyways, that is the difference between local and cloud. Now the other piece here is that when you're spinning up these new chats, you can kind of have these be either local, meaning right here, you know, I'm working in my local files and folders.

And that's great because codeex can actually like edit these files, right? It can delete things, it can make new ones, it can edit them, it can move them around, it can go to my downloads, it can go to my desktop, it can do anything on my computer really. or you could actually have these work in the cloud. And what you'll notice here is when you choose cloud, you no longer have the ability down here to actually choose the model you were using and the permissions because this sets up sort of like a cloud sandbox environment.

Now, I'll be honest, I hardly ever do this because when I'm working locally, as long as I keep my machine on, as long as I keep my PC on, it feels pretty cloud-like. And here's what I mean by that. Right here, you can see that I'm mirroring my phone and I'm in the Chad GBT app. And if I go over here and I click on this right here which says remote, this lets me see all of my actual codeex chats that are right here. So if I go to Herk 2 and I go to summarize past month, this is exactly what we were just looking at right here.

You can see this is literally the same conversation. It has those three chats and I could come in here and I could say hi and this gets sent in my actual codeex right here on my laptop or sorry on my desktop as well as my phone. So, as long as my machine's on, even though this is running locally and I'm out on a walk, I'm out at dinner. I could even be in a different state and I could control my desktop from my phone right here.

So, let's say for some reason I left a file locally on my computer, I could just say, "Hey, can you email that file to me?" And then I could use it on my laptop. So, anyways, just wanted to show off that remote capability. And that's going to bring us into concept number six, which is work trees. Now, honestly, this is something where if you're not really building software or, you know, production apps, this isn't going to matter to you too much.

Like I don't hardly ever use work trees, but it is good to know about since you will see these in the interface. So right here you can see that if I was to go to um the local setting, it says that you can work in a new local work tree which says create a copy of Herk 2 to work in parallel. So basically because I'm working in Herk 2, if I was going to do something like risky or if I wanted to try and experiment with something or for example, if I was building software and I wanted to try to change the way that the onboarding flow worked, but I wanted to like not interrupt the main branch, especially if other people on my team are working on that main branch, I could use a work tree to basically create a copy and I could test in there.

And then what you can do later is you can merge it back into the main. So it's basically just a duplicate that lets you test. But like I said, there's hardly any times for knowledge work that I ever use work trees. And if I ever am building software and stuff, a lot of times Codex will say, "Hey, by the way, you might want to use this. You might want to do this in a new work tree." So, I wanted to call it out because it's important because you might see things like this master branch and you might see other work trees that might have been spun up automatically.

But I will say it's not something that I'm actively thinking about or think that you need to be actively thinking about in order to get the most out of codeex. So, wanted to bring that up. But let's move on to number seven, which is codeex. Now, this is really interesting. We talked about how when you're inside of your project, you have things like an agent.mmd. Now, if I go to my files, there's also something in here called a codeex.

So, if I open this up, what you'll see in here is I have some agents and I have some workflows, but I also have a config. ML file, which is basically like some local settings. And there are basically going to be two different places where a codeex file lives. And that's either going to be inside of your project. So like in this example, this is my codeex inside of my Herk 2. But there's also going to be one which is user or global, which means this lives under your actual user.

And these are settings that hold things like memories and sessions and automations. These are things that will apply to your global codec. So whenever you're in Codex, regardless of what your project you're actually in, the docex will have personal settings and app data and stuff like that. Now once again, I think this is something it's important to understand where that lives and what it does. But this isn't a folder that I'm actively thinking about and actively having to like maintain.

But I did want to call that out because sometimes if you need to have a certain setting applied or something like that, that is where it lives. Now, the cool thing about this is if you're ever confused, you say, "Hey Codeex, what did you do there?" or "Do we need to add this to my codeex or do we need to move this to a different folder?" You can just ask it questions because it can search through its own documentation and understand how to do things like correctly.

But I do think that understanding the difference between project scope things and user scope things that's definitely important especially as we get into the agents which is going to come up later. And that is a great segue into part three of the core concepts which is control and customization. So number eight here is about different AI models. So when you are starting a new chat you can choose the model you want to use.

You can also change the model in between messages. So, I could shoot off a message on Astra and then I could, you know, change this to something else and then I could shoot off another message and I can keep changing if I want. Now, if you're watching this video way later, maybe the model names look different, but essentially the theory is the same. You have different models to choose from and they all have different prices and strengths.

So, like right now, GBD6 Astra is just the absolute strongest, but it's going to cost the most. It's going to eat the most of your weekly limit. Right here, you can see that I'm at 100% because it just got reset. But as you chat with Astro, it will drain your weekly usage faster than you know 5.6 Soul would, which would drain your usage limit faster than 5.6 Tarot would. Now, right here, I just want you to look at the API pricing so I can explain to you how these models are actually billing you.

So, they build by tokens, and they usually build by 1 million tokens. Meaning, on Astra, for every 1 million input tokens, it will cost you $10. And for every 1 million output tokens, it will cost you 50 bucks. And here you can see the different pricing for these different models. And you can see how it gets cheaper as you go down. Now, this is API pricing, which means if you were building an automation that was programmatically using these models, that's how much it would cost you.

But this usage inside of Codex, that's not programmatic. This is usage limit or subscription limit. So, when you pay 20 or 100 or 200 bucks a month for Codeex, this is what you're actually your usage limit is eating up is that subscription. And you're getting way more inference. Like, this is a $200 a month subscription. And if I use all of my weekly usage every single week, I'm getting about $14,000 worth of inference every month and I'm only paying 200 bucks for that.

So the subscriptions are much cheaper than if you were using the API pricing. But if you ever do go over your weekly limit, you'd have to buy extra codeex credits. I don't exactly know why they price it like this, but you know, you can see they just give you codeex credits instead. So let's say I went over my weekly limit. I could go here and I could click on buy credits. This would bring up this screen which lets you buy credits by like the thousands or something like that.

And that is what I wanted to show you guys. So like 2500 credits, 5,000 credits, 25,000 credits. And this is how it would charge you based on those tokens. Now, if you've never heard of tokens before, I know that might be a little confusing. Think about it as roughly four characters or roughly 3/4s of a word. And there's an OpenAI tokenizer right here where if I paste in some text, it will show you how many tokens this would be.

So this paragraph, for example, was about 240 characters or sorry 274 characters and about 56 tokens. And it's interesting because sometimes punctuation is a token, right? Like this period is a token, this comma is a token, this word's a token, um this word's a token. And this is basically just kind of breaking down what it might look like for these tokens. But anyways, you can see this was 56. And what else you might notice is that I earlier said input tokens or output tokens.

Input tokens are whatever you're feeding in. So your prompts or if it's reading like a PDF or a word doc those are input because they're going into the model and output tokens are anything that it outputs. So even its reasoning here is output tokens. This entire thread is output tokens and that's why the output tokens are more expensive. Okay. So let's move on to number nine which is about effort. So within each model not only do you choose the model but you can also choose the effort level.

So right here I can move Astro down to medium or I can move it down to low or I can move it up to extra high or if I go like ultra I have to allow full access because that can get you know pretty autonomous. But anyways the point being as you move up on these effort levels you get more quality like you get more intelligence but you also get more cost. it's more expensive to run it at higher effort levels. And that's why when you see these benchmarks, when there are new models released, you'll see the model, like for example, Cloud Fable 5, you can see this mark was on low and this one was on medium and this one was on high.

So, it shows how one model can behave differently and also cost a different amount based on the effort level that it was being used and tested at. Now, it actually is pretty nice to play with these because sometimes Astra High is just so much more powerful than what you need to do. Like if you were using GBD6 Astra High to help you write an email, that's overkill and you're paying way more than you should realistically to write an email.

I could probably come down here and use 56 Terra and be just fine with that and it's a lot cheaper. So definitely try to play with the model and play with the effort based on your task. But a lot of times if you're just doing a lot of knowledge work, I would just chuck it on sole and I'd maybe just go to medium and just call it a day there. Now the other thing about effort is you can do something called fast mode. This obviously makes the model respond quicker and do things quicker.

And it it's 1.5 speed, but it costs you more usage, so it will eat your weekly subscription faster as well. All right, and moving on to number 10, we have permissions. Basically, right down here, you can see that this is orange and it says full access. This is basically Codeex's yolo mode, which means that it's not going to stop and ask you a bunch of permissions and questions. Can I do this? Can I do this? If you go on ask for approval, it's going to always ask to edit external files and always ask to use the internet.

So that's if you want to sit here and really sort of like manage it and you're wanting to make sure everything's safe, you know, maybe start off like this so you can just understand, oh, okay, it's asking me if it can run this command or it's asking me if it can open up my browser and then you just get familiar with what it looks like for Codex to actually run that agentic loop. You could also go on approveof for me.

So it's only going to ask you if actions are detected as unsafe, like maybe deletes or maybe certain sorts of like API calls or things like that. So that's how these permissions work. And if you really want to get granular about, oh, I want to like make sure these certain actions never happen, you can ask Codex about that and it can work things into those config files like we talked about earlier with the codeex that it can certainly like block things out.

But now let's move on to number 11, which I think is my favorite one, which is skills. Skills are so so important. They're basically reusable workflows. They're recipes that let you do something once and then teach Codex how to do it the same way every single time. So now you can just run all these skills. So like I said, a skill is basically just a recipe. So, let's say you come in here and you make, you know, a chocolate chip pancake and you followed a recipe to make that pancake.

You would basically say, "Okay, if I ever want to make chocolate chip pancakes again, I'm going to use this recipe because I know that I'm going to get a good result." But let's say that you burnt these pancakes and you said, "Okay, well, what I need to do is make a quick update in this recipe to say, hey, you know, cook it up 30 seconds less on each side." And the next time you run the skill, you basically see, okay, are these better?

Are these good? Do I need to make any more feedback in here? Or now, is this skill just the way I like it? And then your agents are able to use these skills. So here's an example where I basically gave it a YouTube video. So you can see that this is literally just a local file path of a YouTube video. And I said that I needed a video description, timestamps, and a LinkedIn post. It went ahead and it ran its agentic loop and it gave me a description, timestamps, and a LinkedIn post.

And then I said, "Okay, now I need you to turn this into an X article." And put the draft into my X as a draft. And it knew exactly how to do this with a thumbnail, with a title. It also put screenshots from my actual video and it sprinkled them throughout my whole X article. And this is because it used a bunch of skills to be able to know how to do this. So right here, if I ask it, what skills did you use? It used my YouTube description skill, my timestamp skill, my LinkedIn post skill, my X article skill, my X article from video skill, my format X article skill.

It used all of these skills because I've taught it how to do something good once. And then every time I run these skills, I just give feedback. Hey, that was good. You know, I liked this, but I didn't like this. Update the skill. And now what's cool is you can just invoke these either with natural language. It will be smart enough to do it with natural language, or you can do it as a slash command. So, I have one in here that I can call like the audit.

And you can see this will run my audit or I have one in here called the 3D brain. And this runs the 3D brain. Man, I think I planned this out so good. This is going to bring us on to number 12, which is agents. So, we talked about codeex. And agents is basically the exact same. It just holds different things. So, right here, you can see that the agents holds your skills. And these once again can either be project level skills or they can be user scope skills.

So, they can be global skills. So, if I come into this chat right here, which is inside of my um you know, Herk 2 project, and I go to open up the files, and I go to my agents folder, which is right here, we have a folder called skills, and this is a bunch of skills, as you can see. Now, if I open up an actual skill, so for example, let me go to my YouTube description skill. This is an actual skill.md. So, once again, MD just means markdown file.

So, what we have here is some metadata, and this is what Codeex will read to understand, okay, do I need to invoke this skill or not? So, it has the name and it has basically when to use the skill. And then all the skill is is just instructions. It's, hey, for Nate's YouTube descriptions, keep them short, two to four sentences, paragraph form, no bullet points, no m dashes. Here's the process. You read the video outline.

You identify the core topic. You write a short paragraph. And that's the skill. It's a very, very simple prompt. But if I go to my ex article one, they can also be way more in-depth. So, this one is way longer. There's a lot of other rules and a lot of other criteria. There's way more steps. There's way more things to do. And also what's cool is skills can reference other things. Skills can reference other skills. They can reference other agents.

They can reference Python files or context files. So in this example, this skill references my voice guidelines like my LinkedIn style guide as well as my ex article style guide. But that is where your skills live inside of the agents folder. And then moving on to number 13. Here we have plugins. And this is where a lot of the magic actually happens because you can super easily come over here in the Codex desktop app.

You can go to plugins and you can connect a bunch of things. You can see all the stuff that I have installed like Alpaca, Gmail, ClickUp, Clay, Google Drive, GitHub, Canva, and the list goes on and on. You can also search for different plugins. So, let's say you were really interested in connecting something like, I don't know, let's see, do they have a LinkedIn plugin? They have a LinkedIn plugin where we can find the right profession, we can grow our business with ads.

We have all these other sorts of plugins, too. So, if you want to try to connect your different apps, just come in here and see if you can connect them using these plugins. Maybe they have Composeio, they don't have Composeio, and if they don't have a plugin here, you can still connect it using Aenv using an API key. But plugins are so much easier because you can just basically sign in once. They've got ones for creativity, for developer tools, for business and operations, for data analytics, communication, and they're basically always growing this plug-in library.

All right, so that now brings us on to part four, which is tools and scale. Okay, we've got five left here. Number 14, we have the browser. Now, this is definitely one of my favorite things about Codeex. If I open up the tab over here, we can open up a browser, which is really cool because I can basically just control this. So, like I could go to school.com. And what you'll notice is when I log into school.com over here, I'm just going to zoom out a little bit.

You can see right here that I'm already logged into my school account. So, I could manage my different communities, which also means that Codeex can help me manage my communities from here. Because when you save these login inside of the Codeex browser, it then saves them. So, if you say, "Hey, could you go to that account and pull the report for me?" or hey could you go into school and could you make this post for me it can do it through the browser if there's not a plugin or if there's not like an API or MCP server and the browser use of codeex and specifically with GBT6 Astra is the best that I've ever used ever I'll play a clip right here where I asked it to basically open up Canva and paint me and draw me using the tools in there and I gave it just a picture of me and it was able to replicate it in a way that I thought was really really good.

So, silly example, but it definitely demonstrates the vision and the browser use capability of this agent. All right. So, number 15, we have sites. So, if you go over here to explore and you click on sites, this is very, very cool because it basically lets you put things out there onto the cloud. Remember earlier we talked about local versus cloud. Codex can build something for you and it can be a local host, but then you say, "Hey, can you just put that on a site real quick so that you could have your team log in or so that you could share it with, you know, other people and make it publicly accessible." Like right here, you can see this London and Paris one is everyone whoever has this URL could go ahead and open this up.

Whereas this one is just me. So it would literally have to be logged into my account in order to be able to open up this site. And what else is amazing about that is you can open up the analytics for this site. So you can basically host things. You can connect your own domain and this is basically going to replace something like a Versel or like a I don't know a Squarespace, wherever you wanted to host your sites normally.

You can now just do it right here from the Codex desktop app which is pretty cool. You can also even connect a database. So on the back end if you had to store like user login data or you know permissions or settings or you know a database of customer records whatever it is you could actually store that here too and it's really cool. All you need to do to actually use a site is you just basically have to do either say hey can you turn that into a site or you could do slash site and then it will basically know that you can you know host a site or build a site.

So great touch here from codeex. All right so number 16 we have sub aents. So, sub agents are really cool because it lets you delegate work out to a bunch of different Codex agents. So, right here in this main chat, you can see that I'm talking to GBT6 Astra, which is a really, really smart and intelligent, but also expensive model. So, let's say I wanted to do a bunch of research, but I didn't want to waste Astra's brain on that.

Or let's say I wanted to do like a bunch of different testing and just do a lot of stuff at once. Astra here that I'm talking to can delegate workout to tons of sub aents. Hey, I need you to search through X and search through YouTube and also dig through my own comments. So, just find, you know, what are people talking about right now in the AI space. Is there any big news or drama? I don't want you to do this research though.

I want you to basically just delegate a bunch of sub agents out to do the work and I want all of these sub agents to be using 5.6 Terra as the model. So, shoot off those agents and let me know what they find. So, this is really cool because I can specify that I want those sub agents, those little like researchers and workers to use different models. So right here it's using its agentic loop and it's going to spin up these agents.

And whenever you see these little colorful things, these are different agents that it's spun up. So right here, this one's called X. And when I open up X, it is actually this sub agent working right here. I can watch this sub agent go through its agentic loop and I can watch it like pull in data and everything like that. So this is the same thing as over here, but this one is just a different model and it's not the main session that you're currently talking to.

You can see we have two others that started working. We have this one called YouTube Pulse. And once again, it's going through the same exact agentic loop. We have this one called X drama. We have this one called audience comments. And we can basically watch all of these work, but we don't have to manage them because once these agents are done, the main session here will say, "Okay, cool. All five are done. They reported back to me.

Here's what they found." And this is really good for gathering different perspectives or researching out a bunch of things in parallel. And these intelligent models are really, really good at delegation. So sub agents are definitely something that you need to be using. So, while these sub agents are fanned out and they're working, let's move on to number 17, which is scheduled tasks. Scheduled tasks are awesome because this basically lets you have your codeex working autonomously for you.

So, on the lefth hand side, if you click on scheduled, you can basically ask codecs to schedule things for you, reminders, updates, or run full sessions. Because all a scheduled task basically is is it injects a prompt into a codec session like this. So, it uses your same local files, it uses your same skills, it uses your model, it uses everything. thing the agentic loop it just does it automatically for you. So in here I you see that I could create one and I could set it up manually.

I could have it run locally or I have could have it run on the cloud. I could also choose what project to work in. So Herk 2 or you know Hyperframes editor. I can also choose what chat. So every one of these routines could be a new chat or it could be a new chat for this task or it could be even in an existing thread that we already have going. And then you can basically choose when to schedule it. So, it could be daily, it could be hourly, it could be, you know, weekly, or you could get it really, really custom in here.

And the cool thing is you can describe everything in here manually, or you could basically just ask Codex to make one for you. So, for example, I have these like seven or eight different ones that are running for um trading. They're literally trading $10,000 of my real money. And I have this set up as scheduled tasks so that they can basically all work together, talk to each other, check the market, make trades, things like that.

And of course, you guessed it, these run in a different project right here called trading challenge. And they all run inside of this challenge thread. You can tell that this has scheduled tasks in it because there's a little clock icon next to that thread. And moving on to the very last concept we have for today, number 18, this is voice mode. Now, everything that you've learned so far, skills, sub aents, projects, agents, all of this can be controlled by using your voice to have a real conversation with Codeex.

With your voice, you can manage different codec threads. You can delegate different agents. You can run skills. You can set up schedule tasks. You can build sites. You can do anything here with your voice. And all you have to do is come down to the bottom left and click on start new voice chat. So, forgive me here as I'm awkwardly like hunching down because my headphones don't reach far enough. But watch this. Hey, Codex.

So, I need you to help me out real quick inside of my Herk 2 project. Can you start a new thread to make a thumbnail? I'm making this YouTube video about 18 CEX concepts. So, if you could make me a thumbnail for my YouTube channel where you see me sitting at a desk working on a laptop and I'm pointing to the right and there's like 18 different little AI agents. Um, yeah, just start start with that. And then once you have finished that thumbnail, could you send it to the thread that is currently working inside of my her 2 as well and it is doing research on YouTube and X and um looking at my channel and stuff like that.

Could you just send that thumbnail to that thread? >> All right, let me check on that. Okay, I've got your thumbnail brief queued up with you with the laptop pointing toward the 18s using your existing photos for reference. And that found your research thread. So, I'll send the finished thumbnail there. Now, do you guys see how this is all coming together? It started a work tree chat. It was doing the agentic loop. It also created a goal down here.

It literally created its own goal because it knew that we had this, you know, task for it and it started working. And you know, the voice chat's still going. So, I don't know what it's going to think of this, but I just wanted to call that out because all of what we just talked about is all coming together because even you can see over here, it started making that actual prompt. Like, it shot off this prompt right here and it started off this new thread.

And now this is working in a work tree and it's going to create that thumbnail for us and then it's going to send it over into this actual chat and we'll see that actually happen. But as you keep navigating, like you can go to the web and you can go to, you know, other things and you can keep this voice working. So as you're just working on your laptop, it'll show you what's going on and you can keep talking to it. And you can also do all this on your phone as well because of the whole remote thing.

You can use voice mode when you're on your phone, too. Okay, so that finished up and you can see what happens is it actually can send tasks or messages to each other, right? So what happened was this was the original thread that it created to make the image and it made this and then it sent it to this thread and said, "Hey Nate wanted me to send this to you. Here it is." So with just your voice, I know that was a very simple example, but you're able to coordinate a bunch of different codec threads, manage them, multitask while you're on the go, while you're flipping between different apps.

Very cool. All right, so now that you guys have learned the core concepts of codecs, we're going to start to actually get in there and play around with some of this stuff. So, what I want you guys to do here is think about the way that we're actually going to start using codecs. Don't think of it as a tool that helps you build like AI workflows. Think of it as your new operating system. Basically, what I mean by that is you should be reaching for codeex whenever you want to do a new task.

And that's the whole mindset shift behind becoming AI native, which is actually the book I wrote right here. As you can see, this book is all mindset oriented. It's basically just about how do you talk to AI? How do you use it? And how do you change the default to, oh, okay, I'm just going to open up Google Chrome and open up this new tab and just do the job. the old way, the manual way that I'm used to. How do you shift to, okay, I'm going to open up codecs and I'm going to use this as my operating system.

I'm going to figure out how can I build a skill for this? How can I use the browser used to do this? How can I turn everything that I'm doing into faster processes because I've built systems around it? And that doesn't mean we're giving up a lot of the judgment or the control. That still sits with us, the human. It just means that we're able to move faster and we're able to do way more. And the way that that truly happens is when you build your AIOS and your second brain, meaning you're not just opening up a new chat. you know, a new chatbt tab every single time you have to do something.

You're building a system where every single time that you talk to it, it gets smarter. Every single time that you build a deliverable, it saves it and it remembers it. You're essentially turning AI from, you know, what we used to call like a personal assistant or like an executive assistant. Not anymore. We're turning this into a co-founder. We're turning this into like a business partner that actually can work with you and keep up with you and remind you of things rather than like forgetting things or hallucinating things.

So, we're going to jump into this next section and I'm going to teach you guys how to build your own AI operating system. And just a quick heads up, guys, throughout this course, I'm going to be playing different clips and different little segments that I might have recorded at a different time of day or, you know, last week or something. So, if I look a little bit different in some of these, that's why. But I have very intentionally laid out this entire course in the order that I think makes the most sense to follow it.

So, hopefully that'll make sense. But yeah, let's get into the next piece and start building out your AIOS. GBT6 Astra is the most powerful AI model I've ever used. So, I turned it into my AI operating system and my second brain. And this is just a quick visual, but right now what you're seeing is my actual company. This is my second brain. This is everything that I know and everything about my business. And because I have everything actually stored and usable, that means so does GPT6 Astra.

So when I say AIOS, what I mean by that is an AI operating system where now I can basically do anything I need to from right inside of this interface with Codeex with GPT6 Astra because now it doesn't feel like I'm just talking to a chatbot. It feels like I'm talking to a co-founder, someone that actually knows everything that's going on in my life and my business. So today I'm going to show you guys how you set up an AI operating system from scratch, but if you already have one going, how you can keep improving it.

And I'm going to give away a bunch of free skills that help you set up exactly this and help you set up other things like auditing your AIOS, leveling it up, and just setting up the structure. Right? Now, what you'll notice here is that this isn't just a random dump of knowledge. Right here in blue, this is my business wiki. So it's like AIS coaching, our corporate structure, our Ammation Society Plus. And when I click in, we can see all of these things in these different relationships.

I can also see how stale this is, so I might need to update it. and it calls out all these areas where like this number is old. I need to update this. But it also shows me all the different connections where this specific node is linked into every other area of my business. So like I said, that was business wiki. I also have meetings that I've added in here, which takes up a big section. I've got video knowledge. So every single YouTube video I've made, it has all that knowledge and it relates it back to everything in my business and in my meetings.

Same thing with the clawed memory right here as you can see. Same thing with codeex memory. I've also got a bunch of projects and then I have skills and agents and this forms together my herk brain and I've even gone as far as to take this exact brain and put it in its own OS dashboard where I can basically have my calendar over here. Today's a Sunday so I don't have many meetings and this is fully functional, fully synced with my calendar.

We've got these three stats, YouTube subs, AIS, AIS plus and these are fully synced. I can come in here and manage my brain. I can search for different things. I can look through different things. I also have my communication fully synced. So Slack, ClickUp and email and these are functional. I can respond to things from here. I can also see different meetings that I have coming up as well as past meetings with the AI summaries already generated.

And then I can get community pulse. So top YouTube comments, top AIS plus posts, what people are stuck on, as well as industry pulse from things like YouTube and X. And all of this of course was made with GBT6 Astra. But really the idea of an AIO OS or an operating system is my framework that I call the four C's. So context, connections, capabilities, and cadence. And the way that I think about this is I think about these first two things as the second brain piece.

So I think of this as your second brain and then over here we have the actual AIOS and this is the capabilities and the cadence. So let me real quick explain what I mean by that. What's the actual difference? So the way that you get this thing to actually feel like it knows you is by giving it context. So I mean things about you and your background and your business and your goals and your priorities and things like that.

I think of context as the things that are in your life that really don't change too much. So quarterly goals or yearly goals or what your business does, your avatar pain points, things like that. and the connections. I think of things as the tools that you use every day because the data in there is always relevant and it's always changing every day. So, your email, different data is always in there. Your conversation, Slack, ClickUp, your project management, your financial information, giving your AIOS the ability to know all the context, but also reach for things just in time when it needs it.

That's how you build a really, really powerful second brain that helps you actually ask your AIOS questions or say something and rather than getting a vague or generic response, it knows what to do. So, for example, when I asked Codex to make me this AIS sizzle reel, I didn't tell it everything I wanted. I just said, "Hey, make me a sizzle reel for AI Automation Society." And it knew all this context, and it also knew that it could go to my school community and look things up in order to make this.

In fact, what you'll notice is it actually went so far as to go to the community, take pictures from it, like take screenshots itself, and add those in here because it knew that this is what I was talking about. So, I have these three little tests that I like to run, which is basically if a teammate messages you with a question and you realize that your AIOS would answer better and faster with the exact sources, then that's a good sign that your AIOS really is where it should be.

Another one is context switching reduction. One thing that you should challenge yourself to do after you've gotten this set up is to try to force yourself to do everything from here, from this interface. rather than opening up all those new tabs and doing it the old way. Try doing it the new way of using the AI as your operating system. And then number three is the knowledge leaves your head. So stop trying to remember everything.

You don't have to rehearse what you decided last quarter or what your customer said in that meeting because you trust the retrieval of asking your AIOS because it can find it in your Slack threads. It can find it in your email, find it in your meetings, or it just knows it. Because if you start to build new skills and capabilities and you start to put cadence into play, which means agents that run autonomously and automations and things like that, these things are not nearly as valuable without the first two C's because otherwise these skills are very generic.

And the automations are just like I said, generic. So these four things really come one after the other, context, connections, capabilities, and cadence. And they all work together very beautifully. And that's how we get our AI operating system. So in order to get started or to scale all this up and get all the resources, I need you to go to my free school community. The link for that is down in the description. Like I said, it's completely free.

And you're going to go to classroom. You're going to click on all YouTube resources. And you're going to grab the AISOS resource pack. This thing is going to come with five skills. It'll come with an onboard skill to get you set up. It'll set up your whole project structure, your files and your folders. Then you'll have an audit skill to do frequent checks on your AOS. You'll have a link skill, which helps you route to different files when you need to.

You'll have a level up, which you can run after your audits that tell you, hey, this is probably some stuff you should do based on this audit. And then you have the 3D brain skill which helps you turn your knowledge into this actual 3D brain like you guys saw right over here. Now, yes, it is these four things. And when you start to run that resource pack, it'll onboard you and ask you questions and it will start to fill in this information which is great.

But then what comes next is something that's super super important and that is called the agents.md. And so if you've been using claude, this is basically the claw. MD, but now this is the one that Codeex is more familiar with reading and it's the exact same thing. So, if you are coming over from Codeex, literally what I would do is I would just copy your claw.md and then just name it agents.mmd. It's the exact same thing.

And just to show you guys what mine looks like, if I go into here and I go to my files, you can see that it's very simple. It's you are Nate Herki operating system. Here's your job. Agents.mmd and cloud.mmd contain the same stuff. And then I basically give it a few core operating rules like to be concise and I use bullet points and don't use m dashes and you know use the Oxford comma. But then I go into a routing map and that's the majority of my agents.mmd.

I think of it as you know core rules but then I think of it as routing meaning can my agent understand where everything lives because if I open up my Herk 2 project which is just like we said a combination of folders and files and that's all this is displaying is folders and files and it's showing the relationship between all of that but the point I'm trying to make is that this is a lot right there's a lot of folders and files and I can go into my projects and there's a lot more in here and then I can go into things like you know my YouTube videos in here and it's even more but because all of this is laid out in a way that to me is intuitive That also means that my agents can crawl it a little bit better.

But the more that I have information in here like routing logic, like, hey, if you need business advice or team stuff or OTAAS, you look in the wiki. If you need corporate structure or entities, you look in this section of the wiki. If you want to look at Nate's voice and style, you look here. If you want to look at course knowledge, you look here. If you want to look X, go Y. If you want to look A, go B. And you can see there's a ton of different rules in here, but what's important is that the agent knows this every single time it loads up so that when you ask for something, it knows where to look.

Because that's essentially how the agents.mmd file works. You know, you say, "Hi, codeex." And before it even will read your message, it reads this first. So, it reads this and then it reads your message and then it will respond with like, "Hey, how can I help you today?" You know, that's kind of what it will say. But it always reads this context first, which is why it's so important. All right. So, if you're a complete beginner, how do you actually get set up with all this?

Well, let me show you. First thing you're going to want to do is you're going to want to go to somewhere on your computer. Let's just say it's your desktop. And you're going to create a new folder. And so for example, this is where I am using my Herk 2 project. But for now, I'm just going to call this AISOS demo. So you can call this whatever you want. Now once that folder has been created locally, which just means on your computer, you're going to open that up in Codeex.

So at this point, if you don't have the Codex desktop app, download that. And then if you aren't on a subscription, just get on subscription. But now what we're going to do is we need to open up this OS. So what that means is you would come in here and you would click on new project. You would create a local project and then you would give it a name and then choose this folder. So this is once again going to be AIS demo and I'm going to open up that folder.

If I go to my desktop and I just have to find this folder we just made right here. Select that and then go ahead and click create project. So this now means whenever we are doing things in here, we're working inside of this actual local folder which if I open this up, there's nothing in here right now. But you will see as we start this whole onboarding, this folder will fill up. So, what I'm going to do is I'm going to go to the resource pack and I'm just going to copy this actual URL.

And I will now paste that into the chat and say, "Hey, I want you to install this and just go ahead and run the onboard so I can start giving you some information and building my AIOS." So, now that this is installed, it's going to start onboarding you. And you can see that it's going to say, "I will save your answer as you go." So, obviously, you guys should take some time and give this some pretty specific information, but I'm just going to blow through this real quick.

So, my name is Nate and I run an AI education community and we have a certification program and we have live events and things like that. And what's going to happen is it's going to start creating folders and files for you. If you click on this button and you go to files, you can see that it's already created a bunch of stuff in here. None of this was in here. If you guys remember, this was all completely empty, but now it's starting to set up the actual structure.

But really, the two most important things to call out right now are the context folder. This is where it's going to start to create some markdown files of business context and also the agents.mmd. I remember I showed you guys mine and this is going to start getting built out over time with you guys right in here. Then it asks you to paste some of your recent writing so that it can start to build some skills around how you write.

So what I'm going to do real quick is just basically fly through these seven questions and then you guys do this as well and then come back. All right. So now that I've done those seven questions, if I open up a new thread, I can actually say, "Hi, who am I?" And it will check my profile first because now it can actually look at all that and understand that. So if I open up the files once again, we can now see that if I go to my context, we have one called about business, we have one called about me, and we have one called priorities.

So if I open this up, you can see that this has information. If I open this one up, this one has information, too. And over time, these will continuously get more filled with context. And this is context, like I said earlier when I was talking about these four C's, context that we want to basically be more evergreen, right? Information that's not changing very often. Whereas these are more the connections where you have information that changes very often.

And that's when you're going to start filling it up by looking at things like this. You're going to start looking at um what bookmarks do you have? What desktop apps do you have? What apps do you use the most on the weekly basis? And I like to think about it as far as like revenue, customers, calendar, coms, tasks, meetings, and knowledge. And then once you've taken some time to like list them out here, just say, "Hey, Codeex, I want to connect to school.

How can I do that? I want to connect to Stripe. I want to connect to YouTube. how can I do that? And it will tell you, oh, you need to get this API key or you need to use this MCP server or maybe you need to use browser use. And it will help you figure out the best way to connect to all these tools. But what else you'll notice is that it's creating the things that we need in case you ever want to go over to cloud code like acloud folder as well as a cloud.mmd.

So it's really helping you make this your own AIOS, your own IP where you're not locked into one ecosystem. So anyways, I just wanted to call that out. But the agents and the cloudmd file are basically identical. Right now we have like the operating system, we have some skills, we have where things live, but right now this is pretty empty. So obviously we need to get this filled up a little bit more. You can also see that in the references section we have a voice.

So if I go to my references and I go to the voice MD, we can see that this is stuff about how Nate talks based on the information that I've given it so far. So anyways, now you can see we're starting to get some stuff filled up here. But now what you'll do is once you have connected some things, you're going to go ahead and run the audit. So you can do / audit. This will automatically be installed because you use the resource guide.

And this basically checks the AIOS. It looks at the four C's. It gives you a score. And it will also look at your agents MD or your cloud NMD and make sure everything's synced up like I said. And what else is cool about this is this creates another folder in your AIOS called audits. You can see there's nothing here called audits. But what's going to happen is it's going to give you a report and then it's going to store your audit.

So every single time you run this, let's say you want to run it every Monday or every two weeks, it will store your scores every time so that you can see how you're actually improving your system, you know, month over month. So I know if you're new to Codeex and everything, this might feel a little bit intimidating, but it's really not too bad. And the cool thing about this is you can just ask questions if you ever get confused.

Hey, why'd you do that? Or where should I put this? Or, you know, how do you feel about all this? You can treat this thing like your best friend who's really smart, who's also a mentor rather than just like a chatbot. Okay, but you can now see that this audit is done. And obviously, we scored a 30 out of 100 because we literally just built this and there's not much in here. But it'll show you across those four C's what needs improvement.

And you can keep working on that stuff. And over here, you can see that we have a new folder called audits. We have this markdown file which shows us that today, September 7th, you ran this audit. And here was basically the conclusion of that audit so that you can improve on it. Now, what you can do from there is you can go ahead and run another skill which comes in the kit, which is called a level up. So, this one will basically look at this audit report and then it will help suggest areas for you to improve it.

It'll help you think about different connections and different ways that you could, you know, build in some more capability and build in some more cadence so that this thing keeps growing and keeps growing. So, here you can see it said, I'd start with turning team updates into one clear action list. It targets your stated bottleneck coordination, taking time away from learning AI and making videos. So, two candidates here, which are team action list and certification improvement backlog.

So, I would then think, okay, cool. So how do we actually start driving towards this? You know, what do you need to see? What connections do we need to set up? And then how do we build these automations? And so you can just keep running this loop of auditing, leveling up, building, auditing, leveling up, building. And this is the type of stuff that Astra is so good at because it's so so smart. It really feels like it's got some really incredible general intelligence, especially as you give it more and more data because it's really good at building automations.

It can oneshot a lot of this stuff and it will help you build all these routines. So automating some of these little tasks is no problem. The real issue is getting everything from your head into the system because the more you give it, the more context you give it, the better it gets obviously. So yes, it can give you these recommendations, but now what I want you guys to think about is how you can give it more data.

So I do have this other skill here called Grill Me. It was inspired by Matt PCO's Grill Me and I will actually put this in the AIS OS kit. So if you install it based on this video, you'll have this here. But I didn't do it right now. So anyways, then you could use the grill me and say, I need you to use this grill me skill to just, you know, find out as much as you can about my current priorities in my business. And what this does is it will basically do similar to the onboard where it asks you questions, but this is a separate skill where it just relentlessly grills you over and over.

And what's cool about this is you just keep having it grill you on different topics because every time you start one of these interviews, it will create a new file in your AISOs and it will store all this interview. So every single time that you come in here for 20 minutes, 30 minutes, and you just get interviewed by AI, it's going to store all that. So you're just building up your second brain over time, and it's really, really cool.

As you can see, it said, I'm going to save every answer in business priorities capture. It created a new folder right here. And now we have this markdown file where as I start to answer these questions, it's going to store everything. So that's something that I would recommend going through with business priorities, your team, you know, your goals, and just like a bunch of different topics about your business and about your life.

Now, the next thing you need to do, and it's how you actually get something more like this where you actually have like all of these relationships forming between these different things that you want to put into your AISOs or into your second brain. This gets really important because the relationships is what makes this actually connect to everything and what makes it feel more holistic rather than just like a data dump.

So, the way that you get to this point with all these relationships is we're going to use Carpathy's LLM wiki. This basically just has AI crawl through data sources and find those connections for you. So, it's really, really cool. And guess what? It's really easy to use because all you have to do is you can either copy this URL, which I'll put in the description of this video. Or you could just come in here and you could copy this.

Like you could literally just go like this, copy it, and then come into your actual AISOs. You can start a new chat and then say, "Hey, based on what you currently know about me, I want you to build me a new LLM wiki, and I want you to do so on all my business contacts and everything using this Carpathy wiki method." And then you can literally just paste in that prompt, and boom, it's going to crawl through everything.

It's going to create you a new wiki vault. And you can obviously be more specific like I have one vault for my YouTube videos. I have one vault for my business knowledge. I have one vault for my meeting transcripts. And so I started to separate them out over time. But just to start, you could do, hey, this one's just for business or whatever you need to do. And it will help you find those relationships. And then once you've done a bunch of grillies, once you've built out these L&M wikis, then you're going to go in here and you're going to run that 3D brain skill.

And that is the one that's going to take all your knowledge and it's going to turn it into something like this. And this obviously will continue to sync and stay optimized and continue to improve for you. And it will probably build that out into something called a local host. But what's really cool is you could ask it to turn that into a site. As you can see, Codex basically lets you build things and store it on their domain.

So then after you build it, you could have it be accessible to different laptops or to your phone or whatever you want. Or if you wanted to keep it local, you can do that as well. And if you also wanted to connect your own custom domain, you can do that, too. So really, the possibilities here are endless. And it's just about doing that loop, like I said, of constantly scaling up your four C's and doing that loop of the audit level up, audit level up.

Now, the last thing I wanted to address was the whole idea of GBD6 Astra driving everything, right? Because Astra is an incredibly powerful model, but I also wanted to say so is 5.6 Soul and so is 5.6 Terra. And for the majority of this knowledge work that you're doing here in your AOS, like asking, oh, can you find this doc or can you help me create this spreadsheet? A lot of that using Astra is probably overkill. Like Astra is one of the most it is the most capable model that I've ever played with.

So what I would recommend is build out some of the stuff. You know, get familiar with how this model works. But then when you start to try to, you know, use different skills and when you start to try to connect to different things, I would recommend trying with 5.6 Soul because Astro is going to crawl through your usage limit, which is the weekly limit. It's going to eat at that more because it's a more expensive model than 5.6 Soul is.

And once you really start to get comfortable here, you can play with different things too, like the effort level. You can make it go on lights, which reduces some of the capability, but it also makes it cheaper. And then you could also go to 5.6 soul, and you could play with the effort level over here as well. There's a lot of cool things to dig into once you really start to connect a lot of stuff to your codeex system.

Once again, I just think it's important to call out that all you're building here is you're building files and folders. And what's cool about that is as you build out your files and folders, it will grow into something that's just amazing. So now I have my herk 2 which like I said has everything in here. And the cool thing is if I wanted to build a Hermes agent I can connect that to this. If I go back to cloud code I connect it to this.

Whatever is the new tool, whatever is the new AI model, I don't have to worry about switching over. I don't have to worry about being vendor locked because I own all of this stuff right here and every agent can crawl through it and use it. And that's really what we're building here. We're not just building a codec skill or a codeex hub or a little like 3D brain. We're building IP. We are building a knowledge base that is going to be the most valuable thing because now we can work through it because there's so much context and knowledge in here.

So I really want you guys to seriously get in there and start doing a bunch of grill me and just building up your routing and your context. So remember free school community linked in the description. You'll find all the resources that you need right in here. So you've got the foundation set up. Obviously like I mentioned this is never a finished product. I've been building my own AIOS for about 9 months now and every day I make a change to it.

I always make improvements. I always clean things up. And that will always just be the case. You're always going to keep improving that thing. But obviously, you can build things along the way that help you just become way more fast, way more efficient, way more powerful. And those are called skills. So, let's get into this next section where I teach you guys how to build skills better than basically anyone out there.

And this is my proven skill building and skill using method. So, let's hop right in. Today, I've got this proven six-step process for building codec skills better than 99% of people. So, let's not waste any time and just get straight into this one. All right. All right, so these are the six steps that I'm going to go over. I'm going to explain each of these and tell you why they're so important and then we're going to get into Codex and actually try some of the stuff out.

And real quick before we get started, I'm going to talk about what actually is a skill. So, if you already know what a skill is, then just go ahead and skip past this part. But for those of you who need a refresher, here we go. So, I'm going to use my chocolate chip pancake analogy. Let's say we have this chef and this chef makes the most amazing chocolate chip pancakes and you want to know how to make those. This is essentially the output that you're looking for.

The way that you would be able to copy this chef is by looking at the recipe that the chef used or the recipe that the chef made. So the chef gives you the recipe, this is you. And now you're able to pretty much make the exact same output, the really, you know, popular famous chocolate chip pancakes because you followed the recipe. So this recipe is basically the skill. This is essentially the skill.md file, which means a markdown file.

It's just a simple language. It just means that inside of the skill file there are like pound signs and asterisks to indicate like bullet points and headers and things like that. So it's it's just natural language. But then the agent is basically able to take this skill file and just use it so that if you say, "Hey, Mr. AI agent, you know, make me those chocolate chip pancakes." It wouldn't have to be like, "Okay, well, let me just do some research on how to make them, and I don't know exactly what kind of pancakes Nate wants.

I don't know how big they should be." So what I'll do is I'll just follow this skill. I'll follow the recipe. And now I get the same output that Nate's looking for and I get it consistently the same every single time because it's all documented for me right here. And these can be really simple. It can be a simple prompt like, hey, you know, help me turn this email into something that's more professional or something that sounds like me and maybe that's like my Nate email skill.

But it could also be complicated processes like doing research on the market and analyzing, you know, 50 stocks and telling you which one to buy. So really, it's whenever you want to basically like codify some sort of process that you do and so that you can delegate that process to an agent and then you turn it into a skill and now your agent can use those skills. All right, so now that that is out of the way, let's start with number one up here where we have reverse engineer.

So the whole idea with reverse engineering your skills is basically that you want to start with an output. You want to start with what is the definition of done? What are you actually looking for? Because let's say you ask your agent here for chicken, for example, and you actually want like chicken parmesan on a bed of pasta, but because you just said chicken, the agent might interpret that a little bit differently and make you a chicken sandwich.

And then next time you ask for chicken, it might make you, you know, chicken thighs. It doesn't actually know specifically what you want. So if you start with an output and you have, you know, essentially this chicken parmesan and you say, "Okay, let's reverse engineer this food and see what went into it, how long we cooked it, how did we get here?" And that's how you build the recipe. So, for example, if you wanted to build a skill for the end of the week report, you've got certain columns in your Excel sheet.

You've got certain calculations that were made. It's way easier to give the agent that Excel sheet to give it the final deliverable and say, "Hey, this is an output that is really good and this is what I want to build a skill for so that you understand how to take some raw input and turn it into this output that I have already told you that I like and this is what we're looking for every time." And then it can basically walk you backwards through that process.

Okay, what data did you look at? where did you get it from? How did you calculate it? Where did you format it? You answer those questions and then you have a version of a skill that already knows sort of like the north star that it's building towards. I think it's so much easier to run the process, get the output and say, "Okay, let's turn that into a skill." Rather than saying, "Hey, build me a skill for building a YouTube dashboard." And then you might have this vision and your agent might have a completely different vision and then you're going to get frustrated when it delivers you a chicken sandwich and you actually wanted chicken parm.

Now remember, all of these concepts I'm going to, you know, bring back together when we actually hop into Codex and I show you some stuff. But let's just keep moving down the list because I think this foundation is important. So number two, we have one specific job and one specific trigger. So remember how I said that these skills are markdown files. Skill.md. What happens in the skill.md is you've got a YAML description.

It's called YAML front matter. And then you've got the actual skill instructions, which is the meat of the skill. So right here is one of the skills that I'm going to keep coming back to in this video because it's it's one of my favorite skills. And you can see up here this metadata, this is the YAML front matter. So if I view the source, it looks like this. It's actually just separated by these three dashes. So this would be the YAML front matter.

And then everything below it would be the actual instructions of the skill. Now this is markdown. And when I said markdown is very simple. It is. You can see here are two pound signs. And that just indicates a header. We can see that we've got these little dashes which are bullet points. And so when markdown is actually rendered, it looks more something like this. And you can see it's just formatted better. So this is the way that I like to look at it.

But if you click on view source inside of the Codex app, you can see the raw markdown file. But anyways, the metadata up here is the YAML front matter and that tells us what is the name of the skill and when do you explicitly use it. And there are other fields that can be populated in here like in this one we have an argument hint. And basically this X article skill is used when I ask my agent to turn an YouTube video into a long form X post.

And so sometimes it'll feed in this argument which is my YouTube video URL that it will take, it will download, it will transcribe it, it will take screenshots of it, all that sort of, you know, all the stuff. And then once the agent has basically said, "Okay, cool. Nate wants to turn this YouTube video into an X article. So, okay, cool. I found this skill that I need to use. Now that I know this is the skill I'm going to invoke, let me read the entire description of the skill.

So now I understand exactly what to actually do." And you can see this skill is pretty long. There's a lot of instructions in here. And this wasn't like me on one try turning this into a skill. This is probably a skill that's been iterated on 25 or more times. And we'll talk more about that in a bit. But the whole idea is that you want a skill to do one very specific job. You don't want to have a skill that's like run the marketing team.

You want to have a skill that breaks that marketing team, all of those processes into individual steps. So in my book right up here, becoming AI native, I talk about this and I call it the function breakdown. I call it the the tree. Basically, your job is a tree and you've got different trunks with different like, you know, bullet points in your job description and then each of those trunks have branches and each of those branches have ultimately leaves and you want to turn all of those little leaves or those little tasks into skills because you can chain skills together over time.

But the point being, if you have a skill with one very specific job, you can give it one very specific trigger, which means that your agents are going to be able to execute them more consistently, invoke them automatically. It just helps you separate out what your agents are doing in a much better way than if you have a skill that's like 30 pages long and it's supposed to do so many different things. So think about breaking down processes at the task level and turning each of those tasks into skills.

All right, moving on to number three. We have thinking about the freedom level. So what I mean by this is when you're automating things, you basically have to figure out is this a deterministic automation or a non-deterministic automation? Basically, is this something that's predictable and we know exactly what comes in and we know exactly what happens and we know exactly what comes out or is it more of a non-deterministic AI agent, more of a nondeterministic black box where we know sort of what the input's going to look like.

We sort of know what's going to happen inside the process, but we do kind of know like what the output should be. We still know the definition of good and the definition of done. You can think about it like, can I automate this using rules? Hard rules, hard logic. Is x greater than 10? Is x equal to 500? or is it something that needs a lot of judgment? Analyze this. Turn this into an email. Turn this into a spreadsheet.

And it's really important to think about where does your skill live on that spectrum? Because if you have a very deterministic skill, like for example, it just has to take a Excel sheet and it just has to populate the cells into the CRM or something and that's basically just data processing transferring. That's a very deterministic process. And if you write the skill in a very nondeterministic way, there's a lot more room for error.

There's a lot more room for AI to interpret something wrong and do something wrong. And that's the case where you want the skill to be like step one do this, step two, do this. Exactly, exactly. Exactly. Do this. It's very specific. But if you've got something nondeterministic, like for example, my X article skill, we don't want to be so specific. We want the AI to be able to use its judgment and to be able to use research and thinking to generate a unique output because every YouTube video is different, which means every X article is going to be different, which means all the screenshots that it needs to take are going to be different.

I couldn't say something like screenshot the video at the 1 minute mark and then the two-minute mark and then the 5minute mark and put those into the article at line 400, line 600, line 700 because then the articles would come out feeling generic and they probably wouldn't even make sense and it just wouldn't be a very good output. So think about the freedom level of the process and when you're doing this manually, do you follow the same set of instructions every time or are you constantly using judgment and are you constantly doing different things within the process to ultimately get to that definition of good?

By the way, guys, I've got this completely free SOP for you about getting your first a automation client. It's going to go over the exact steps that has been proven for hundreds of our AIS Plus members to get their first paid gigs. It goes over the one sentence service pitch that can get you started today, why your first client should cost you money, the 5-minute video that answers, can this person actually deliver before you've actually received any money, what to do when you have zero case studies.

There's so many good things in here that are going to help you out. Even if you already do have clients, I would recommend grabbing this because, like I said, it's yours completely free. So, if you want to grab this, there's a link for it down in the description. Let's get back to the video. All right, moving on to number four, we have verification. And this is probably the most important piece of building skills. So, the whole idea of building a skill is that now you can trust that your agent's going to give you an output more consistently that meets your standard.

But what you want to do in there is you don't want to be constantly being handed the agents V1. You want to be handed an output that's already good to go that you can give it a quick skim, approve it all, and then shoot it off. And the cool thing about agents building stuff to ultimately achieve some sort of northstar is that you can also have agents check its own work, verify its own work, or you know, other agents verify different agents work.

So every single skill that I build works in some sort of verification loop, meaning the agent who builds the thing, delivers this output, and then we either have the same agent or different sub agents come in and verify that output and then provide feedback. And this verification loop can go on multiple times. Sometimes it's just, hey, here's the V2 and it's approved. Here's the V7. I've even had agents verify over and over and give me like a V15 or 16.

And that basically just ensures that your time isn't being wasted verifying and sending feedback when you can have agents do that for you. Now, when it comes to verification, there is a difference between objective checks and subjective checks. So, let me explain what I mean by that. An objective check is something that can literally be proven. Sort of like the non-deterministic versus deterministic thing. Objective means okay um I wanted you to do research and then the verification was to pull in 500 sources cut that down to the best 250 and then every single fact that's in the article I want that to be double checked by second agent and that's objective we can literally prove 500 sources cut down to 250 every single fact double checked by a different agent that's objective that is a rule does x equal y is a greater than b but then you have some things that are subjective like verifying the video right if it's it's creating a video for you or if it's creating a website for you.

A lot of these subjective checks are more like, oh, you know, does everything look good? Is everything inbounds? Is it loading in a certain way? When you don't have an actual hard metric to align it to, you have to sort of be a little bit more subjective on your verification. And what you're thinking about doing is turning that agent into an LLM as a judge, which basically means, okay, so if AI is going to be applying its approval, and it has to use judgment to approve, then how can you tell the agent exactly what you're looking for?

What does good typically look like or feel like even though there's not a hard rule? So, for example, with the X article skill, I've got some objective checks in there, like there are 10 screenshots from the video. But then there's other subjective checks like how do you make it flow in a way that makes sense? How do you make it sound like Nate? How do you make sure that the images that are put into the the article, the screenshots, are cropped?

There's other subjective checks that we have to let it do things where it like opens up the app and it scrolls through and it reads through and it screenshots and it verifies. But a lot of those checks, like I said, are more subjective. And so that's where iterating on these skills takes a lot of time because you're constantly running the skill, analyzing the output, giving feedback, running the skill again, analyzing the output, giving feedback.

And you're basically just like training the skill where every single time you use it, it gets better. But the thing about verification is there's always a way. You might be thinking to yourself, well, I don't really know how I would have agents verify that process. Agents can do anything. They can use your computer. They can use your browser. They can look at things. They can listen to things. They can do anything. So just think about it like this.

If you assigned that task to a human, what would you do to basically give it the stamp of approval? And then just explain that to the agent and that's your verification. That doesn't mean it's going to always come out 100%, but it's going to be more like 95% rather than giving you something that started off at like 75 or 80. Okay. And moving on to number five, we've got walk it down. And when I say walk it down, I mean walking it down the model list.

So whether you're using Cloud Code or Codeex, we all know that different models have different strengths. And we all know that models that have the strongest strengths are the most expensive. So for example, Astra is more expensive than Soul, but more capable than Soul. Soul is more expensive than Terra, but more capable than Terra. So the idea is you build a skill and you're getting this good output. And maybe you were testing that with Astra.

Okay, well let's run that same skill on Soul. Are we getting the same result? If we're getting the same result and it's cheaper, okay, let's test it on Terra now. Are we getting the same result? Is it cheaper? Okay, let's test it on Luna. There's no reason to be running a skill with Astra if you could run it with Luna and get the exact same output. But it is important to test it because not every skill fits that. I've had some skills where I run them on Haiku or Luna because they're just super simple.

For example, when I give my agent a YouTube video and I say, "Hey, I need a YouTube video description and timestamps that I can do with Luna, and doing it with Astra is overkill. But for this ex article thing, I typically like to use at least Soul or Astra because it just has a better understanding of screenshotting things and putting it in the right spot and cropping it down and even blurring things out. It's so much better with the browser use with Soul and Astra.

And then once you've landed on a model that you like, you can take that one step further and you can walk it down the effort level. So start it off on maybe high and if it's not good enough, then move it up a little bit. And if it is good, then move it down to medium and just keep finding basically the simplest model or the lightest and cheapest model that still executes at the level of quality that you're looking for.

And then moving on here to number six, we have the bike method, which is I've kind of already alluded to it multiple times throughout this video so far, but really it's just the idea to me that your skill is never done. Every single time you run the skill, you're going to improve it. You're going to say, "Hey, here's what I really liked. Here's what I didn't like. Update the skill so that next time it's better." Almost every single time I run a skill, I give it feedback and I tell it to update.

And if you think about this, like you're teaching a kid to ride a bike, that's what a skill really should feel like. You start off very cautious. You're watching everything. You're guiding them. You you've got your hand on the the the steering wheel. Steering wheel, I meant like handlebars. And you're you're right there. And then what happens is you give feedback. You say like, "Okay, that was good, but you know, you were leaning a bit too far to the left.

Make sure your weight's more in the center." And then you keep going. Eventually, you take off the training wheels because the skill is getting better and you're getting more trust in the skill. and then you give more feedback again and then eventually you take off the elbow pads, right? And then you keep giving feedback. But that doesn't mean that you just take off the kid's helmet and let them bike on the highway. You're not going to do something reckless like that.

You're also not just going to shoot them off down the road and then go inside and take a nap. You're still going to be in in some way watching or having certain guardrails in place in order to make you feel comfortable and in order for you to have more trust in the actual skill itself. And I truly believe in the idea that there's no such thing as a finished product unless your skill is super super deterministic and it runs perfect every time and you don't have to worry about it.

But when the skills are more on the judgment side of the spectrum, you know, as we talked about up here, the more your skills live over here, the less I believe that you can actually have a finished skill because like I said, every time things might happen a little bit differently and every time your process might change or new models might drop and you're just constantly going to be giving feedback every time you use it.

Okay, so let's hop into Codeex here and we can take a look at how this actually works. Now when you are inside of your project and if you're inside of your AIOS which is usually what I'm building in the codec skills will live in a folder called the aagents and then inside of the aagents there's a skill or sorry not a skill there's another folder calledskills and if you're doing this in cloud code the skills live in aclaude and then in a folder called skills now these can be transferable I basically just tell codeex or claude hey see all the skills in there and bring them over here too so just I have duplicates of them but that's where they actually live inside of your um project unless you have them at a global level which just means they're living locally across all of your codeex projects rather than just inside of your AOS.

So that's where they live and you can always just say hey you know Codex I have this skill I don't remember where it is could you show me the file path and it will find it and you can move it if you want but anyways that's where they live and you can see I actually just ran this ex article skill on a video so it says your ex article draft is saved. I'll click into it and I actually did obviously already publish this one but I didn't even have to change anything.

I basically just clicked in here. I read it all and I published it. And you can see that as it's going through, it already formatted everything and it used the video. Of course, it took screenshots of things and it like put them in the right spot to line up with what was actually being said in the article. And it even added this little um I don't know what you want to call it, like a spotlight. It added that. I didn't actually do that, but it will basically crop things out and it will add things like that into my actual article because I've told it in the skill to do things like that.

And you can see that for this specific video, this ran on GBD6 Astra. So, what I'm going to do real quick is I'm going to walk this down. I'm going to give this same prompt to Soul and Terra and tell it to make the X article and it's going to use the skill. And we'll see how those outputs compare to Astra's output because this is a pretty complex skill. It has to transcribe the video. It has to open up the article. It has to make the thumbnail.

It has to format everything and it has to screenshot everything and put it in and then actually like drag it around. So there's a lot of browser use and there is a ton of judgment inside of this. Like I said, this is not a deterministic skill. So you can see right now I have Soul, Terra, and Luna all running. It's been about 10 minutes, so I'll just check with you guys when this is done. But I just wanted to show you how all of them because of the skill, because of the verification, are viewing images.

You can see how many times Luna has viewed these images here because it's taking screenshots and it's trying to understand, okay, which of these should be worked into the article and where and why. Same thing down here with Soul. Obviously, this one is a super super visualheavy sort of skill, but because I've worked that in there, all of them are viewing images no matter what. And so, it'll be really interesting to see how they decide to place them and, you know, what images they actually choose to put in there because X limits you to a certain amount of images per article.

So, I'm going to let these run. We'll compare the results and we'll kind of talk about how walking it down has changed my perspective on this specific skill. All right, so you can see now that we have Luna and Terra have finished up. Soul is still working. So, we'll start reviewing these two and then we'll hop over to Soul. Hopefully, it'll be done by the time we're looking through these. So, Luna took 28 minutes and 33 seconds.

Let's open up the draft and see what we are working with. So, we have um the thumbnail in there. We have I designed a one person million-dollar business with Claude. Um the title is the same as like the opening line, which I don't love. There's also this weird spacing was right there. I don't know if it tried to like center it, but I do notice that. Anyways, we have sort of like the TLDDR. We have these different headers here.

I'm yet to see an image. Here comes the first screenshot. So, this is talking about um the three different types of ideas to compare. And in the screenshot, we do see all three. So, that matches up pretty well. Um we see agent report card as well as down here. So, really what I'm checking for right now is that it all sounds like me. So, this is kind of trained on like my LinkedIn style guide and my YouTube style guide and like the way that I speak, but I'm also making sure that the images look good.

So, the test suite is a golden data set. We know what the correct answer or correct action should be. And we see an evaluation right here. The first run scored 88. That's what we see. Um, approved the new policy. Same 16 tests. Ran it again. That looks decent. I clicked create report and we don't really see the report here. So, that's a little bit off, I would say, but it's not too bad. I'm actually impressed that Luna is doing it this well.

This is customer support. This is kind of just the home dashboard. And then down here we see searching for companies using clay. It did do a nice little spotlight animation here when we're looking at the actual pricing. And then we've got the three Ps down here. Okay, so this is not too bad. We'll have to compare, but I would say that I was impressed by Luna's ability to screenshot, add spotlights, put it in the right spots.

So that is Luna. That also took 28 minutes and 30 seconds. Okay, so we have Terara. And by the way, all of these are running on high. So we have Terara here. took 26 minutes. So about 2 minutes, 2 and a half minutes faster than Luna. Let's open up this draft. See what we got. So same exact um thumbnail. We have an image right away. How I built a $1 million AI business model with Claude. This image isn't great. Like to start off the article like that, that's not a very strong way to start it off cuz it looks like it's cut off like that.

So that's bad. Um we go through the three filters. Oage doesn't look very good either. I would already say right now that um Luna did a better job. I mean, this isn't a bad Also, this is a zoomed in. So, it took a screenshot of the video and then it zoomed in on the score going from 88 to 94. So, that's not terrible. Read complaint check company fit recommend small trial. What you'll notice here is it actually, if I can open this up, it redacted sensitive details.

So, it put this block over it and said sensitive details redacted. So, I think that that's pretty cool. I like when it does things like that. It did a little spotlight effect here. It redacted more sensitive details in this one. As you can see, it did it again here. So, it's it did it again here. It It shows so many times when it needed to redact sensitive details. It did it again. It did it again. Okay, but this is obviously an issue.

It didn't verify this good enough. Like, you can see that there's literally four images in a row down here. This one looks bad. I think that, you know, you you you have to use the browser to like drag these around. And I think that it just gave up or it stopped and thought it was done. So, so far I would say that Luna did a better job than Terara. And Terra was, you know, it's a more capable model apparently than Luna.

It's also more expensive. So, right now, if I was choosing between these, I would choose Luna. But now, Soul just finished up and Soul took 38 minutes. So, normally when I do run this, I run this on Astra. I usually run this on Astra low, and I run it on fast mode to get it done faster. But, let's see. This did it. Let me open this up. Okay, so here is uh Soul's version. I built a $1 million business with Claude. We have the same sort of like TLDDR, the three filters.

We have a picture of the three filters right here. So, that's not bad. Choosing the product. Okay, it's zoomed in here. These are all zoomed in, by the way. So, it's it's it's using more, I guess, vision intelligence to choose what to actually display in the image. You can see it redacted here the demo receipt. So, not too bad. It zoomed in a little bit here on the report, although we don't see the score 88. What it what it highlighted here was 14 tests pass and two failed instead of showing us the 88.

So, just pointing that out. It also zoomed in down here on some analysis of that report. It did a little spotlight effect here to show the 94. It redacted more of these receipts. It did another spotlight here. It shows sales and support without losing control. So, that's not terrible. We've got this customer support image as well. We've got more internal source ID redacted. Another spotlight effect on the money. And yeah, so this one isn't too bad either.

I would say honestly like I'm wondering if Luna's was better. And that's the thing, like these are so different and sometimes I have tutorial