How I Get Fable 5 Level Autonomy with Any Model Using AI Harness Engineering
Jordan Urbs · 2026-06-23 · 35м 5с · 63 775 просмотров · YouTube ↗
Топики: ai-loop-engineering
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model=deepseek-v4-flash · prompt=summary-v7 · 10 185→3 042 tokens · 2026-07-20 11:54:50
🎯 Главная суть
Агентская обвязка (harness) — это программная инфраструктура (тело), которая позволяет любому LLM выполнять длительные автономные задачи. Модель (мозг) арендуется и может исчезнуть (как Fable 5), но обвязка остаётся вашей и может работать с любой моделью — от GPT до опенсорсных. Владение обвязкой даёт суверенитет: вы не зависите от компаний и правительств, которые могут отозвать модель.
Что такое агентская обвязка и как она работает
Агент — это модель плюс обвязка. Модель читает промпт, выбирает инструмент, запускает его, проверяет результат и решает, закончено ли. Обвязка даёт телу «руки и пальцы»: доступ к инструментам (терминал, API, MCP), системы верификации, память о выполненных шагах и механизмы определения завершённости. Без обвязки модель остаётся просто чат-ботом, неспособным ничего сделать.
Внутри обвязки могут работать несколько агентов-подчинённых, каждый со своим контекстным окном. Основной агент-оркестратор вызывает подходящего под-агента, даёт ему чистый контекст и получает результат. Это предотвращает засорение основного окна и повышает качество.
Проблема арендованной модели: Fable 5 и три урока
Fable 5 была выдающейся моделью из-за того, как она работала с Claude Code — обвязкой от Anthropic. Модель исчезла («policy pull»), но Opus 4.8 могла бы сделать ту же работу, если бы была правильная обвязка. Две ключевые проблемы:
- Модель арендована. Вы не владеете ей, и доступ может быть прекращён (правительство, компания).
- Нет рычагов. Если обвязка встроена в модель (как у Fable), вы теряете всё сразу.
Решение: строить обвязки с помощью передовых моделей (Opus, GPT, Gemini), а затем выполнять с опенсорс-моделями. Так вы экономите деньги, получаете приватность и сохраняете качество — обвязка уже хороша.
Компоненты обвязки на примере рабочего пространства Jordan Urbs
Обвязка — это папка проекта, содержащая:
- Базу знаний (knowledge base) — все документы о бренде: голос, тон, фреймворки, глоссарий.
- Папку
.claudeс:- Агентами — системные промпты для каждой роли (блог-райтер, контент-идеатор, ревьюер голоса).
- Навыками (skills) — инструкции, как писать в стиле бренда («стоп слоп», «голос Джордана»).
- Командами (commands) — готовые сценарии (например, «переупаковать транскрипт в полный пакет контента»).
- Claude MD — файл с мета-контекстом, который загружается при старте и говорит агенту, где искать навыки, команды, какую структуру использовать.
При старте агент читает только Claude MD, а не все документы — это экономит токены и качество.
Пример работы: автоматическая переупаковка контента бренда
Обвязка для переупаковки видео-транскриптов в полный контент-пакет. Агент-оркестратор последовательно вызывает:
- Райтер тредов — пишет X-тред на основе транскрипта.
- Ревьюер голоса — проверяет соответствие бренд-гайдлайнам, используя навык «стоп слоп».
- Генератор изображений — создаёт картинки в дизайн-системе бренда.
- Ньюслеттер-райтер — пишет draft для ConvertKit.
- Блог-райтер — создаёт пост для сайта.
Каждый под-агент работает в свежем контексте. После завершения обвязка выдаёт готовый набор: Substack draft, X-тред с изображениями, блог-пост, email-рассылку, метаданные для YouTube. Вся цепочка заняла около 37 минут без участия человека.
Пример самостоятельной сборки: каталог Sovereignty Atlas
После потери Fable 5 автор решил построить обвязку для своего каталога sovereignatlas.com — сайта с 240 листингами. Он открыл новый сеанс Claude Code, включил план-режим и попросил: «Давай построим обвязку для повторяющихся задач — добавление новых FAQ, страниц, рефреш исследований». Модель предложила структуру: команды (/add-listing, /seed-faq, /refresh-research), агенты (исследователь, SEO-аудитор, ревьюер) и автоматические проверки качества.
После сборки обвязка запустилась полностью автономно: провела конкурентное исследование, написала 2 руководства (Homesteading, Libertarian), добавила FAQ к листингам, проверила исторические утверждения на достоверность и потребовала источники там, где утверждения были непроверенными. Всё заняло около 22 минут — без участия человека, кроме финального утверждения.
Как построить обвязку самому
Проще всего скопировать готовый шаблон — например, Safe Agentic Workflow от Scott Graham (Cheddar Fox). Он содержит 11 агентов для разработки софта, но может быть адаптирован под любую задачу. Скопируйте URL шаблона (см. описание видео) и в своём IDE (Claude Code, Cursor) скажите: «Давай построим обвязку на основе этого шаблона, хочу делать X». Или просто попросите модель: «Построй обвязку для таких-то задач». В режиме плана она сама предложит структуру, агентов, команды, навыки.
Работать обвязка может с любым LLM — от Opus до локальной опенсорс-модели. Для сборки лучше использовать передовые модели (качество выше), для выполнения — опенсорс (дешевле, приватнее).
Автономность и контроль качества
Обвязка может быть полностью автономной: она не только генерирует контент, но и проверяет его через специального агента-ревьюера. В примере с Sovereignty Atlas агент-ревьюер нашёл необоснованные исторические утверждения и заставил предыдущего агента добавить источники. Это снижает количество ошибок и делает возможной работу без человеческого глаза, хотя автор рекомендует всё же просматривать финальный результат.
Итог: модель арендована, обвязка — ваша
Мозг (модель) можно менять, тело (обвязка) остаётся у вас. Строить обвязки нужно на передовых моделях, но запускать можно на опенсорсе. Это превращает разовую работу в автоматизированный конвейер, который не зависит от капризов рынка ИИ. Вы перестаёте гоняться за новыми моделями и получаете долговечный актив — инструмент, масштабирующий любую деятельность.
📜 Transcript
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We all know Fable 5 was one heck of a model. Then it got pulled. But if you know how to build a system that makes any LLM perform at that level, then you'll never have to worry about chasing the next big AI breakthrough or a company or government rug pulling you ever again. And that's what I'm going to share with you in this video. What an agentic harness is, how they work, and how to get started building your own so you can get long horizon creative autonomy without Fable 5. Plug in any model you want. so in this video i'm going to introduce you to what an agentic harness is i'm going to show you one of mine in action right now and then we're going to build one on our own using a template or simply prompting our AI to do it. And they'll give you some more tips on getting started. Before we begin, I just want to encourage you to hit that subscribe button because this type of sovereign AI usage, like the real foundations of AI, is what I like to explore on this channel. I don't think anyone should be dependent on the shiny objects, the next big hyped tool out there, the next big hyped model. We should know how to use this intelligence. from the ground up so when the rug gets inevitably pulled out from under us and we lose the best model ever we're not completely screwed Just a few hours before Fable was pulled, I built a 240 listing directory. Fable came up with the SEO, AEO strategy. It scraped the whole web and it created the entire architecture and infrastructure of this sovereign individual-minded directory. It categorized things. It made an llms.txt. It rendered the whole thing with Astro. And it was just a really impressive result. So I got really excited about Fable. And then Fable was pulled and builders, including myself were really bummed because it did such a good job at long horizon autonomous work but the truth is we don't actually need fable to do long horizon autonomous work opus other models are all intelligent enough what you need is a good harness An agentic harness is the rig that keeps the building loop for an AI going. When you know how to build your own harnesses, you're not going to be as vulnerable to the rug pulls that might happen due to a government or a company or whatever it might be next. So in this video, I'm going to show you all about agentic harnesses, how they work, and then we're going to set one up to keep building my directory for the next steps because I can't use Fable anymore. So let's talk about the loop. Now, what an AI is going to do when it's building an agent, it's going to read what the prompt is, it's going to pick a tool, it's going to run the tool, it's going to check it, and then it's going to find out if it's done or not, and then it's either going to start over or move on to the next thing. That is what the AI agent loop looks like. Okay, so let's unpack that. You have AI, the intelligence, the LLM, that is the brain. Okay, that's here in the middle. But the harness itself... is going to be the body the fingers the arms what it needs to actually get stuff done that actually is good so you have the context which is like a knowledge base you have the tools which might be mcps or using the terminal the harness has systems for verifying that the work is good it has systems for determining if the work is done or not and then it has a memory like what actually happened and what needs to be next so In essence, an AI agent is really a model plus a harness. And this is really important to remember, in my opinion, because Fable was the model, okay? The reason Fable was so freaking good, because the Cloud Code or Cloud App is the harness that makes the agent so freaking good. So when you don't have Fable anymore, what do we do? Don't fret, because we can create this on our own, and in some cases, even make it better. So a good harness can run with any model. You can run it with GPT, you can run it with Gemini, you can run it with Claude, and perhaps most importantly, you can run it with open source models. The model is probably not going to be run on your local machine, though it might be able to. Especially maybe a year from now, it might be completely normal that we run harnesses on our machine. I've been using Goose a bit with local models and Odysseus, and we're getting to a point where this is going to be a thing. But for now, what's important to understand is that while we're renting the intelligence, probably, we can own the harness. And I'll also call it a rig in this video, because that's what we call the A-Captain's Academy. You can own the rig, which is like the software, the body, the robot that you can plug the intelligence into. And if you can own that, then you're not as fucked when the government tells Anthropic to shut down its model. Okay, so let's address the two problems with letting the model itself hide inside the harness, which isn't exactly what Fable was, but for sake of the metaphor here, let's go with it. Problem number one is you rented it. So perhaps it's not Fable 5's intelligence that made it so impressive. Obviously, Opus 4.8 could have made that directory, but the harness, Claude Code, which Fable 5 was designed to really use and maximize, was the body for Fable. So Opus can still use Claude code, it's just not going to be as good with it unless you set it up to be as good as it can be, which we're going to do later. So imagine the harness lived inside a Fable, you rented all that. So if it's no longer available, it's gone. Problem number two is you have no leverage when it's not yours. And this is the main point I'm trying to drive home here. Is you want to know how to build these things to plug in any model, whether it's local, remote, whatever. So then the next time a big black swan event happens, you're not screwed over. I'm just going to keep saying that. The agentic harness is your ticket to running powerful AIs without worrying about where the intelligence is coming from. In a previous video, I mentioned Odysseus. That is a great workspace. It's not quite a harness in the same sense we're talking about. here here we're talking about being able to one-shot entire projects long horizon autonomous creative work so you can build the harness yourself and then run it with pretty much any model now an agent like i mentioned is essentially a model plus a harness you can still plug weaker brain into a great harness and it'll still ship and it'll still do a pretty good job the better your harnesses you could have a genius brain but no harness and it's still just gonna be a chat bot it's not gonna do anything it needs to have the agentic capabilities to do stuff so to me this is like the elephant in the room fable 5 was amazing because have how it works with cloud code So what I've been saying for a long time in the AI Captain's Academy is you want to build your tools, your workflows, your pipelines, your harnesses with frontier models and then execute with open source. Why? Because with the frontier models, Opus, GPT, Gemini, it's going to cost more, but it's going to do a great job. Even in Odysseus, you have teacher mode, which will call a frontier model to create a skill or procedure that the open source model just doesn't do well. But then... Once you've got a quality harness built by the Frontier models, not only is it yours, but now you can run cheaper, more economical, open source models, either local or remote, and get better privacy, and save money, and get really good results. Because the harness is really good. I use the Venice API for my harnesses because I can call frontier models and I can call open source models and I can choose for which task am I going to need which model for either saving money or making sure I get the best performance possible for that specific task. So what this means in essence is AI writes the code now. It makes the things for you. You just say what you want. Your job has moved up. You are now the strategizer. You are the director. The AI does the labor. The rig itself, the harness, is what you need to make sure that labor produces consistently. You want good quality. You want to make sure you don't have to babysit it. Once you get these harnesses created, you plug in whatever the input is, in my case, like a transcript. So let's dive into what it means to build a rig from scratch, okay? You don't really need to start one from scratch. You could. cloud code and codecs know how to do it but i actually recommend stealing a good one so this is from cheddar fox scott graham who was on the channel a while back to introduce these and changed my whole life learning about these so this is the safe agentic workflow this is for development and we're not going to need something for all cases that is this crazy but you could use a harness like this to build software. This is the scaled agile framework methodology adapted for AI agent teams. You could use it for any kind of team. So let's explore what that actually means. So what happens in the harness is you have multiple agents in a team. In this case, you have 11 agents. They all do different things. They all have skills. They all are triggered based on hooks or the main orchestrator agent calling them. Now, I am not a full-on developer or whatever, so I'm not going to get too deep into this because I'm not the person to be able to do that. But just imagine you have all these skilled agents on your team that know what they're doing and have a full fresh context window to do it. Here's an example of a harness I'm running right now inside Cloud Code. this is inside my brand knowledge base and it's already been running for seven and a half minutes maybe not too long but it's got a bunch of phases here where it takes a transcript from a video or conversation and turns it into all kinds of content it makes images it makes a substack draft it makes a convertkit draft it reviews it all it does everything it calls different models to do that like it uses opus to write but then uses gpt 5.5 to review what was written and make sure it fits all the brand guidelines and then it makes videos which you're going to see in this video. Anyway, this is a harness here and this just goes on for as long as it needs to and it creates whatever I set it up to create. You don't have to be a developer or a fancy engineer person to be able to use something like this. At the end of this video, we'll jump into an actual template on GitHub that you can use to get started and I'll show you some specific templates that help with certain tasks and how to build your own. Okay, so let's go back here. I accidentally closed it. Whoops. It was at about 21, 22 minutes. So it's going to keep going now. It's going to start over. But anyway, if I hadn't closed it by accident, we'd be at over 22 minutes now without needing any input by me. so actually this is actually a good example here send message isn't available as a tool here i'll spawn a fresh agent for the cycle for the next part of wherever it's at it needs to use the send message tool but the main agent can't do it it has to spawn a new agent that does get access to that tool if we want to see everything it spawned this sub-agent that says okay you are the repurposed threads agent revision cycle two on the standalone tweets only so read this file and then reread the skills thread writer voice standard and stop slop and make sure that it's good basically so it's got its constraints here it has its job okay so let's back up what just happened here is In my workspace, the Jordan Erbs brand workspace, we have my knowledge base, which says everything about basically who you are, who I'm making videos and content for, how I talk about things, my glossary, sovereignpreneur, the sovereignty ladder, which you saw in the directory, my brand positioning, what is my brand, who do I speak to, what am I... writing about the thesis, my voice and tone. Anyway, so all of this stuff, my frameworks, everything about my brand is here, as well as my sub projects, as well as my domain. So whenever I open up an agent in this folder, I can literally just say like, hey, update my website with this. And it has everything it needs and it knows what to do. So that's part number one. That's the context, my knowledge base. That is a crucial part of a solid harness and AI agent. It needs to have its knowledge base. Then comes the dot cloud folder. Inside the dot cloud folder is where we're going to see, okay, these agents being spawned. In here we see we have our main agents, blog writer, content ideator, and then this is like their system prompt. Content ideator, you generate content ideas for the sovereign prenewer brand across all formats and map them to the four tier sovereignty stack. First, read the thesis, then read the four tiers, then read the positioning document. Okay, so it says here's all the things you need to do to catch up. on the knowledge, here's what you gotta do. But in this case, we're in the content folder, this one. And so we have another .cloud folder, which says agents repurpose threads. So this agent produces X content from a transcript analysis. And here we are in there. So in my main folder, it's got my agent system prompts. And then in my actual content repurposing folder, it's got its agent system prompts. Then you have the skills. So we have the newsletter writer skill. that knows how to write like me and says, hey, check out the voice and tone document to write like Jordan. It's got the stop slop skill. Props to Hardik Panja on GitHub for creating this. Like, hey, make sure it doesn't look like AI, basically. And it's just got the skills that are needed for that workspace. And then here we have no skills at all, actually, in content because it's actually pulling the skills from here. But we do have commands. So the repurpose command, repurpose a transcript into a full Jordan Urbs brand content package. So this is basically what the whole orchestrator agent is following in this harness workflow. And that's what keeps it on track here. But this is the beginnings of a harness. You have the agents, you have the skills inside a workspace. And then in the safe agentic workflow, you'll also have hooks. commands, agents, skills, and even a Claude MD. So we didn't talk about Claude MD. It's also called Agents MD in cursor. But essentially, the Claude MD here gives the context for the conversation to your main agent. So in our case, Claude MD, this is the Jordan Herbs brand workspace. So when I start Claude here, it automatically says, hey, this is the Jordan Herbs brand workspace. Open this folder when working on anything related to the brand. And so it knows what all the folders are. And it just has to read this file, visual generation workflow, plain language standard, voice rules. It starts here, so it doesn't actually have to load every single file. It already knows here in the beginning, hey, when you're looking for brand specific skills, go here. When you're looking for the content repurposing harness, open up this. And that is how this main agent when Cloud Code is opened on the command line here in VS Code, will automatically know, okay, Jordan provided a transcript, so let's run the multi-format content repurposing harness. And that's exactly what's going on here. And like I mentioned earlier, we're at 21 minutes. We're now approaching 30 minutes here with no interaction from me, aside from when I closed it by accident. And it is just running its thing. And it's got code it runs. It's got skills it touches. It does all kinds of stuff, like imagegen.shell. This is a script here. Let's look at the prompt. Yeah, this is the prompt with my colors based on the brand, which is here in Jordan Herbs KB. We see it here in design, design system. There's the Jordaner's visual design system. And so this whole harness knows where to look for all the data without having to overwhelm a single agent. Because if one agent were to load all these documents, it would take hundreds of thousands of tokens. And you only have a million token context limit, and your quality gets worse the more tokens that are used. So instead, the main agent only loads what it needs to, if it needs to. And otherwise, we'll spawn an agent, give it the agent system prompt, like, hey, you're the context. ideator start doing this here's what you do and here are the documents you're going to need so in this case the content ideator is going to need to read the thesis file the sovereignty stack file the positioning file the glossary file the ideation protocols which is all quite a bit but at least it takes place in a sub-agent conversation a fresh new context window so it doesn't have to clog up the main one because the main one is just making sure we get everything high quality So then after that whatever agent, let's say in this case we have the image generator agent, whatever it's called in here, generating the assets, then another agent's going to come through. Let's say, for example, the thread was written, then the voice reviewer agent is going to come through in a new conversation, doesn't know anything about the past, and the main agent says, hey, here's your system prompt, you're the voice reviewer. First steps, check out the voice standard skill, the stop-slop skill, the messaging document. voice and tone. So learn everything about Jordan's brand, how you write, how to not write. And then you're going to check what was written by the last sub agent in a conversation you have no idea about, you have no context of. You're going to check that out and you're going to make sure it's good. And then here is the return format. You're going to give a report. Then that report goes back to the main agent and the main agent determines, okay, do we go on or not? And that brings us back to the loop. Read, pick tool, run, check. Are we done? Yes or no? And then it just keeps going. So essentially every sub-agent is running in this loop in some way, shape, or form. We're running everything right now to Cloud Code in Opus. But the great part is once this is built, and the same thing with this here, I can open this folder. in open code using an open source model here via venice and i can run the same workflow and it will do pretty much the same job just with a different intelligence model behind it so if cloud code ever rugs me and i can't use opus anymore or whatever i have a rig that i can just plug in my custom intelligence to so the model yes is rented but the rig itself the harness is owned this is the sovereignty filter i like to call it it's in the framework in my knowledge base you can Swap the brain, but keep the body. You own the body. You are the sovereignpreneur here. So now is the time I'm gonna give you a CTA in the AI Captain's Academy. We have a bunch of agentic harnesses for solopreneurs to kickstart your next venture, especially if you're trying to sell AI. So for example, this is a lead getter. It'll use Apify to scrape the web and find leads for you. It'll verify the contact info. It'll find the specific pain signals, and it'll even create a hook for your cold email. Then we got a funnel builder to help build a funnel. There's a little video. explaining how it works here. And it walks you through step by step. So in this case, it'll help you with a client. You could also use it for yourself. The idea is that you run an audit on a website and it will run this 10 agent pipeline, web crawler, API caller. to call free APIs for metrics about the website. It'll find competitors. It'll analyze AEO. It'll strategize for SEO, write a report, design the report, build the report, review the whole design, then write a cover letter, and then validate everything with quality review. And then you can just email the client and be like, okay, hey, I made you this AEO audit. This is free, but if you want the big one, it's a few thousand bucks. But here it is. So we have all these rigs in here. They're all harnesses. And they're free. It's a seven-day free trial. You can come in here and steal them. leave. It's all good. This is my personal content forge. This is exactly what I was showing you here. This is it. Oh, hey. So yes, it created a substact draft. Boom. Premature freedom. I built the dream, then gave it up on purpose, right? And then it wrote a newsletter draft. Oh, it sent it to the wrong place. That's interesting. So it made everything. It baked for 16 more minutes. So all of that took about 35, 37 minutes to run through everything. here's all the content premature freedom it's funny it's kind of a random one but we got the youtube metadata here titles description even though this is not a youtube video yet chapters i normally run this with the youtube transcript after this time i ran it with the transcript from before then here we have an x thread with images that weren't generated oh there were images okay they're generated images on brand And then we got the blog post here, we got the emails here, the newsletter. So it went through and did all that, basically. That's a harness. And now I'm just gonna say, fix that part of the harness so it doesn't happen again. And then git push. The harness is fixed. It sent the newsletter to ConvertKit right here. I built the dream, then moved to a suburb on purpose. Yeah, it is kind of weird. what I did with my life. And then finally, probably the coolest bit is here on the web now, premature freedom. Oh, it didn't pass the test. This is for my ghost writer, which is another video on the channel. Hopefully you'll see, but this is the UI for my ghost writer because I like making the content, but I don't like posting it. So this is the X thread that can be copied or you can edit it. It'll make the blog post. It's got an image here, all on brand, the newsletter, which is what we just saw on kit. and then all YouTube metadata, which isn't accurate at all because this isn't actually a YouTube video like it normally is. And then there's the checklist of everything that's here. And then the ghostwriter, Tommy, can mark things as posted and it all syncs to GitHub. And boom, that's Jordan Nerve's content repurposing system. That's a harness in action for something I think every solopreneur or creator kind of should probably be valuing, repurposing your content without needing 100 different subscription platforms or a big team, et cetera. So how do we get started? Well, the first step would be simply to copy something that's already been made. Now you have the safe agentic workflow, and you could simply use this template. You could copy the URL. There's a link below, by the way. Copy it, and then in your IDE, or even open code, which I've been becoming a fan of the desktop app. Lately, you start a new session. You say, let's build a harness based on that URL. I want it to do X and Y and Y. z let's talk about it and then shift into plan mode and then you get started that's the like simplest way to do it and your ai will then say okay we should duplicate it we should clone it or we should just take the ideas and build our own thing every model is probably going to have a different opinion on that so let's explore how I would do this now for the sovereignty directory. So here in the SovereigntyAtlas.com, I noticed that my data for SEO API key wasn't being called like I thought it should be. So I said, hey, run an audit. What's going on with our SEO? Was the strategy made correctly or not? And basically it said it was, but Opus came back saying, all right, here's what we can do to fix the schema. and make it better. So my recommendation for the next step is still A, seed the listing facts, deploy the schema fixes now, or C, build. I wanna do all these things, but I want to do them efficiently. I want us to build a harness for these common tasks of adding new content and ensuring that the schema and everything matches and fits the directory strategy most often. And then I'll go into plan mode here. Let's talk about it. Sub-agents, skills, etc. So now, I didn't copy any GitHub URL, I just said let's build a harness. That's a great instinct. Right, thanks a lot. The work I just did by hand is exactly the type of repeatable workflow that should be a harness. There you go. So we're now building a harness inside cloud code for this repetitive task for this particular project, which is a directory and it's going to need new content. So this will save tokens and time in the long run, because next time that I want to add new FAQs or new pages like the home setting libertarian pages, it'll just run through the harness and I won't need to ask me any questions and I won't need to waste a bunch of tokens like figuring it all out like it will right now. okay so now claude has come back to me which content workflow should the harness cover this determines how many commands and agents we build seed frequently asked questions on listings yes add a new listing yes write a new guide yes refresh research and audit sure why not how autonomous should the pipeline be where does a human gate it so basically I'm just going to need, with this recommended option, the agent researches, drafts, and reviews the voice. The orchestrator presents the final artifact for my approval before it touches seed files or the DB. I'm just going to say fully autonomous because I'm pretty confident with Fable's original work. Where should the harness live and how should content reach production? Yeah, right there. Great. So now it's building the harness and we'll come back to that and run it when it's done building. Because I didn't want to do the human approval, it's going to do automated quality bars that make autonomy safe, which is probably smart. But this is essentially like even this safe agentic workflow, this is like enterprise grade AI stuff. These harnesses are how you go from like novice amateur AI slop to like really good quality. Now I don't post anything without reviewing it. Even the Atlas, I went through most of it before I put it online and I was like, holy moly, this is so good. I was like so impressed with this research and everything. And I know most of it's accurate because I'm familiar with most of it anyway. And I think that's just, part of the appeal of fable as well and these newer frontier models but anyway it does such a good job that then the human almost just needs to like read it okay that's good ship it uh and you know i i still haven't gotten to that point with my blog posts and that's probably a good thing because they're supposed to be coming from me a human but they are a good starting point okay so it's pretty much done now what you have now a fully autonomous content harness at sovereign directory fast claude So here we are at the cloud folder. We have agents. Maybe it explains it here. We have commands for adding a frequently asked question page schemas to listing up pages. Adds a listing with the correct running and trust label. Writes a guide in Jordan's voice targeting a keyword cluster. Refreshes demand data. Runs the SEO AEO audit. Wow, cool. Okay, two open items for you to do. Populate the Netlify build hook URL. Okay, I gotta figure that out. Confirm the harness can reach the Superbase production connection. All right. So, want me to commit the harness or take it for a real spin? We'll say yes. Let's do that. And to make sure it does it right, we'll say write a handoff prompt to start in a fresh conversation. So when you run a harness, you generally want to make sure it's in a new conversation. So there's no like leftover residual context and tokens. And when you start fresh, you're going to get better results anyway. So here we get finishing up whatever it needed to do. Going to make some commits and then we'll start a new conversation. So we got this handoff prompt. We'll clear this and let's just read it real quick. You're in this directory. It has an autonomous content harness that I built in verified end-to-end, read clotmd first. Actually, I don't even want to say all that. State what I want to do in this session. Run, refresh, research. All right, so I'm just going to copy these. Actually, we need these constraints, too, because I haven't fixed whatever that is. All right, so we'll clear this, paste that. And now I'm not telling it that it's in a harness. That's the real point here, because it should automatically open up CloudMD, which says, hey, this is the Sovereignty Atlas directory harness. Here's everything you need to know about it. Here are your commands. Here are your agents. Here are your skills, reference files. So that's what it's going to do first. And you really want to make sure you have auto mode on, too, by the way. But be careful with auto mode. So it's running the refresh research skill. Let's check that out. Interesting. refresh research where is it finding that skill is there another huh well i don't know where it found that skill but it's using this skill now directory strategy and then it's using the researcher sub-agent so in here okay there's refresh research oh okay it was the forward slash command okay so forward slash refresh research command it loaded that as a skill basically So get the pipeline and it spawns the researcher agent. And that's what we see here, the researcher agent. And let's see, do we have a researcher agent in here? Yeah, researcher MD. Cash first demand competitive research for sovereignty outless content. Map a target to PAA questions, volumes and competitive signal runs live for data SEO. You produce a research brief. Okay, so it's going. So here we see we've got it running. We're five and a half minutes in now. If I scroll up a little bit, we'll see. We had the researcher go. We had the SEO, AEO auditor go, which was phase B. Then the main. And then that agent gave the report to the orchestrator agent. The orchestrator agent reads it. to decide what's next. Report is good. So let's set up task tracking and see the first batch. And now it looks at the commands and what's necessary to run. Now I understand the pipeline, and it keeps going. So now we're phase A, because we're still in phase A, the research brief for the FAQ batch. And it's just gonna keep going. So once again, that's the harness. It's just gonna go. We'll check back in when it's finished. Okay, boom. Now let's take a look. It's done. Step one, refresh the research. I didn't spend any money for the SEO stuff. Step two, seed the FAQs. so new stuff to the database i think full gate chain half the stuff i don't even understand but it understands and it knows why this is necessary and that's what's important here two things you need to know this is not a clean that new batch committed mid-session yeah that's because in another conversation i was testing it to make sure the system was working so yeah that's okay also worth noting the auditor report only through this thing okay the deploy path change mid-session yeah Okay, so I'm just going to explain. The issues came because I had a testing agent checking everything out and it didn't know you were working. So that said, make sure everything is ready to go and commit and push and deploy everything. By the way, that cooked for 22 minutes. Fable did such a better job, though. Didn't need to ask questions. Didn't even need to think. And then you know what I'll do? separately in a new conversation here. I'll split this, run Claude, add a recently added section on the landing page, and push. So this should be able to give us an idea of how well it worked. Okay, cool. So I got through it. Now we should see the recently added. Okay, great. This one was submitted with the form a few days ago, the submit a listing. I had a friend actually submit his community in El Salvador. So now once this is done, we should see new ones here and we'll know that it worked. Meanwhile, I'm just going to do some other little fixes. All right, so I finished the first thing and then I actually set it to write these two more pages that apparently were easy pickings for the SEO. So it's running the full pipeline on writing these two guides. okay so the voice reviewer agent came through plot had to look somewhere else to find that agent and so we're gonna have to fix that after and then it found some problems unsighted historical claims so the reviewer is being appropriately strict and adding a source is the honest move these are falsifiable claims let me revise homesteading cycle one to add a citation so this is what's cool about the harness that's properly created is it's not just gonna write something and make it up to make you happy because then another agent's gonna be like, yo, that agent just made some shit up to make you happy because that reviewer agent's job is to make sure nothing that's not real gets through. So this goes back to why I said I wanted to be fully autonomous. I don't wanna read it myself, but I wanna make sure it's good. Now, do I recommend you do that? No, I think we should read these things ourselves. But this whole project is kind of more of an experiment for me than anything else. But I am going to check it later. So, I mean, yeah, I mean, to each their own with that. Homesteading, 34 out of 50 ship. Libertarian, 45 out of 50 ship. Okay, cool. So it made it. It had to run through the loop again because it decided that it wasn't good enough. So I'm just going to finish this up, put it live, and we will hopefully see it under the recently added section. I also added a recently modified section, but nothing can show up there yet because it's like a new field in the database. So let's take a look. All right, and it's done. We have these new guides. Let's take a look here. If I refresh here on the main page. Okay, I'm not seeing the recently added thing, but... Let's take a look at these actual pages, the guides. Yes, they are here. Great. So I just made this, posted today. We've got some sources. Archives.gov. Okay. Killing the free land myth, plainly. Frequently asked questions. And it actually did add these FAQs. And then let's look at this. What is a libertarian? Somebody calls themselves libertarian, you just nod along, but you're not totally sure what you just agreed to. written in my voice okay that has my voice standards this isn't just ai written so that's why it looks not like most ai slop then what else it did was it took for example the cold card wallet and it added uh fax after frequently asked questions and that's all for more seo stuff so it just ran all that through the harness, and it also tells me, oh, there's things we can fix. So that, my friends, is a harness that we just built in action with instant results working on its own for, I don't know, we probably went on over an hour here, in and out with the different tasks. Okay, so we've gone through what an agentic harness is, how they work, how to get started. We've built one, so let's TLDR here. Models, intelligence is essentially rented. Perhaps you have a powerful enough computer, but let's just say Fable 5 vanished in three days and disappeared. Couldn't use it anymore. So we have to keep this in mind if we want to be sovereign for newers. The harness is the rig around the model. It's the body for the agent, and this is the part you own. Open source. Keep it on your computer. It doesn't matter if intelligence disappears. You can plug different intelligence into it. Build with Frontier. Run with Open Source. Save the money on running it, but make sure you get the best quality when you build. Start by stealing a good one. You're obviously not really stealing. Shout out to Scott Graham. Thank you for providing this to the world. It's awesome. Safe agentic workflow. The link is below. You can also just do what I did and just tell CloudCo to start building it. And believe it or not, I'll do a really good job. Swap the brain. Keep the body. That is a durable asset. So I hope this was helpful. Make sure to say hi on the AI Captain's Academy if you want to explore harnesses and rigs. If you have questions, everyone is welcome. We also host two calls a week in there. I will be there. We can hang out, ask questions, anything you need. And don't forget to subscribe if you want to learn about AI agents with me. See you later.
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Fable 5 was incredible, then it got pulled. I didn't lose a single workflow, because the part that did the work wasn't the model. It was the harness. You don't need another AI tutorial. You need a community full of people who are actually building. Join the AI Captains Academy: https://skool.com/aicaptains Ready to go deeper? Free 5-day email courses: → AI Foundations Sprint: https://foundations.aicaptains.ai → Command Line Bootcamp: https://bootcamp.aicaptains.ai An AI agent is really a model plus a harness. The model is the brain (the intelligence you rent). The harness is the body — the context, tools, checks, and memory that turn any LLM into something that actually ships work instead of just chatting. That body is the part you own. In this one I break down what an agentic harness is, walk through the agent loop (read → pick a tool → run → check → done?), and show two of mine running live: my content forge (which cooked for ~35 minutes with no babysitting) and a directory harness I build from scratch on camera for sovereigntyatlas.com. You'll see the real rough edges too — I close a running harness by accident, a draft lands in the wrong place, and my voice-reviewer agent catches unsourced claims and forces a rewrite. That's the honest version. The future belongs to builders who can create their own solutions. Stop depending on others' platforms and start building your own digital empire. Join the AI Captains: https://skool.com/aicaptains 🔗 Resources: Venice API (get $10 free credits): https://venice.ai/chat?ref=PA5RHk Safe Agentic Workflow Github: https://github.com/bybren-llc/safe-agentic-workflow Opencode: https://opencode.ai/ VSCodium: https://vscodium.com/ Venice AI: https://venice.ai/home ⏱️ TIMESTAMPS: 0:00 - Fable 5 got pulled 0:39 - Why this channel — sovereign AI 1:03 - The directory I built right before Fable vanished 1:50 - What an agentic harness actually is 2:17 - The agent loop: read, pick, run, check, done 3:04 - An agent = a model + a harness 3:58 - Rent the brain, own the harness 4:27 - The two problems with renting the model 6:05 - Build with frontier, execute with open source 7:11 - Your job moved up: you're the director now 7:34 - Stealing a harness: the SAFe Agentic Workflow 8:55 - My content forge running live (~21 min unattended) 11:11 - Anatomy of a harness: the knowledge base 11:48 - The .claude folder — agents and skills 13:08 - Hooks, commands, and CLAUDE.md 14:55 - Context engineering with sub-agents 17:15 - Swap the brain, keep the body 17:32 - The AEO audit rig (a 10-agent pipeline) 18:55 - What the forge produced (and what broke) 21:08 - How to get started: steal a good one 21:55 - Building a harness from scratch on Sovereignty Atlas 26:07 - Running it fresh — the handoff prompt 30:01 - Results: the directory updates itself 31:03 - The voice reviewer catches unsourced claims 33:36 - That's a harness — recap 34:26 - Start by stealing a good one 34:48 - AI Captains Academy + close The move underneath all of it: build with frontier models (Opus, GPT, Gemini), then execute with cheaper open-source ones. Swap the brain, keep the body. That's a durable asset — and you don't need to be a developer to own one. For fellow builders who'd rather own the rig than chase the next hyped model. Say hi on X: https://x.com/jordanurbs Substack: https://jordanurbs.substack.com/ For the algorithm: Claude Fable 5 AI Harness Engineering AI Harness Harness engineering ai What is harness in ai