How to Build Your Own Agent OS

Ajouté : 2026-06-02

[00:00:00]How to build your own agent operating system. What if every AI tool you've ever used has been making you slower?

[00:00:05]What if switching between Claude, ChatGPT, and a terminal every hour is actually your biggest productivity problem right now? What if the problem isn't the AI, it's that you have no system around it. What if the people who are getting 10 times more done aren't using better tools, they're using a better operating system. And what if you could build one this weekend for free?

[00:00:21]Hey, I'm the digital avatar of Julian Goldie. I help people learn how to actually use AI agents to build real systems that do real work, not theory, not demos, actual workflows that run without you. Today I'm pulling back the curtain on the exact system I built after 100 hours of trial and error, nine complete failures, and five lessons I had to learn the hard way. This is the full seven-layer blueprint for building your own agent operating system. Stick with me to the end because the last layer, most people skip it, and it's the one that makes the whole thing compound over time. Right now, most people using AI are bouncing between a dozen different tools. ChatGPT in one tab, Claude in another, a terminal running somewhere else. You paste context into one, copy the output into another, and none of them actually know who you are.

[00:01:00]Every prompt is a cold start. That's not an AI problem, that's a system problem.

[00:01:03]I was doing the exact same thing. Every morning switching between Claude for writing, Keyword Tools for SEO, Google Docs for drafting, all these platforms for publishing content for the AI Profit Boardroom. Each tool was useful on its own, none of them talked to each other, none of them knew my voice, my goals, or what I'd already built. I was spending 20% of my time just re-explaining context. That's friction, not leverage.

[00:01:22]So, what is an agent operating system?

[00:01:24]Think about how your laptop works.

[00:01:26]You've got an OS underneath everything that manages resources, handles memory, lets apps talk to each other. An agent operating system does the same thing for your AI agents. One dashboard, every agent, all your history saved, previewable and searchable. Shared memory that every agent pulls from. A system that runs and improves even when you're not in it. Now, let me tell you about Hermes because it powers a huge part of what I'm building. Hermes agent was built by News Research, launched February 2026, and hit over 100,000 GitHub stars in under 3 months. It's not a chatbot, it's a fully autonomous agent that lives on your machine, builds persistent memory across every session, and gets more capable the longer you run it. When it solves a complex task, it writes a reusable skill document, so it never has to figure that out again. It integrates with Telegram, Discord, and Slack, supports over 40 built-in tools, including web search and browser automation, and the whole thing is MIT licensed, completely free, no lock-in.

[00:02:18]Hermes isn't just another tool you add to the pile. It's designed to sit inside a system, which is exactly what we're building. Before the blueprint, here are the five mistakes I made on the way.

[00:02:28]These are the things that will waste your time if you don't know about them up front. Mistake one, treating AI as a tool, not a system. I used to pick up each new agent like it was a fancy hammer. Claude for writing, Hermes for research, another tool for images. But when every problem looks like a nail, nothing fits together. The breakthrough wasn't finding a better model, it was designing a system around the models I already had. Once I did that, everything became dramatically more useful without changing anything else. Mistake two, paying for subscriptions before checking the free options. I was setting up paid memory tools, dashboards, automation platforms before testing whether the free stack could do the same thing. It usually can. Hermes is free, Claude Code has a free tier. Obsidian, which I'll cover in the memory layer, is completely free and stores everything locally. The rule I follow now, prove the workflow first, then upgrade only when the free option genuinely can't keep up. Mistake three, relying on built-in chat memory.

[00:03:16]For a long time, every Claude conversation I had started from zero.

[00:03:19]I'd explain who I am, what the AI Profit Boardroom is, what tone we use, every single time. The in-app memory that most AI tools offer isn't detailed enough.

[00:03:26]Details are everything. The fix is an external memory layer every agent can pull from. More on that in a moment.

[00:03:31]Mistake four, building automations in N8N. I spent a lot of time wiring content pipelines in N8N. It works, but it's brittle. Every webhook needs its own logic, and it breaks when anything updates. If you already have a solid agent like Hermes running, you can run those same workflows natively inside an agent operating system with no code. N8N is useful for plumbing two tools together. An agent operating system doesn't need plumbing. The agents talk to each other through a shared workspace. Mistake five, letting outputs land in random folders nobody can find.

[00:03:58]Think about everything you've ever created with AI agents. Images, scripts, websites, voice notes, how much of it have you ever found again and built on?

[00:04:05]When outputs disappear into random folders, you lose the compounding value.

[00:04:09]Every artifact needs a home that auto collects it, organized by type, previewable on demand. Inside the AI Profit Boardroom, I built a full mission control system, a Next.js dashboard where every agent lives in the same sidebar and every output is automatically saved to the workspace. I use it to run content production for the AI Profit Boardroom end to end. I feed it topics that AI Profit Boardroom members are asking about, generate scripts, SEO content, and studio assets, and it all flows back into the system automatically. That's not something I manually manage. It runs. If you want the full setup, the prompts, the zip file, and the 30-day roadmap, it's all inside the AI Profit Boardroom. Four weekly coaching calls, live help building this out, and every update I make gets pushed straight to members.

[00:04:50]You can find that at AI Profit Boardroom.com. All right, here's the seven-layer blueprint. Each layer feeds the next. Skip one and the layers above it collapse. You build bottom up. Layer one is the foundation, your hardware. A modern laptop is fine. Everything we're building runs locally on your machine, no cloud subscription required. Layer two is the memory layer. This is the one most people skip and the one that changes everything. I use Obsidian combined with Omi. Obsidian crossed 1.5 million users in early 2026. It stores everything as plain markdown files on your machine. No proprietary formats, no vendor lock-in. Any AI agent with local or MCP access can read from and write to your vault. Since early 2026, Obsidian ships with an official CLI exposing over 100 commands, so your agents can search, create notes, and navigate your vault directly from the terminal. Omi captures your conversations and screen context throughout the day, and you can sync those memories into your Obsidian vault.

[00:05:43]From there, every agent you use pulls that context automatically before responding. What this means practically, when I ask Hermes for keywords relevant to the AI Profit Boardroom, it doesn't guess. It pulls from my vault. It knows our audience, our niche, our previous content. The output is immediately useful because it starts with full context. Layer three is the brain, the models you route tasks to. Think of models as engines and the architecture as the vehicle. Models change constantly, so what matters is the routing layer. When a better model comes out, you swap it in without rebuilding anything. Start free on Open Router.

[00:06:14]Layer four is the agents, the harnesses that wrap the models and give them tools, memory, and the ability to act.

[00:06:20]Hermes for long horizon autonomous tasks, Claude Code for anything touching a code base, Open Claude for image generation and voice. You don't need all of them on day one. Start with Hermes and add others as you need their specific strengths. Layer five is the command center, a single interface where every agent lives in the same sidebar and all your work is visible. Without this layer, you've got a collection of tools. With it, you've got an operating system. Built in Next.js, you can build it yourself or grab the full setup from inside the AI Profit Boardroom. Layer six is production. This is where actual work gets created. For me, that's goals mode, SEO, content production, a studio for images and video, a notebook for research, and a workspace showing everything I've built. When I need SEO content to bring more people into the AI Profit Boardroom, I go straight to that section. Already set up, already contextualized, no re-explaining required. Layer seven is the loop. Every output your agents produce gets written back into the memory layer. Every piece of content created in the AI Profit Boardroom, every completed task, every research output, it all flows back into Obsidian as structured notes. Every new chat starts smarter than the last.

[00:07:23]Without this layer, your system is the same on day 100 as it was on day one.

[00:07:27]With it, it compounds. A few practical tips before I wrap up. Don't try to build all seven layers at once. Start with memory and agents. Get Obsidian set up. Get Hermes running. Those two things alone will change how you work within the first week. Don't skip the loop. It feels like extra work. It's not. Set up your agents to write notes back to the vault from the beginning and let it build. Build for the architecture, not the current tool. Models change, agents get replaced. What doesn't change is the seven-layer structure: foundation, memory, brain, agents, command, production, loop. Build that now and every new tool that comes out just plugs in. Wait, and you're starting over every time. If you want the full process, SOPs, and 100 plus AI use cases like this one, join the AI Success Lab. Links are in the comments and description.

[00:08:07]You'll get all the video notes from there plus access to our community of 75,000 members who are all building with AI right now. And if you want the complete agent operating system setup, mission control dashboard already wired, studio configured, SEO section built out, prompts, roadmap, and live coaching calls, that's all inside the AI Profit Boardroom. Four coaching calls a week, video answers to every question, every new update pushed straight to members.

[00:08:30]Get everything at aiprofitboardroom.com.