If you've worked with a second brain or memory in claude, you know how powerful it can be for AI to always be able to pull in relevant and up-to-date context around you and your business. But what makes this even more powerful is to have a personalized dashboard or command center on top of it to manage your intelligence and to automate work. So in this video, I'll show you the four big benefits of having this dashboard or command center set up.
I'll show you what an agentic OS actually is, show you the three options you have to build one and an easy way to set this up for yourself today. Now, you might have heard these terms like aentic OS or command center and there are many other fancy terms being thrown around, but all it really means is to have a personalized dashboard like this set up with all the relevant and up-to-date context in your business in one centralized place. Now, there are four main benefits to having this set up.
And the first one is, of course, you can have a completely personalized intelligence or UI dashboard for yourself with access to live data from all of your softwares and data from your second brain if you have one. And they can be molded into a custom UI that presents you with the most relevant information for you. For example, in my research tab, I can instantly see the latest information on AI entropic updates, uh, YouTube trends.
I can see the top uh, Reddit AI discussions. I can see competitor activity. In my coms tab, I can see unrelied messages across all my communication channels like LinkedIn DMs, my Circle AI community, uh, YouTube and my email, and all other relevant and up-to-date intelligence I need for my day-to-day work.
And of course, these dashboards can be customized for each of our team members. For example, for one of my sales reps, his dashboard is customized to his most important day-to-day work in sales. And we even have a companywide dashboard for general intelligence and analytics.
But besides that, this command center also allows you to take actions with AI right from that dashboard. I can, for example, directly use skills by clicking buttons to, for example, repurpose my YouTube video into a LinkedIn post. Because it's connected to my softwares through MCPS, it can even take actions right inside of those softwares.
For example, I can respond directly on LinkedIn here. I can use a skill to draft a reply and then actually send it out through LinkedIn right from my dashboard. I can also spin up an AI conversation anytime inside of this dashboard.
Uh, and these agents of course have access to all of the context behind this dashboard. I can also set up specialized longunning agents, uh, like my YouTube research agent here and run them. And I even have a widget here where I can chat with AI that has context on the dashboard I'm looking at right now.
And these AI capabilities are not limited to one model because a command center like this becomes model agnostic. As you can see here, I can use claude, but I can also use codeex or I can integrate it with any other AI provider that I want. Any of these models still has access to all of the context of course behind this dashboard.
And lastly, of course, because it lives on a live URL, we can really easily share it with team members or share this with potential AI agency clients that we set this up for. Now, because of this combination of things, you can imagine this can really become your single command center or operating system for doing work instead of being in the cloud desktop or in the terminal or hip hopping between uh many of your different softwares. Now, we actually have three options to set this up besides this live URL.
I've also set one up inside of Obsidian and another one which is a live artifact inside of the cloth desktop. Later in this video, I'll give you the advantages and disadvantages of each of these setups, give you my recommendation, and then show you for each one a simple way to set it up. But before that, let me quickly go over how this actually works because it might look very complicated, but it's actually not that complicated.
And the simplest way to understand how it works is by understanding the layers of an agentic OS or an AI operating system whatever you want to call it. Now first of course we have our L&M layer um with our AI models like club JPT or Gemini. Then we have the memory or the context layer which usually live in the folders on our computer with markdown files that contain context on us our business and even up-to-date context on everything that's changing and happening across our business.
And with this context and memory, these L&Ms can of course give us far more relevant and better outputs. But agents with like claude and chachbt can of course also save to this memory. So we get persistent context and memory across different chats, different AI providers and even across different team members.
And this context or memory is of course just a folder on your computer with markdown files, text files. Or you can be using Obsidian for this memory or context layer, which is just a tool or an app that helps you visualize a folder with a lot of files in a better way, which is also known as the second brain. Now, if you have no idea what this is yet or you haven't set this up yourself, I have two full videos covering how to set up a second brain.
So, if you haven't yet, make sure to check that video in the link in the description below, but you should be able to follow this video, too. Then next we have the capabilities layer with features like schedule tasks, routines, skills and loops that allow these agents to actually do tasks and work for us autonomously. And then we have the connector and MCP layer that allows these agents to actually get data and take actions in our softwares.
And because we have these capabilities like for example scheduled tasks, we can for example pull up-to-date context from our softwares or the internet like meeting transcripts from our email inbox, YouTube data, uh recent news and feed it that intelligence and that data directly into that context layer or memory layer. And it's how we provide that memory layer with up-to-date and relevant intelligence for us. But there's still one layer missing because if you just use cloud for example uh in the terminal with cloud code, we need to prompt an AI model each time to actually get access to that up-to-ate context and intelligence from the memory layer.
So what's missing is really that interface layer, a place where we can actually see and act on all of this data and manage the infrastructure in a better way, which is really the essential thing for AI to become our main operating system for work. And that's why of course these AI providers are investing a lot in developing their desktop apps like the cloud desktop or openi codecs or Google anti-gravity. But the downside of course of using these AI providers is that they're not personalized and they're one sizefits all and they don't actually allow us to visualize this context or memory layer very well.
So, if I want to get a clear insight on daily intelligence or my analytics, uh my to-dos or my comps, I'd either have to set up different scheduled tasks like here and go hip hop between them, look at the markdown files it generated for each day, usually of course generated in text files, so harder to digest. And if you get a folder with hundreds or thousands even of these context files, it just becomes hard to digest of course. And even if you use a tool like Obsidian to visualize some of these markdown files a bit better.
For example, here the market research brief, they're still laid out as long text files, uh, which is just not a great way for humans to consume data. So, you can see why setting up a custom or personalized dashboard can be much more practical. Also, you might have seen or heard about these tools like Hermes agent or Hermes AI.
These tools basically have their own infrastructure or framework that incorporate all of these layers, but they've added their specific UI instead of the cloud desktop or the codeex UI. But I recommend setting up one of these custom dashboards because the biggest value of a command center like that in my opinion is to have that personalized UI or intelligence layer because if you set it up well, you immediately have the most important context to start your day, to start taking action, to make decisions, and to know what to prioritize. And of course, this can be set up custom for each of your team members if you're in a business.
Now, before showing you how to set it up, if this is all going a little bit too quick for you, you might just be starting with this and it might be a little bit overwhelming. We have a full uh Aentic OS setup course in my AI accelerator that walks you through all of this step by step together with unlimited one-on-one uh live tech help, multiple weekly Q&As with me and my team, and resources to make all of this a lot easier for you. So, if that's interesting to you, you can check out my AI accelerator in the first link in the description below.
Also, if you're a small business and you want me and my team to actually set this entire infrastructure up for you together with consulting and training for you and your team, you can also book in a free call with us in the second link in the description below. And if you might be a bigger business and looking for a long-term AI partner, you can also book in a free call with my AI agency in the third link in the description below. So, how do we set it up?
Now, first you want to define what kind of custom dashboard you're going to build. and I'll show you how to set up each one after. Now, the first option you have is to set up a live artifact inside of Cloud.
The second option is to set up a custom dashboard inside of Obsidian. And the last option is the one that I showed you at the beginning, which is to set it up through a custom HTML page that can be deployed on an actual website. Now, the advantage of a live artifact is that it's the easiest to set up and the least technical.
The downside is that you won't really have an action layer inside of this dashboard because you can't actually trigger skills or run agents directly from this dashboard. You can also not really take actions in software. So, if you want to take actions on this data, you'd need to open a new task.
They're also not sharable with other people and they can't be used across teams. You also have some limitations with the UI. But if you're just going to use it for yourself and are mostly interested in that visual layer, not really the actions and want to start simple and maybe already use the club desktop a lot, then I'd recommend starting with this one.
Then for Obsidian, the upside is uh that you can actually add in that action layer. You have much more flexibility in the UI and it becomes sharable. So you basically get a dashboard overlay here on top of your Obsidian.
And again, you can have these buttons like escalate that actually trigger skills or take actions in softwares. And you can even build in a terminal here to directly interact with cloud code or can also be used for codecs or or gemini if you use those. Now, it is a bit more technical to set up, but if you and maybe your team already use Obsidian, this is probably your best option.
And I'll show you in a sec how to do it in an easy way. And then if you want the most flexibility, you can use the last option because you're basically building a custom app just like the example I showed you in the beginning. Now we can either uh build this for ourselves by just deploying it on a local host or you can host it on a website with even password protection so it can be shared with other people.
Now the big downside with this setup is that any AI action uh we integrate into that app or dashboard this will be done through the API. So it will be significantly more expensive to take take those AI actions uh in comparison to the AI actions for example we would do on the Obsidian setup. So that's one thing to keep in mind.
And if you're setting up or planning to to set up AIOS systems or dashboards for clients or other people, I would either go with option two or option three depending on if you're going to use Obsidian for them or not. Now, I'll show you exactly how to set up each one. But there's one thing you want to keep in mind for all of these is first just focus on building the interface, the action layer where we add in the skills or we can use agents or MCP actions.
worry about that later because 80% of the benefits really come from that personalized overview or intelligence. And even at that interface layer, you want to start really simple. Start with the essent essential things uh that you want to see when you start your day and then build on top of that.
And then once you actually start getting into the dashboard more and more on a daily basis, that's where you can start incorporating actions. Me for example, that's where I'm at. I'm now opening it daily to just get a quick glance of everything that's important for me.
And the more I'm doing it, the more actions I'm I'm adding in because I can see what's actually helpful and what not. So very much take the minimum viable product approach. Uh that's my recommendation.
So first, how do we set up a live artifact command center now before even this three-step process? If you haven't actually set up a second brain yet or a folder on your computer with some context, this is really the first step before even doing this, but I'm assuming you already have this. If you don't, uh, don't worry.
just watch my other video to get the exact step by step on setting up your context folder or your second brain. Uh again, I'll make sure to link it in the description below. But once you have that, there will be three steps.
First, we have to set up an MCP out of our context folder or our second brain folder. And this means that we basically have a connector that can access the context in our second brain or in our context folder. Now, why do we need that?
Because these live artifacts, the way they work is they pull data only from connectors and MCP. So they can pull data from our softwares. Uh but of course we also want to uh pull data from this memory layer, this context layer.
And because that lives on a folder on our computer, we need to actually build a connector, an MCP out of that folder. So the artifact can actually pull data from it because then every time we reload or open uh the live artifact, it will automatically be updated with the context in our second brain and our softwares. Now setting up this MCP is a bit more technical.
Um, the way you would do it is by building an MCP of the folder on your computer by using the MCP builder skill from Entropic, then deploying it on railway and then creating a connector out of it. It you can do this through cloth code, but if you're interested in joining my accelerator, we list all our skills, including our vault MCP skill, which basically builds this entire MCP out of your second brain automatically for you. So, if you're going to use that skill, all you need is to make sure that you have Obsidian set up.
It's a free app that visualizes that context folder on your computer. Then all you have to do is go here to settings, download a free community plugin which is called relay. Here in browse, you go and search for relay.
You can you can just install that one for free. You can then just import our skill and then it'll walk you through the entire process of setting up an MCP. It'll set up a railway server and then give you a URL which you can just copy, go to the customize tab, go to the connectors and add that as a custom connector.
You add that link there. You can call it your second brain and then all you have to do is log in with the same account as um the relay plugin and then you have it set up. Then once you have set up that MCP, all we need to do is just prompt Claude inside of Cloud Co-work to build us a live artifact with the dashboard we want.
We can tell cloud something like build me a live artifact. You can give your specifications and all the integrations that you want to add in this live artifact and how the dashboard should look and you can build an initial version of this command center. Now again keep it simple at the start.
I also built a skill that helps you get to a good initial live artifact according to best practices fast which is also available together with all our other skills inside of my AI accelerator. And then the third step is to actually start using it and then iterate and improve based on uh you using it. Now, if you want to set it up in Obsidian, the nice thing is we don't actually have to set up an MCP out of our second brain because it also already lives inside of Obsidian, which is, of course, a local app because this command center basically lives inside of one of the subfolders as you can see here.
Now, before showing you how you would do this, again, if you're a bit less technical and want to make this process of setting up the Obsidian dashboard really simple, we also built a skill for our accelerator members that does this entire process for you and sets up this initial dashboard directly for you inside of Obsidian. All you'd need to do is import that skill, run the skill. It will then ask you if you want to set up a web dashboard or an obsidian dashboard.
Now, in this case, I asked it to do web dashboard, but you can choose obsidian dashboard. It will walk you through a process, ask you some questions, which connectors you want to integrate, etc. It will then set up an initial dashboard for you according to your connectors etc.
Then you can iterate on that in cloud co-work or in cloud code. Scale you'd have to run in cloud code, but you can do uh the iteration process in co-work or whatever. All you do is you select your folder that's connected to your Obsidian and it can just prompt Claude to adjust the dashboard inside of the folder to any layout styles that are more relevant to you.
And if you use the skill, you already have the terminal integrated with Cloud Code. So, so you can actually work directly from here. Now, if you want to build this out yourself, what you'll need to do is first to install some Obsidian community plugins.
You'll need the custom JS plugin, the data view plugin, the shell commands plugin, and the terminal plugin. And these you need to actually be able to build sort of an HTML dashboard inside of Obsidian and actually that actually looks nice. So again you could just go here to the settings go to the community plugins install those four like customJS data view shell commands and terminal and once you have those set up you can just prompt claude in cloud co-work or cloud code or even openai if you use that give it access to the folder of that second brainer obsidian and ask it to create a new folder which is called dashboard and then you can basically tell it to create your dashboard in your way.
Now, important to also ask it to integrate your MCPs and softwares and what data you want to visualize, of course. And then lastly, if you want to add in actions, you can also do it that way by just prompting cloud code or cloud co-work, but it's important to tell uh cloud or any AI provider to use claude in headless mode, which I think is also possible for open AI or most other models, but headless mode in cloud basically makes it run claude autonomously in the back without using the API. So, it will run locally.
This is how we make sure that if you for example want to take an action here by running an agent or a skill that you're not running that through the API, which of course again will cost significantly more. So again, you can just tell cloud any buttons or actions you want to include. All you want to specify is that you want to run cloud in headless mode.
Again, it will probably take some iterations to get to a good dashboard, but again, it is very powerful in my opinion. And then lastly, I'll show you how to set up a custom page or app that you could also deploy on a custom website with password protection and share with other people just like the one I showed you at the beginning of this video. Now, again, the process of setting this up is a bit more technical because we're basically building an a custom app.
Uh so, first I'll give you the overview of how you would do it if you want to use our skill that helps you set this up fast and then I'll tell you how to do it without our skill. Now firstly again because it lives in a custom interface we need to actually set up an MCP just like with the live artifact out of our second brain. So you can use the same process I mentioned in the live artifacts to do this or again you can use um the OS MCP scale in my accelerator that helps you set this up for you in an easy way.
Now once you have that MCP set up out of your second brain you can use that same plugin that I showed you before the obsidian set setup to get to an initial live dashboard fast too. So you can import that Aentic OS plugin in the customize tab. And once you've added it, you can just use a skill inside of the plug-in, which is the Agentic OS setup skill.
It'll then ask you if you want to set this up in Obsidian or as a custom standalone web dashboard. In this case, you would select standalone web dashboard. It's then going to walk you through the entire process.
It will ask you for your API key, your entropic API key, because remember with this custom dashboard setup, we're using cloud or any other AI provider you want with an API. Of course, you can get your API key by just going to platform.cloud.com. Log in with your cloud account and you'll get an API key.
It'll then ask you some questions like the name you want to give this dashboard, if you want to add in any team members. It will ask you which softwares you want to integrate. You want to of course mention your second brain connector here too.
It'll ask you some more questions to try and personalize your dashboard for you right away. And after going through some questions, it will give you a local link where you can basically test this app yourself. And if you ask cloud in the chat to also build you a production app right away that you can share with other people, it will also give you that link right away.
You can then open it up and you'll have your initial dashboard set up. Of course, connected with your specific connectors that you indicated and any specifications you gave it. Now, it will be in my style of my brand, but you can easily adapt this by just telling Claude in that same chat to adjust the style.
Maybe throw in your brand guideline. And of course, this will just help you to get to an initial setup. Um, the way to actually get this really personalized and good for you is by just going into that same chat and iterating with Claude, asking it to make changes in the dashboard, adding in specific actions, etc.
Any changes you want to make, you can just go in this chat and iterate together with Claude. If you want to share it with someone, uh you can just share that link and you can also set up a password protect by just asking. Now you'll have to do this in the code tab again because it has to deploy things on real way and if you want to do it yourself again first step is setting up an MCP out of your second brain with the MCP builder scale deploying it on real way creating a connector out of it then you need to work in cloud code and basically build a custom Nex.js or react app and build together with cloud exactly the app that you want.
Now, when you're building this app or dashboard, it's important to know that in this case, you want to mention to clot that this has to be integrated with the cloud SDK because we need to use APIs because we can't use the headless mode like with the obsidian setup. Of course, you want to mention in your cloud code conversation all the MCPS, the skills you want to add. Again, it is a little bit of a process because you're basically building a custom app.
Um, but I recommend trying it out because it become can become very powerful. Again, if this is a bit more technical, I highly recommend maybe starting first with the Obsidian setup, uh, which is, uh, probably the better setup anyway, if you're using this for yourself and already working with Obsidian because we're not we don't have to use the API, so it's going to be a lot cheaper, too. And if you're really new to this, you could also consider just setting up um, that live artifact, which is probably the easiest way.
If you want access to all of the resources, skills, plugins, and the full OS course, uh, you can check out my AI accelerator in the first link in the description. And if you want to learn more about the second brain setup and this agentic OS, you can also check out the video here above.