You NEED to set up a multi agent team with OpenClaw and Hermes

Open Claw and Hermes agent is the most powerful combo in AI right now. When

used together, you literally gain superpowers and your productivity explodes. In this video, I'm going to go

explodes. In this video, I'm going to go over why having these two AI agents working together is incredible. Why you

absolutely need to be building a two agent setup, and I'll show you some use cases that have improved my workflows a ton. If you stick with me until the end

ton. If you stick with me until the end of this video, you're going to have an army of AI agents making your life so much better. Let's get into it. So, I

much better. Let's get into it. So, I

have been playing around a ton with OpenClaw and Hermes agent over the last few weeks, and I have come up with a system that it's amazing. First, I want to tell you why having a multi- aent

workflow is the future, and why you need to be building this out immediately. The

reliability of my AI agents has exploded since I started using these two together. One of the biggest complaints

together. One of the biggest complaints I get all the time is, "Oh, my open claw is constantly breaking," or, "Oh, my Hermes agent is constantly breaking."

When you have them working together, your downtime turns to zero. The moment

one of them goes down or doesn't perform well or breaks or does something wrong, the other comes in and fixes it easily for you. So, the reliability of your

for you. So, the reliability of your entire AI agent system gets so much better when you start using these two together. You're basically building your

together. You're basically building your own AI company where these two AI agents have each other's back, supports each other's work, and make sure they both do amazing things. These are also two very

amazing things. These are also two very different AI agent harnesses. They both

have very different strengths. The

people going on Twitter saying, "Oh, one killed the other. One's better than the other." They're idiots. They don't know

other." They're idiots. They don't know what the hell they're talking about. You

want to use them together because they both have very different strengths that complement each other really well. And

I'm going to second go over what those strengths are. which you want to use for

strengths are. which you want to use for each. It allows you to make sure the

each. It allows you to make sure the best task gets handed to the right agent so the tasks get done better, quicker, and cheaper. With this setup I'm about

and cheaper. With this setup I'm about to show you, you're going to be saving a ton of money because you'll be able to use the right agents with the right models for the right tasks, and you're going to be getting more done at the

exact same time because you'll be able to multitask and have the better task getting done by the right agents. So

before I pop open those two agents and I show you real quick how to set them up and sol them all that, here's just where I see their strengths and weaknesses at the moment and how they complement each other so well when you use them together. And then again, right after

together. And then again, right after this, we'll also go over the workflows of using each. Open Claw I'm using as my main agent. The reason why I'm doing

main agent. The reason why I'm doing that is it's just proven for me personally to be much more stable, to get updates quicker, and just a lot more

reliable when getting big tasks done.

Hermes agent on the other end has been a great assistant slashmonitor for me and I'll show you what that means in a second. But it's been great at assisting

second. But it's been great at assisting OpenClaw. It has been much more

OpenClaw. It has been much more performant for me. Basically, it's a lot faster and using a lot less tokens, which has been great. A big reason for that is it's just a lot lighter weight.

I think it was designed a lot more efficiently than OpenClaw. And the best part about all these is OpenClaw has been great at keeping Hermes agent working. And Hermes agent's been great

working. And Hermes agent's been great at keeping Open Claw working, which has been fantastic. I haven't had basically

been fantastic. I haven't had basically a second of downtime since these two started working together. The moment one breaks, the other swoops in to fixes it, which has been great. So, with that being said, knowing what each strengths

and weaknesses are, how one is a main agent, how the other is an assistant, let's go over how to use them together, and some workflows I think will be amazing for you. So, here we go. I got

my open claw Henry on the left. I got my Hermes agent Hermes on the right. I

apologize when I named my Hermes agent.

I was not feeling creative in the moment. So, it's just named Hermes. It

moment. So, it's just named Hermes. It

is what it is. What I'm going to show you now is how I use them together, some workflows you can steal immediately that I think will improve your life a ton, and when you want to be using each. So,

let's talk about models I use for each.

First of all, Henry is powered by Opus 46. I'm just going to be honest with

46. I'm just going to be honest with you. Opus is the best model for AI

you. Opus is the best model for AI agents. It is what it is. I want Chad

agents. It is what it is. I want Chad GBT to be good for AI agents, but it just isn't. So, I highly recommend using

just isn't. So, I highly recommend using Opus, the API, for your main open claw agent. I understand it's pricey, but if

agent. I understand it's pricey, but if you want the absolute best performance, you have to be going with Opus. If price

is a big thing and you can't be spending that money on Opus, the next best model is Chat GPT. You can plug in your chat GBT OOTH really nicely with the existing

plans you already have. So, you'll be saving a ton of money. Listen, I wish it was better than Opus. I really do, just because they're encouraging the use of the OOTH, but at the moment at the filming of this video, it just isn't,

but if you can't afford the Opus API, Chad GBT still works well. Plug that in.

When it comes to Hermes, I currently have ChatGBT plugged into that. If

you're on the $20 Chad GPT plan, it's going to be hard for you to plug it into both of these because that's going to be a lot of usage. So, I'd recommend going with one of the cheaper plans out there,

like the GLMs of the world, if you have Chap GBT already on your main OpenClaw agent. As an assistant, Hermes doesn't

agent. As an assistant, Hermes doesn't need quite as much intelligence. So,

you're fine getting away with one of those cheaper AI plans for Hermes agent.

So more expensive intelligence on the left in OpenClaw, cheaper intelligence on the right in Hermes since it's more of your assistant and OpenClaw is more of your main agent. Keep in mind things eb and flow all the time. If you're

watching this video in 2027, things might be completely different. The AI

models I using might be completely different. Gemini might be the best

different. Gemini might be the best model at the moment. Hermes might be a thousand times better than OpenClaw in 2027. So, make sure to subscribe and

2027. So, make sure to subscribe and turn on notifications down below. So,

every time there's an update or a model changes or harness changes, you'll know immediately cuz all I do is make amazing videos about this stuff. I also do live boot camps every single week in the Vibe

Coding Academy on Open Claw and Hermes Agent. So, make sure to hit that down

Agent. So, make sure to hit that down below and join the number one community in AI. I'll be doing a live boot camp

in AI. I'll be doing a live boot camp this week on these two tools as well and using them together. So, the first use case I'm going to start out with is super simple. Then, we're going to get

super simple. Then, we're going to get to the most advanced stuff. This has

been probably the most important use case of having a two agent system that I've ever had. The Open Claw team is incredible because they release new big updates every single day. They have like

the most amazing open-source community behind them. The issue is it's

behind them. The issue is it's constantly breaking every time I upgrade. Every time I upgrade, there's

upgrade. Every time I upgrade, there's something breaks and I have to go and fix it. Which for a lot of people,

fix it. Which for a lot of people, they're experiencing this and it's super stressful because your best friend AI agent goes down. You can't talk to it anymore. Like this is literally an

anymore. Like this is literally an example from last night. I updated to the latest Open Claw and boom, it just stopped responding to me and kept saying missing API key for OpenAI even though I'm not using OpenAI for my OpenClaw

agent at all. So what I immediately did is I went to my Hermes agent and I said, "Hey, I'm having issues my OpenClaw.

Here's the error I'm getting." It went in, it looked around my OpenClaw code and it fixed it for me. Instantly found

the issue, fixed it for me, and it was good to go. My downtime in OpenClaw has went from like an hour every time I upgrade to literally seconds if it ever

breaks. My Hermes agent and my OpenClaw

breaks. My Hermes agent and my OpenClaw agent know each other inside and out.

So, anytime there's an issue with one or the other, they go in and fix each other. This is why it's so critical to

other. This is why it's so critical to have a multi- aent approach is because these are fragile, these harnesses. If

one piece of code gets messed up, the entire thing breaks. So if you're just relying on one single agent, you have a single point of failure. But if you have two agents going, it doesn't matter if

one or the other completely breaks. You

have backup ready to go in and fix each other. So first use case, I know is

other. So first use case, I know is super simple, but it probably is the most important out of them all. And

that's just having backup. That's having

multiple points of failure. So as you're doing upgrades and updates to each, the other can watch it and make sure they keep performing well. The next workflow I want to go over is how to build things

with each and that is the supervisor builder workflow. This is relevant if

builder workflow. This is relevant if you have a mission control, if you build out any apps with your agents or anything like that. So for instance, right now I want to build out a dashboard for my scanner system. For

those who aren't familiar or new to the channel, I have a whole scanner system I set up that's constantly scraping the web at all times looking for business opportunities for me where I can build

SAS or guides or different things to solve challenges online. It's a whole very complex scanner system. I want to build a dashboard for this system so I can monitor all my scanners and see how

they're performing. This is where the

they're performing. This is where the monitor worker workflow comes in. I'm

going to have Henry, my open claw running on the best AI model, Opus, come up with a plan. Hermes is going to execute on it and then Henry will go back, make sure it performed well, and

give feedback. This is a really great

give feedback. This is a really great system because as long as you have a very high intelligence model and a lower intelligence one, you don't need the higher intelligence one doing

everything. As long as they're planning

everything. As long as they're planning and monitoring, you can have the cheaper model do the execution and you'll still get really good results and save tons of money. So, let me show you how this

money. So, let me show you how this works. So, I'm going to have OpenClaw

works. So, I'm going to have OpenClaw build a plan around this. I'm going to say, I want to build a dashboard for our scanner system. It should be a next.js

scanner system. It should be a next.js app and show the scanners, their status, and when the last run was. Can you build a plan for this I can hand to the other agent, please? Henry, my openclaw

agent, please? Henry, my openclaw powered by Opus 46 is going to go and build this plan that we are then going to hand to Hermes. There's another step I'm going to show you right after this

and that is the review step. Henry is

going to basically make sure Hermes is going and doing the right thing. But

let's first get this plan from Henry.

All right, there we go. Henry finished

the plan. We have this markdown file right here, which is great. I'm going to click that so we can open it up. Here we

go. Boom. Look at this beautiful plan.

Wow. This is a 256line plan. Let's give this to Hermes now. So,

plan. Let's give this to Hermes now. So,

I put in the plan that Henry built and I put in a caption. Hey, I want to build a dashboard. Here's the plan. And I'm

dashboard. Here's the plan. And I'm

going to hit send. And now Hermes is going to get the plan and actually start building it out for us because it has that plan from Opus. It's going to be done really, really well because it has a really wellthoughtout plan. By the

way, if you have an extra monitor or something, the setup you see here I have up at all times. I have two monitors.

So, I have Henry and Hermes up on my second monitor at all times so I can quickly go and chat with them. Having

these up at all times, always visible, like out of the side of your eye, makes it so you're a lot more likely to use them. So, I highly recommend if you're

them. So, I highly recommend if you're doing this setup and you're copying me here, keep up to windows just like this.

This is Telegram, by the way, up on your second monitor or wherever at all times.

Just you always remember to be using them. All right, looks like it's done

them. All right, looks like it's done building. Let's check it out. Let's see

building. Let's check it out. Let's see

what we got here. See how it looks. Oh

wow, look at this. This was all built by Hermes agent. Okay, so here's my scanner

Hermes agent. Okay, so here's my scanner dashboard. 12 of the 18 scanners

dashboard. 12 of the 18 scanners healthy. Six are erroring out right now.

healthy. Six are erroring out right now.

And then we can see each of the scanners. This is great. I can see the

scanners. This is great. I can see the last run, the next run, how long they've been running for. This is really, really cool. I wonder what happens. Can I click

cool. I wonder what happens. Can I click it and something happens? Okay, I click it. It's loading. I'm going to imagine

it. It's loading. I'm going to imagine it's going to show me the runs and what it discovered and things like that. Oh,

wow. Boom. I can see it. The last run, the run history, everything in it. I

love it. That's really, really sick. So,

it did a really good job and it looks very nice. Now that we have the code

very nice. Now that we have the code built, let's go back to our open claw because again, we want to use the smarter model as the checker. Make sure

things went well. Almost like a Ralph loop. And let's say check out the code

loop. And let's say check out the code here and let me know what you think. And

I'm going to hit enter. Now, Henry will go and check out on the work on Hermes.

And if there's improvements needed to be made, OpenClaw will let me know. This is

how you both get better performance and also save tons of money because your more expensive agents aren't doing the work. All right, and here's the view.

work. All right, and here's the view.

This is solid work builds clean, well structured. Here's my take. Looks like

structured. Here's my take. Looks like

it's pretty good. Has some notes for improvement and we can give that back to Hermes now to fix that. But now you can see the system in action and it's so good. Use case number two is the monitor

good. Use case number two is the monitor system. I regularly schedule cron jobs

system. I regularly schedule cron jobs with Hermes to check on things that Henry is doing. The reason why I can do this is because Hermes is cheaper to run because I'm using cheaper models and

it's a lighter weight agent, I can have it constantly monitoring things Henry has built out. So, for instance, those scanners that Henry originally built, I have Hermes go in and every two hours

just look into them. So, kind of like this dashboard system we just built out, I had it running on cron jobs before this in Hermes, and it would go see the state of all the scanners, give me

advice on what's working and what isn't, and it just had this do it every two hours and alert me when things were wrong. Because Hermes is lighter weight

wrong. Because Hermes is lighter weight and cheaper, you can have it doing cron jobs a lot more often, checking in on other things, checking in on what Henry

is doing, or even checking in on social media, your emails, whatever it is.

Hermes acts as a way better monitor than Henry because of its lighter weight and cheapness. So if you have an app you

cheapness. So if you have an app you built with OpenClaw or you just have some sort of process your Open Claw does, setting Hermes up as kind of a hallway monitor that's just checking in

every few hours to make sure it's going well and alerting you if something goes wrong is a really powerful way to be using Hermes just because as an assistant it's just really good at these

types of tasks. Again, it's all about checks and balances. Them checking each other's work, making sure it's going well. It's just increasing the

well. It's just increasing the reliability and performance of everything your agents are doing. The

third use case I want to go over is a shared memory workspace. What does that mean? That basically means you have a

mean? That basically means you have a custom memory system that both agents use where they can share information with each other. This dramatically

improves the memory of your agents because now everything your agents do separately goes to one centralized space that helps improve the memory of all your agents and just make them all

better. The more mistakes each agent

better. The more mistakes each agent makes, the more information that goes to the shared memory system and improves all your agents overall. Let me show you how this works. So in Obsidian, I have a

few different folders here. You can see over on the left hand side you can see an agent Hermes folder, an agent openclaw folder, and an agent shared folder. In the individual agent openclaw

folder. In the individual agent openclaw andaw agent Hermes folders are all their memory. So everything they're doing,

memory. So everything they're doing, their daily logs, the mistakes they're making, and any working context they have. This is great for improving each

have. This is great for improving each individual agent's memory. But here's

where it gets good is the agent shared folder. Now they have a shared workspace

folder. Now they have a shared workspace that they're both checking in on to see what each other are doing, lessons they've learned, decisions they've made, and it helps them improve each other.

This is where like the recursive self-improvement comes in is when one agent learns something or makes a mistake or gets better. It's able to share all that information with the other agents as well. By having two or

more agents doing work, they're now improving each other even faster. As you

can see, I was planning this YouTube video this morning with my Hermes agent, and it put the entire plan for this YouTube video inside the shared folder so that I can then go to my open claw

and say, "Hey, what do you think about this? How would we improve this YouTube

this? How would we improve this YouTube script?" And things like that.

script?" And things like that.

Everything is stored in the shared space so they can improve each other. This is

a much better memory system than having just a bunch of separate agents working and not talking to each other. This is

all done in Obsidian, which is a completely free app. you can download. I

have a guide on Obsidian. I'll link to that down below on using Obsidian with AI agents. Make sure to check that out

AI agents. Make sure to check that out right after this if you want guidance on setting up the shared memory system as well. Just as a side note, too, for all

well. Just as a side note, too, for all of these, you can just copy and paste this YouTube video or hit share down below and then copy link and then give it to your agents and say, "Hey, check

out this YouTube video and set all this stuff up." It'll actually generate a

stuff up." It'll actually generate a transcript for you. look through the transcript, pull out all the learnings, and set this up for you. So, super easy to implement anything I share with you in any of these videos. Just take the link to the video and give it to your

OpenClaw or Hermes, and it will set it up for you. So, we talked about the planner builder system. We talked about the kind of hallway monitor system where Hermes is checking in on OpenClaw,

making sure things are running well. We

talked about the backup system where if you upgrade and one thing breaks, they can get each other's backs. We talked

about the shared memory system. These

are core infrastructure use cases where if you implement these, everything just gets better and improves. Your memory

stops going to crap, your performance gets better, you save money, things break less, everything just improves. So

implement these core structures into your multi-agent system and things will be great. I'll put links down below for

be great. I'll put links down below for both OpenClaw and Hermes agent so you can get them installed and use them together. Leave a like, subscribe, and

together. Leave a like, subscribe, and turn notifications if you got anything out of this. And again, I do live boot camps every week on Hermes and OpenClaw.

That is in the Vibe Coding Academy. Link

for that down below. Make sure to join that now if you want to learn a ton more about AI and the most important cutting edge skills on planet Earth. I hope this was helpful and I'll see you in the next