Hermes Agent VS OpenClaw

Hermes Agent vs. OpenClaw. There's a new AI agent in town. It just pulled up to OpenClaw's front door.

It's name is Hermes Agent. It was built by a research team called Noose Research, and the reason people are losing their minds over it right now, it's not just because it works, it's because it actually gets smarter every single day you use it. Think about that for a second, right? Most AI tools you use today, they forget everything the moment you close the chat, every single time, right?

You log back in, you start from zero, you re-explain everything, you re-explain your goals, you re-explain who you are, over and over again. Hermes Agent does the opposite. So every time you use it, it learns, it remembers, it builds a little library of skills based on your work, your business, your preferences, and the next time you come back, it already knows, it picks up where you left off. And that's not a small upgrade, that's a completely different category of tool.

And in a world where OpenClaw has been the kind of king of agents, the most starred open source projects in the history of GitHub, the thing Jensen Huang from NVIDIA called the operating system for personal AI, Hermes just showed up and said, hold on, there's a better way to do this. Today, we are going to break down exactly what Hermes Agent is, why it matters, what it does at OpenClaw.com, and most importantly, what this actually means for you, whether you're running an agency, a freelance business, or e-commerce, or any kind of operation where you're trying to do more with less. Because the AI agent war just started, and the side you pick matters, right? So let's get straight into First, let me give you the fast version of what OpenClaw is, because you need that context.

Basically, OpenClaw started in November 2025, it was built over a weekend, and it became a really powerful project. In fact, it became one of the most starred and used software projects in the world, right? It was a very powerful open source project, still is today. And that was insane growth.

It actually went from like zero to, I think it was 300,000 GitHub stars in the space of 60 or 90 days. Absolutely blew up. People were calling it the closest thing to Jarvis we've ever seen. 60,000 GitHub stars in just 72 hours when it first came out.

Now, why is that? It's because OpenClaw did something nobody had really done cleanly before. Unlike typical chat bots, it's an autonomous AI agent capable of acting on instructions, interacting with applications, and performing tasks without constant supervision. It can run locally on your computer, connect to your messaging apps, maintain long-term memory, and implement commands on its own in plain English.

It stopped being a chat bot, and it started becoming a worker. You could even tell it to manage your email and all that sort of thing. And that was a dream. An AI agent running 24-7, and for a lot of people, actually delivered.

In fact, OpenAI's CEO, Sam Altman, was so impressed, he actually hired OpenClaw's creator, right? So it was a big deal. And yet, there is a problem with OpenClaw that nobody talks about enough, right? It's memory.

It forgets. Not completely, but here's the thing. So OpenClaw has memory per session, memory per assistant. It stores things, but it doesn't learn from its own work.

It doesn't get better, right? So the biggest difference between Hermes agent and OpenClaw is self-evolution capability. OpenClaw mainly relies on local environments and lacks automatic skill generation. What that means in practice is like, every time OpenClaw solves a problem for you, it doesn't file that away as a lesson.

It doesn't think, okay, this is how I solved that kind of problem last time, let's remember it for next time. It just moves on. And Hermes agent does not do that. And that's the difference.

That one difference is what this whole conversation is about. So let's talk about what Hermes actually is. Hermes agent is a fully open source AI agent released by Noose Research on February 25th, 2026. It has a built-in learning loop that creates skills from experience, maintains memory across sessions, and evolves with usage.

It supports Telegram, Discord, and multiple platforms and runs on a $5 BPS, or you can just install it locally if you prefer. Right, so you can run your own self-improving AI agent, one that connects your Telegram, your Slack, your Discord, your WhatsApp for literally free. And the other thing is you can connect it to something like Olama and then just bring your own AI models, which means that you can run all of it for free, and this just self-improves forever. Pretty crazy stuff.

And also Hermes agent is not tied to your laptop, right? So you're always on AI that works whilst you sleep. Now here's the core thing that makes Hermes different, the thing that everybody is talking about. So when Hermes agent completes a complex task such as, for example, debugging a specific workflow or optimizing a process, it synthesizes that experience into a permanent record.

These are stored as searchable markdown files following an open standard called agent skills IO. They call these skill documents. Here's what that looks like in practice for someone running a real business, right? Let's say you are running a social media agency.

You tell Hermes, find me the top five trending topics on x today, write three content angles for each and format them into a nice Google Doc ready for my client call. Now Hermes goes and does that. That's pretty standard. That's not even impressive at this point, right?

But here's what makes Hermes different. After it finishes that task, it writes a skill document. It records exactly how it did it, what sources it checked, what format it used, what worked, it stores all of that. And then next Monday when you ask it to do the same thing, it doesn't start from scratch.

It searches from its own skills library first and it doesn't re-derive the solution from scratch. It builds on what it's already learned. And so after a month of working with you, Hermes knows your clients, it knows your formats, it knows what you prefer, it knows your shortcuts, it has a personal playbook specifically for your business. And so it becomes closer and closer to a trained 24-7 AI employee.

And a year ago, the idea of a self-improving AI agent was something that was basically not working in practice. But today that's very easy to set up in an afternoon with core code and a quick setup with Hermes. Now this is an unmistakable shift, right? What I'm seeing here is like builders who once ran OpenClaw as a go-to persistent AI agent are switching to Hermes agent.

I'll give you an example of this. If you actually look on OpenRouter and you see the categories, you'll see that in the personal agents categories, Hermes agent is catching up with OpenClaw. More and more people are using it. Why is that?

It's because it runs more reliably, it handles smaller models, and it doesn't have as many of these security risks as something like OpenClaw. Also, it's super easy to switch. So Hermes actually provides a one-click command to migrate all of your OpenClaw data whilst preserving every memory and skill. So with one command, you can take your whole OpenClaw setup, your memories, your skills, your API keys, and just switch over.

And the people switching are not doing it because Hermes is shiny and new, they're doing it because of one specific thing, the practical sticking points around OpenClaw. For example, crashing on model switches, unreliable tool calls, bloated TypeScript code base, right? And the security issues as well. So that's pushed many people towards Hermes as well.

One developer actually put it bluntly. They said just being able to docker it was enough of a benefit for me. Now, to be fair, and I want to be fair here, OpenClaw is not anywhere close to being dead, right? It's still probably the most popular software project of all time, especially when it comes to open source stuff, right?

But the difference here is that Noose Research co-founder, Technium, is visibly engaged, right? He's commenting on builds, asking for feedback, integrating community contributions. Browser use actually became an official Hermes browser backend after a community member surfaced it. And that's the difference between a project on Autopilot and a project on FHIR.

So momentum matters. And right now Hermes definitely has it. Now, let me talk about the actual features so you understand what we're working with when it comes to using Hermes. So it has over 40 built-in tools like web search, browser automation, vision, image, generation, text-to-speech, code execution.

This all comes in the setup with it as well. And it can do all the same stuff as OpenClaw as well. So you can tell it, for example, every Friday afternoon, pull my client reports from the last seven days, summarize the key numbers, drop it in Slack, and done. You never have to think about it again.

The other difference here as well is like it's supported on macOS, Windows, and Linux. So it's pretty easy to set up here. And it stores everything in one command. So it's pretty easy to just get it rocking and rolling, essentially.

Now, it also has a built-in memory that saves to local files. So it has a third-party integration called Hindsight, which adds structured fact extraction, entity resolution, and multi-strategy retrieval. Meaning instead of just storing text, it understands relationships between things, right? Now, what that essentially means in plain English is if you've got normal sort of memory tools, it will save stuff like client name is Sarah, budget is $10,000, and that's it.

Just sitting in the file. Hermes with the Hindsight upgrade understands Sarah as a client. She has a $10,000 budget. She works in e-commerce.

She mentioned in March that she wants to expand to TikTok ads. So when you ask in April what Sarah cares about, it connects those dots because it knows, right? Because it understood the relationship between the facts, not just the facts themselves. And that's a fundamentally different type of memory.

Now, some people say, is Hermes as good as it sounds? The thing that I would say is number one is a little bit technical to set up, right? So the onboarding is a bit messy. And then also it doesn't have its own gateway UI, like for example, OpenClaw.

And Hermes agent is still early. So the documentation has gaps, the community is small in OpenClaw, and reliability varies depending on which AI model you pair it with. That's a real caveat, and I'm not going to pretend it's perfect, right? But the latest version released has optimized for sub-agents and scheduling.

That was a few days ago, and it's always been updated constantly. And the fundamental architecture, the idea of an agent that builds skills from experience and never starts from scratch, that's not a hype concept. That's basically how human expertise works. And basically, this is building on it.

So I think OpenClaw was the first big proof that people want agents to actually do things, not just chat. Hermes is the next step. Agents actually get better the more you use them and they constantly improve. Now, here's a question that I get asked all the time.

I'm not technical. Why does any of this actually matter if I'm not a technical person? And between the gap of technical person and everyone else in AI, that's closing faster than anyone predicted. So you can easily get this set up inside your terminal.

There's a bunch of GitHub commands, and actually, I wouldn't even use that. I would use something like Claw Code to help you get this set up from scratch, right? And that way, you don't need to spend hours messing around in terminal. You can just get Claw Code to install it for you, set up the APIs, and then you're good to go.

And today, anyone can do that themselves. Now, here's the part of the conversation that I think matters most. It's not really about Hermes versus OpenClaw. That comparison is interesting, but the bigger picture is we are now in a world where you can have a personal agent running 24 hours a day for free, that knows your business, learns from everything it does, and talks to you on the apps you already use, and then gets smarter every single week.

That's the world we live in, right? 2023, the conversation was AI can help you write emails. 2024, it was AI can help you write content. 2025, it was AI can automate tasks if you set things up right with stuff like NA10.

In 2026, the conversation is you can have a personal AI employee that never quits, never gets tired, learns your entire business, and is totally free. It's a totally different conversation. It's a totally different universe. And the people who are ahead right now, and they're not the ones who use chat GPT to write emails faster, they're the ones who built systems, who set up agents, who learned how to tell an AI worker what to do and let it run.

And this is exactly what we work on in the AI Profit Boardroom. It comes with loads of tutorials on Hermes Agent, how to use it, 30-day roadmaps, all the prompts, and an awesome community of supportive people. So if you want to get that, link in the comments and the description on exactly how to use it. Where does this go from here?

Hermes Agent has 8,800 GitHub stars right now. OpenCore has over 300,000. That gap is real. OpenCore is not going anywhere.

It's a massive community, NVIDIA's full backing, and Sam Altman's implicit blessing from hiring its creator. But here's what happens when a self-improving system meets a static one. Static stays exactly as capable as it was when it launched. The self-improving system gets better every single week.

So the gap between them doesn't stay the same. It grows. OpenCore has more users. Hermes has a better learning architecture.

And there are two different kinds of lead, right? Those are two different kinds of lead. And depending on which one matters most to your case, the answer might be different. For a big company that needs agents running across multiple teams with clear permission controls, you'd probably go with OpenCore and Nemacore for that.

But if you're like a solo freelancer or you're struggling with stuff, then I would go with, for example, Hermes Agent. And if you have lots of time, I would just try both of them. Neither of them are going to be the 100% finished product because they both just came out within the last three months. These are definitely things you want to keep an eye on.

And the thing is, whatever comes next, if you learn those skills right now, it's going to help you in the future, right? It's going to help you become better at setting up AI agents and also understanding how they can work inside your business. If you want help on doing all of that with real people alongside you, that's exactly what we do inside the AI Profit Boardroom. So let me close with the thing that I actually want to take away from all of this.

The Hermes versus OpenCore conversation is interesting, but it's a symptom of a bigger thing. We are entering a period where every business owner, every freelancer, every creator has access to tools that would have cost $100,000 a year in staff time just three years ago. Tools that learn, tools that work whilst you sleep. The only question is whether you actually use them.

Not whether you use them perfectly, not whether you become a technical expert overnight, just whether you start, right? Because here's what I know from watching the space every single day. The people who are winning right now, not the smartest, they're the ones who actually implement this stuff, right? The people who actually get started with this.

And you're watching this at the moment when Hermes agent is rough, when the gap between it and OpenCore in terms of users and ecosystem is enormous, when most people have no idea this thing even exists. That's exactly where you want to be because six months from now, let's say Hermes has 100,000 GitHub stars and everyone's talking about it, that's going to be too late. Today is early and that's the advantage you can build today, not tomorrow, today. So go install it, go try it, go build something with it, test out the memory, test out the self-learning loops.

And if you want to do that with a community of 2,600 people alongside you, step-by-step with guides, coaching calls, and tutorials every single week, you know where to find us, arprofitboardland.com, and I'll see you in the next one. Cheers.