Hermes Agent vs OpenClaw transcript

People keep saying Hermess Agent kills Open Claw. That take is wrong and I'm going to explain exactly why. Because these are not even the same kind of tool. Open Claw is a messaging gateway that happens to have an agent inside it and Hermess is an agent that happens to have messaging connectors. If you don't understand that difference, you will pick the wrong one and waste weeks setting it up before realizing it does not fit how you [music] work.

I have used both extensively and I'm going to walk you through every real difference, every trade-off and exactly who should use which one. Not going to be picking a winner for clicks. I'm just going to tell you what actually matters if you're a founder or a builder or an operator trying to get real leverage from AI [music] agents. Let me start with Open Claw because most people still do not understand what it fundamentally is.

Open Claw started as a what WhatsApp relay bot. Someone wanted their AI assistant to respond on WhatsApp and they built a bridge for it. That DNA is still the core of the product. Today, Open Claw is a gateway. Capital G. Everything flows through one central process called the gateway. It binds to a port. It manages sessions. It handles channel routing, tool dispatch and events. Think of it as air traffic control for your AI.

Every message from every chat platform, every single tool execution or every state change goes through this one process. And the channel support is absurd. I mean, it has over 50 integrations with WhatsApp, Telegram, Discord, Slack, iMessage, Matrix, WeChat, Line, email, Signal, Google Chat and built-in browser. I mean, the list can go on and on and on. It now has over 345,000 GitHub stars as of the filming of this video and 15,000 community built skills on Claw Hub, their public marketplace.

That is the scale we're talking about here. Now, the way you set up or configure your Open Claw is through a set of markdown files. The most important one being, if you've ever installed Open Claw, soul.md. This file defines who your agent is, it's it's personality, it's boundaries, it's behavior rules. You edit soul.md and you are literally editing the agent's identity. Then you have memory.md for persistent facts and context.

You have tools.md for what tools the agent can use. Everything is explicit. Everything is a file you can read and edit. You get what I'm going with this. This is the philosophy of Open Claw. You shape the machine. You control every behavior. Nothing happens that you did not explicitly configure. If you are the kind of person who likes building systems from scratch and knowing exactly why something behaves the way that it does, Open Claw is beautiful.

Hermess Agent, and yes, I'm going to say Hermess and not Hermes or whatever people keep fighting about in the comment section. I see you. Hermess Agent was built by New Research or News Research. Again, something the comment section is definitely going to fight with me about. It is one of the top open source AI labs. It launched in February 2026 and went from version 0.1 to version 0.8 in 2 month with 209 merge pull requests and 53,000 GitHub stars already.

Now, the first thing everyone talks about with Hermess is memory. And yes, it has persistent memory. It maintains two curated files, memory.md for environment facts, conventions and lessons learned and user.md for your preferences and communication style. Those get injected into the system prompt at session start. But, here's the thing. A lot of agents have memory now. That is a table stakes. That is not what makes Hermess different.

What makes Hermess different is self-generated skills. That is the part most people skip over and it's the single most important technical difference between these two tools. When Hermess finishes a complex task like debugging a deployment issue or summarizing a long research document, it doesn't just move on to the next task. It pauses. It looks back at the steps it took and if it figured out a good approach, it writes a reusable skill file and it saves it.

These skill files follow the agent-skills.io spec. Each one is a directory with a skill.md file, optional scripts, references and assets. And they are loaded efficiently into the agent. Level zero is just the skill name and description. About 3,000 tokens. Level one loads the full context when needed. Level two loads specific reference files within the skill. What that basically means is the next time Hermess encounters a similar problem, it searches its own skill library first before trying to solve that problem again from scratch.

That is the learning loop. It executes, evaluates, extracts, refines and retrieves. And that loop is what separates Hermess from frameworks where you manually author every skill yourself. It also has a full text search over all past sessions stored in an SQLite. So, it can recall conversations from weeks ago. Okay, let me explain why the self-improving loop actually matters. It's actually such a cool functionality. Because this is where the conversation stops being theoretical and it starts being practical.

If you're a founder, an operator, a builder or even a creator, your work is made up of recurring patterns. You check similar dashboards every morning. You write similar briefs every week. You do similar code reviews. You process similar customer requests. You run essentially the same operating loops in your business over and over again. With Open Claw, every time you encounter one of these patterns, the agent handles it based on whatever skills you have manually configured.

If you want the agent to get better at it, you write a better skill file. With Hermess, the agent handles the pattern and then writes its own skill file based on what worked. Next time that that pattern shows up, it already has a solution in its library. And if the solution gets refined over multiple encounters, the skill file gets updated. That is why it's compounding. The longer you end up using Hermess, the more skills it accumulates from your actual work.

Now, there's a real trade-off here. With Open Claw, you know exactly what every skill does because you wrote it. Or you asked it to write it. With Hermess, you are trusting the agent to learn the right things and some of you are going to love that autonomy and some of you are going to hate it. If you prefer tighter control and less autonomous, let's call it drift, Open Claw is going to feel safer and more legible. If you prefer less manual configuration and more agent autonomy, Hermess is going to feel more powerful over time.

Let me be specific about where Open Claw is clearly stronger. I mean, first, channel coverage. It has 50 plus platforms versus six that Hermess has. That's not a small gap, 50 versus six. If you need your AI agent on, for example, iMessage or email or Matrix or WeChat or any of the dozens of other platforms Open Claw supports, Hermess simply does not offer that. Conversation over for that use case. Second, multi-agent routing.

Open Claw lets you run different agents for different channels, contacts or groups. One agent handles your personal DMs with a casual tone and calendar access. Another handles your work Slack with a professional tone and project context. Another can handle your community Discord and essentially they all run through the same gateway. Hermess doesn't have this. It's one agent, one persistent operator. Although they do have what is called sub-agents, but essentially you're handling one main persistent operator.

Third is the ecosystem. It has 15,000 plus community skills on ClawHub. If someone has already built the skill you need, you just have to install it and move on. Hermes has a much smaller and newer ecosystem. Fourth, transparency. Open Claw's memory is explicit. Files on disk you can read, edit, and version control. You know exactly what the agent remembers and why. Hermes also stores memory in files, but the self-generated skills add a layer of autonomy that some people find harder to audit.

Now, let me be very specific about where Hermes is a clear winner. First is the most obvious one, the most amazing one, the learning loop. I keep coming back to this because it genuinely is the defining feature for it. No other open-source agent framework has a system where the agent writes its own reusable skills from completed tasks and improves them every single time during use. That is unique to Hermes right now.

Second, session search. I mean, full-text search across all past conversations using SQLite and FTS5. You can ask Hermes to find something you discussed 3 weeks ago, and it will pull it up. Open Claw has what is called a vector search over memory files, but the cross-session recall in Hermes just feels more natural. And you'll notice this if you use both. One is a lot better at remembering things. Third, speed of development.

Hermes went from 0.1 to 0.8 in 2 months with 209 merged PRs. It added browser use integration, remote back ends, work tree parallelism, parallelism, paralleli- parallelism, parallelism. In the beginning, new research is shipping extremely fast. >> [snorts] >> And fourth, the Honcho integration for dialectic user modeling. That is the advanced memory feature that builds a deeper understanding of who you are across sessions.

Not just what you said, but how you think and what you prefer. Let me make this simple. Use Open Claw if you need AI connected to multiple messaging platforms, if your work involves WhatsApp, Telegram, Discord, Slack, and email, and all that at the same time. And if you want explicit control over every single behavior. If you like building and configuring the machine yourself, or if you run a team and need multiple agent routing across different channels.

And if the 15,000 skill ecosystem saves you time. Use Hermes if you want one personal agent that gets better through repetition. If your work has recurring patterns that compound. If you care more about the agent improving itself than connecting to 50 platforms. >> [snorts] >> If you want broader model access, and if you prefer less manual configuration, and are willing to trust the agent with more autonomy. Or you're just simply happy to.

And honestly, some experienced users are running both. I mean, I am. Open Claw as the orchestrator for planning, decomposition, and sequencing, and Hermes as the execution specialist for things like fast and repeatable task loops. It's not a bad setup if you have the technical appetite and time. But, I do want to end on what I think is the most important thing here. The biggest mistake right now is not picking the wrong agent.

The biggest mistake is still using AI like a chatbot. Most people open a chat window and ask one question, get one answer, and they just close the tab. That's it. That is not leverage. That is Google, essentially, with extra steps. AI agents are different. They persist. They remember. They run recurring workflows. They can monitor things or route tasks. They remove actual grunt work from your day. And the people who set this up now are going to have a massive advantage over the people who wait until it just feels obvious or gets at the height of its popularity.

So, pick the one that fits how you work. Set it up this weekend, or today if you have time, and start building the system that works for you while you sleep. If you want to watch a full hands-on setup tutorial for either Open Claw or Hermes, I have both of these videos already on my channel. And don't forget to subscribe if you want more real breakdowns on AI agents, automation, and how to actually use this stuff to build.

I'll see you in the next one.