If you have been tinkering with agents for a while, OpenClaw probably sounds very familiar. For a while, it was one of the most interesting things to come out for building an assistant with real tools, channels, and memory. The problem is, when you move from tinkering to daily use, the seams start to show. Not because the idea is bad, but because there comes a point where everything gets too mixed up: instructions, memory, automations, skills, and operational context all living in the same place.
That is why I find Hermes Agent interesting. I do not say this in a “the new thing is out so here it is” kind of way, because in this sector that happens every other day. I say it because the proposal makes a lot of sense if you are coming from OpenClaw and have already hit its limits. Hermes Agent, which is also open source and comes from Nous Research, starts from a very simple idea: a useful agent does not just need more tools, it needs more order.
Why I Think It Is a Better Alternative Than OpenClaw Right Now
OpenClaw opened an important door. It taught us that you could talk to an agent via Telegram, put it on a server, connect it to external services, and ask it for truly useful things. That is still powerful. But it also left a pretty clear feeling for many people: when everything depends too much on the chat and immediate context, keeping the system clean becomes a pain.
Hermes Agent goes straight at that problem. The nice thing is not that it does different magic, but that it tries to better separate each layer of the agent. And that difference, which in a video might sound like a technical detail, is felt a lot in daily life. It is not the same to have an assistant that responds well today because it has fresh context, as to have one that knows how to distinguish what is a stable instruction, what is a constraint, what feedback deserves to be saved, what memory should persist, and what part belongs to the general orchestration.
The Important Idea: Memory, Skills, and Learning Are Not the Same
This is where I think Hermes makes the most interesting leap. Many people throw everything into the same bag and then wonder why the agent becomes inconsistent. But no, a memory is not a skill, and a skill is not the same as learning.
Memory should store things worth remembering between sessions. Your preferences, decisions already made, useful context, mistakes not worth repeating, or information about how you work. Skills are something else. A skill is a reusable procedure. It is a structured way to do something over and over without having to explain it to the agent from scratch.
And then there is learning, which is yet another distinct layer. Learning is not dragging more text into the prompt every time. Real learning is detecting that a task repeats, that there is a way to solve it that works, and converting that into something reusable. That is where Hermes is especially attractive, because one of the ideas it proposes is exactly that: a repeated procedure could end up converted into a skill instead of getting buried in an old chat or poorly placed memory.
Harness Engineering, But Well Separated
Another part I really like about Hermes is how it lands what some call harness engineering. The name sounds weirder than it really is. At the end of the day, we are talking about the layers that wrap around the model so it stops being just an LLM responding text and starts behaving like a usable agent.
In Hermes, that idea is very clear because it relies on five layers that make a lot of sense when you look at them calmly: instructions, constraints, feedback, memory, and orchestration. Instructions are what set the general behavior. Constraints put limits so it does not do silly things or step out of bounds. Feedback serves to refine what works and what does not. Memory stores what should survive a specific conversation. And orchestration decides how all of that fits with tools, tasks, channels, and real execution.
Said like that it sounds like naming pedantry, but it is not. When those layers are better separated, the agent stops being a mass of accumulated prompt and starts behaving with much more coherence.
It Does Not Live Only in the Terminal
Another thing I like is that Hermes Agent is not conceived as an experiment locked in a console to make pretty demos. You can use it from the console, yes, but also connect it to other channels like Telegram, Discord, or even email. And that changes the movie quite a bit, because a real agent makes sense when it can be where you already work, not just in a technical window opened out of curiosity.
There it also follows the OpenClaw line, which was precisely one of its most powerful parts. The difference is that Hermes seems to want to do it with a cleaner base so you do not end up patching half the system every time you add a new integration.
It Can Run Locally or on a VPS, Which Is How It Should Be
Hermes is not about selling you a closed app and that is it. It can run locally if you want to test or keep it close while you tinker, but you can also set it up on a VPS to leave it running 24/7, which is ultimately the interesting part if you want it to act as a real assistant.
The installation, moreover, does not seem designed to complicate your life. On Linux, macOS, and also on WSL2 the startup goes with this one-liner: curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash. If you are on Android with Termux, the exact same command is used and the installer detects Termux automatically. On native Windows it is still in early beta, but they already have their PowerShell command too: irm https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.ps1 | iex.
That does not mean there is no infrastructure part, even if it is small. You have to decide where it will run, what credentials it will use, and what real permissions you give it. Precisely because of that, it is worth looking at the complete installation guide in the official Hermes Agent documentation, which is also what they mention in the video when they get to that part. There they calmly explain what the installer actually does, how the layout looks if you mount it per user or as root, and what nuances there are on Windows. You can find it at https://hermes-agent.nousresearch.com/docs and, honestly, it is the fastest way to not waste time with half steps.
Choosing a Provider Stops Being a Prison
Another practical point is that it does not marry you to a single AI. When you finish installing it, the next natural part is connecting it to something useful, and that is where Hermes fits quite well with what is shown in the video. You can use Ollama if you prefer to run models locally, use OpenRouter if you want to have several models and providers under a single door, or connect it to ChatGPT and in general to OpenAI-style providers if you already work with that ecosystem. And then there is the other half of the matter: not only which model you connect it to, but where you are going to talk to it. There integrations like Telegram come back in, which is where many end up noticing whether the agent really serves them or stays as a pretty demo.
In the end, the good thing about an agent like this is not marrying a brand, but being able to choose the right tool for each case. There are tasks where it pays to spend more and others where it makes no sense at all. If on top of that the system is better organized, that choice weighs less on the general chaos and more on real performance.
Migration From OpenClaw Seems Much Friendlier Than I Expected
If you already have OpenClaw set up, there is one thing here that made me laugh because it is simple but useful. Migration exists and does not seem conceived as a drama. The command is this:
hermes claw migrateAnd just for that you can tell they understand where the people who are going to try it come from. They are not pretending OpenClaw never existed. On the contrary. They assume that many people come right from there and that the logical thing is to offer a reasonable on-ramp.
That said, good migration is not just moving files. Mental cleanup also matters. If in OpenClaw you had eternal instructions mixed with irrelevant memories and procedures that should have been skills a long time ago, taking all that as-is to Hermes would be changing the name to continue with the same chaos.
Where It Can Really Make the Difference
For me the most promising thing is not a specific channel or a specific integration. It is the loop. The possibility that the agent does something, receives feedback, saves what it should, distinguishes whether that belongs to memory or a skill, and refines its way of working without turning every conversation into a context dump.
That point seems key to me because it is exactly what separates a vitaminized chatbot from an agent that truly evolves with you. If every repeated procedure can be refined until it becomes a skill, and if memory stops being a messy drawer to only store what deserves to persist, the system gains a lot of value over time instead of degrading.
My Personal Take
I would not say that Hermes Agent comes to erase OpenClaw from the map nor would I buy that easy headline, but I do think that right now it is a much better thought-out alternative. Especially for people who have already passed the hype phase and want something that can be maintained without constantly fighting with context, with increasingly fatter prompts, or with automations that only work when the planets align.
OpenClaw had a lot of merit because it taught us where things were heading. Hermes Agent gives me the feeling of taking that good intuition and organizing it better. And honestly, in agents, that order is worth more than it seems.
If you come from OpenClaw and were waiting for something that keeps the good idea but with a cleaner base, I would definitely keep an eye on this one.
What do you think?
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