Prime Agent VS Hermes: Which AI Agent Wins?

Prime Agent versus Hermes, who wins? That's a question a lot of you've been sending me since Prime Agent dropped this week. And the honest answer is more useful than a winner because these two agents learn in completely opposite ways. One of them keeps his own notebook.

The other one reads yours. And once you see that difference, you know exactly when to reach for each one. Today I'm going to run them side by side on the same tasks on my machine and spell out every single difference for you, how they work, how they learn, how they run whilst you sleep, no scoreboard, just the facts on camera. And near the end, I'll show you the setup where you don't have to pick a tool because that's a part almost everyone misses.

Quick background. Prime Agent comes from Prime Intellect. It was released August the 6th, open source, MIT license. It runs in your terminal.

You can log in with the cloud or chat GPT subscriptions you already pay for. Use API keys from over 20 providers. Their launch post reports 95.5% on the ARC AGI three above the human expert baseline. And that number is self-reported.

So treat it, treat it as their claim, but the repo is real 11,000 stars in days. And I've been running it myself since launch. Hermes comes from News Research, also free, also open source, also runs in your terminal. Wherever else you want to plug it, it plugs into almost anything.

So you can use it with, for example, open router. You could use it with free models, local models through Alarma. It can search X Live. It connects to MCP tools.

It's been my daily driver inside the agent operating system for months, running everything from competitor watching to content research. So both are free, both are open, both run real work. The difference is deeper than the features. Here's the framework that makes it all click.

I call it the two notebooks test. Every agent that learns has to write its lessons somewhere. Somewhere is a notebook. So Prime Agent keeps its own notebook.

It writes, it edits, it owns it. Hermes, the way I run it, reads your notes. You've all your business context. The notebook belongs to you and every agent you run can read it.

So one has a self-writing notebook. One has a shared notebook. That's a whole comparison. Everything else hangs off that.

Let me show you what that means in practice, starting with how each one works. So Prime Agent has one tool, a live Python session that stays open the whole time. If you need to write a file, it writes a tiny bit of code. If it needs to do a search, it's going to code.

If it needs a helper agent, it's going to write a function call and a full sub-agent spins up and hands the answer back. They call this a recursive language model. The practical part is simple. Big things sit outside the AI's memory and it grabs only the piece it needs.

So for example, I actually tested this on my machine. I gave it a log file of 120,000 lines. And as for the one critical line, it wrote two small code snippets, kept the file out of his head and came back with the exact line verified by hand. Now Hermes actually works with a toolbox instead.

So it has skills, tools, profiles, connections. You give it a job in plain English and it picks the tools for you. So for example, it can search X for what's trending right now. It can call other models.

It can hand a job to a background agent and keep going on. My machine actually runs image generation, video generation, live research, all through the same one line command. So on the first difference, prime agent turns everything into code inside one session. Hermes reaches out into everything you've connected it to.

One goes deep, one goes wide. Now the big one, how they learn. So this is where the two notebooks really split. Prime agent has something called the continual harness.

The agent keeps notes about itself, how to behave, what it learned about your project, what skills it had. Every 25 turns, a separate pass reads what just happened and makes small evidence backs edits to those notes. So if it fails a test twice, it writes a lesson down. You correct it.

It runs one command slash refine, and the correction gets baked in permanently and they built guardrails. So the base instruction never changes. Every edit gets snapshotted so you can roll anything back. You can open the notebook and read exactly what it learned.

I did this on my own install, corrected it once, ran slash refine, watched it apply one edit and the next session it just did. That's real. I recorded it. Hermes learns differently.

It has automatic learning for behavior built in, but the bigger layer, the way I run it is the shared memory. So inside the agent OS, for example, Hermes reads and writes an obsidian vault, a folder of plain notes on my machine, every session saved, every decision written down my business context, my story, my rules, my project history. And here's the part that matters. That vault isn't Hermes private property.

Claude reads the same vault. Every agent I run reads the same vault. You teach a vault once and every agent on the team knows. So if you spell it out plainly, correct prime agent and prime agent gets smarter.

Correct the vault and your whole agent team gets smarter. One lesson stays in the tool. The other spreads out across everything that you run. Neither is wrong.

They're just built for different jobs. So prime agents notebook makes one agent sharper and sharper at the work you give it. The shared vault makes every agent you'll ever run start from the same knowledge deep versus wide. Again, quick pause, because if you're already thinking, I want that shared memory set up.

That's exactly what the agent operating system inside the AI Profit Ballroom is. So you have one dashboard where your Claude, your Hermes, your OpenClaw, all your agents plug in and read one memory and new tools like prime agent slot right in next to them as they drop. You get the zip file, a 30 day roadmap for wiring in the shared vault, video tutorials and daily updates as we improve over 3000 business owners are in there and plenty of never touched AI before joining. Link in the comments description or go to the AIProfitBallroom.com.

So the third difference, how they run when you walk away. So prime agent sessions are demon backed. So if you close your laptop, the agent keeps working. If you reconnect later, pick up where it left off.

It has heartbeats that wake you on a schedule, persistent goals that survive across sessions, a bounded autonomous mode with time and token budgets you set and running agents can message each other directly and coordinate without you in the middle. Hermes runs background work too in its own style. So it can hand jobs to background agents and fan work out in parallel and inside the agent OS Hermes runs some real schedules. So for example like I have my competitor watcher running on a timer every morning at 6am.

My analyzer for content restokes at 6.20 daily. Those are Hermes jobs that run today whilst I sleep and I can show you the output. Prime agents overnight power lives inside its own sessions. Hermes overnight power in my setup lives in the agent operating system around scheduled tasks, jobs, dashboards and results waiting in the morning.

Now let me make this concrete with some jobs running side by side. You'll see those on screen. So job number one was find one critical line in a giant log. Prime agent writes code, keeps a file out of memory, returns a line.

Hermes uses tools to search and return line. Both get there. You'll just see the different paths as you can see right now. Job number two, teach it how you like something written.

So let's say for example, you want order confirmations worded a specific way with prime agent. You correct it once you run slash refine and it's locked into the agent's notebook with Hermes in the vault. You write the rule once in your notes and every agent Hermes, Claude and all of them follows it from then on. Job number three is you watch something on a schedule.

So with Hermes in the agent OS, my competitor watcher just runs every morning with no touch. With prime agent, you'd set a heartbeat, let the session wake itself. And job number four is spawning helpers. So prime agent runs a function call and a sub agent runs in parallel.

Hermes hands the work to background agents. It's the same idea. Helpers doing the digging whilst the main agent stays clean, just different mechanics. If you notice what's happening, all four, nobody loses.

The paths are just different and the differences tell you what each is for. So when would you reach for which? Here's the honest read. Prime agent shines on long, deep, self-contained work, big coding tasks, research methods, the kind of jobs where one agent grinding for hours, getting sharper as it goes is exactly what you want.

The prime intellect team built emulators from a written spec with it. That's a lane. Now Hermes actually shines as the connected agent. So the one wired into your whole world.

So your memory, your schedules, your other tools, live search, your business context, it's the agent already knows you. And here's the thing. You don't actually have to choose. They're both free.

They both log in with what you already pay for. They run side by side on the same machine. Mine are doing it right now. The real question is the one from the start.

Where do you want your lessons to live for deep solo work? Prime's notebook for your business, a shared vault, every agent reads. Now let me clear up three beliefs that stop people here. The first number is people say two agents is twice a complexity.

I can barely handle one. The opposite is actually closer to the truth because each one installs a one command. And if the memory lives in one shared vault, adding an agent doesn't add confusion. The new agent reads the same notes and starts from what your setup already knows.

The system carries a complexity, not you. The second is a self-improving agent sounds risky. What if it learns the wrong thing? Fair and primary intellect themselves tell the story of the agent learning to cheat at a game and saving the cheating skills.

That's why the notebook is reviewable. And it's a small snapshotted and reversible. Same with the vault. It's plain notes.

You can read the rule for both is review what your agent learns. You stay the boss. And this is a habit, not a technical skill. And number three is this stuff moves too fast.

By the time I learned one, the next thing drops. That's exactly why the learning layer matters more than the tool tools change weekly prime agent, three days old, but lessons you keep in a notebook in a vault carry forward. So the people who started feeding memory systems like obsidian months ago, didn't have to start over this week and won't have to start over next month either. Now here's what to actually do next.

Install both they're free and take a few minutes each. Give prime agent one deep task and correct it once with slash refine. So you see the notebook work, give Hermes one connected task, then decide where your lessons should live. And if you want the version where this already wired together, the agent operating system inside the AI profitable room runs Hermes and your other agents on one dashboard with the shared obsidian memory, the scheduled morning jobs and the workflows I've shown you today.

There's a 30 day roadmap for setting up your agent memory in your business, step-by-step and tutorials. And as members test prime agent setups, we cover those tools the same week. You get four coaching calls every week where you can ask about your exact agent stack live a prompt library, a member map to find people near you running the same tools. And someone's always online link in the comments description or go to the AI profitable.com to get access.

Here's where I'll leave you. Prime agent versus Hermes was never really a competition. One keeps own notebook and get sharper alone. One regional book makes everything you run smarter together.

Both are free. Both are real and both are running right now. The tools will keep changing. The notebooks are what compound.

So pick where your lessons live. Start writing them down in every agent you touch from here. It gets better because of it. See you in the next one.