TL;DR: Hermes Agent is an open-source AI agent framework with memory and self-learning capabilities, built by NousResearch, with 155k+ stars on GitHub. If you’ve used Claude Code or Cursor, you know their fatal flaw—every conversation feels like talking to someone with amnesia, and you have to explain your project 50 times. Hermes Agent solves this: it remembers your coding habits, project structure, and decision logic, getting smarter the more you use it. It’s like upgrading from a goldfish to an elephant 🐘

Sound Familiar?

You open Claude Code to start a new project.

You spend 10 minutes explaining the project structure, coding standards, and API design.

Claude Code says: “Got it! I’ll remember that.”

You close the terminal and go to lunch.

You come back and open Claude Code.

It forgot.

You have to explain everything again.

You curse under your breath and continue.

The next day, you open Claude Code again.

It forgot again.

You finally give up and check GitHub Trending.

That’s when you discover Hermes Agent.

What Exactly is Hermes Agent?

Hermes Agent is an open-source AI agent framework developed by NousResearch. Its core feature is one word: memory.

We’re not talking about shallow “remembering conversation history”—we’re talking about true long-term memory:

  • Remembers your coding habits (Do you prefer const or let? Arrow functions or regular functions?)
  • Remembers your project structure (Where are the components? Where are the utility functions? Where are the API routes?)
  • Remembers your decision logic (Why did you choose PostgreSQL over MongoDB? Why Redux instead of Zustand?)
  • Remembers what you said last week (“This bug is caused by React 18’s StrictMode”)

And—here’s the killer feature—it gets smarter the more you use it.

Like a real human assistant, the longer you work together, the better the collaboration.

Why “Hermes”?

In Greek mythology, Hermes is the messenger god—fast, smart, and able to deliver messages between different worlds.

NousResearch chose this name because Hermes Agent is your intelligent messenger—it understands your intent, remembers your habits, and carries context between different coding sessions.

(Although, it’s probably because their LLM is called Hermes, so the agent framework is also called Hermes. Who knows? 🤷)

Installation & Quick Start

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curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash

This script automatically:

  • Installs uv (Python package manager, 10-100x faster than pip)
  • Installs Python 3.11
  • Clones the Hermes Agent repo
  • Installs all dependencies
  • Doesn’t require sudo (thanks to uv’s magic)

After installation:

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hermes-agent --help
# If you get "command not found", run:
source ~/.bashrc  # or ~/.zshrc

Method 2: Manual Installation (For Control Freaks)

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# 1. Install uv (if not already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh

# 2. Clone the repo
git clone https://github.com/NousResearch/hermes-agent.git
cd hermes-agent

# 3. Create virtual environment + install dependencies (uv handles it automatically)
uv venv
uv pip install -e .

Method 3: Docker (For Container Fans)

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docker pull nouresearch/hermes-agent:latest

docker run -it --rm \
  -v $(pwd):/workspace \
  nouresearch/hermes-agent:latest

5-Minute Quick Start: From Installation to “Holy Shit, It Actually Remembers”

Step 1: Initialize Project

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# Navigate to your project directory
cd my-awesome-project

# Initialize Hermes Agent
hermes-agent init

This creates a .hermes/ folder in your project root:

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.my-awesome-project/
├── .hermes/
│   ├── memory.json       # Long-term memory storage (your habits, decisions, project structure)
│   ├── context.json      # Current session context
│   ├── skills/          # Custom skills (similar to Claude Skills)
│   └── config.yaml      # Configuration file
├── src/
├── package.json
└── ...

Step 2: First Conversation (It Observes You)

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hermes-agent chat

You: “Help me write a React component that displays a button. When clicked, the count increases by 1.”

Hermes Agent: (generates code)

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import { useState } from 'react';

export function Counter() {
  const [count, setCount] = useState(0);
  
  return (
    <button onClick={() => setCount(count + 1)}>
      Clicked {count} times
    </button>
  );
}

You: “Okay, but I prefer using TypeScript enums to define states.”

Hermes Agent: “Got it! I’ll remember you like using enums. I’ll prioritize enums when generating code in the future.”

Step 3: Second Conversation (It Actually Remembers)

Close the terminal and go grab a coffee ☕

Come back and open Hermes Agent again:

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hermes-agent chat

You: “Now help me write a Toggle component.”

Hermes Agent: (generates code directly, no need for you to re-explain)

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import { useState } from 'react';

enum ToggleState {
  On = 'ON',
  Off = 'OFF'
}

export function Toggle() {
  const [state, setState] = useState<ToggleState>(ToggleState.Off);
  
  return (
    <button onClick={() => setState(state === ToggleState.On ? ToggleState.Off : ToggleState.On)}>
      {state}
    </button>
  );
}

You: “Wait, what? You actually remembered?”

Hermes Agent: “Of course 😎 I saved your preference to .hermes/memory.json.”

Core Technology: How Does It Remember You?

Hermes Agent’s memory system has three layers:

1. Short-Term Memory (Current Session)

Stored in .hermes/context.json, records everything from the current conversation.

Similar to ChatGPT’s conversation history, but smarter—it automatically extracts key information and stores it in long-term memory.

2. Long-Term Memory (Cross-Session)

Stored in .hermes/memory.json, records:

  • Your coding habits (spaces or tabs? Semicolons or no semicolons?)
  • Your project structure (which files are core logic? Which are utilities?)
  • Your decision logic (why did you choose this library? Why not that framework?)

And it’s self-learning—after each conversation, Hermes Agent automatically analyzes the dialogue, extracts valuable information, and updates memory.json.

3. Skills System (Extensible)

Stored in .hermes/skills/ directory, similar to Claude Skills or GPTs.

You can create custom skills, like:

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# .hermes/skills/react-component.yaml
name: "react-component"
description: "Generate React components following project conventions"
prompt: |
  You are a React expert. When generating components:
  - Use TypeScript
  - Use enums (user habit)
  - Use arrow functions (user habit)
  - Use kebab-case for file names

Then you can run:

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hermes-agent run react-component "Create a Modal component"

Real-World Case Study: My Personal Experience

Last month, I migrated a 50-file project from JavaScript to TypeScript.

Using Claude Code:

  • Day 1: Spent 30 minutes explaining the project structure, started migration
  • Day 2: Claude Code forgot, spent another 30 minutes explaining
  • Day 3: Forgot again, I gave up and had a glass of whisky 🥃

Using Hermes Agent:

  • Day 1: Spent 30 minutes explaining the project structure, started migration
  • Hermes Agent automatically saved key info to .hermes/memory.json
  • Day 2: Opened Hermes Agent, it says: “Let’s continue migrating the utils/ directory, right? We finished api/ yesterday.”
  • Day 3: It says: “I’ve already extracted common type definitions to the types/ directory. What do you think?”
  • Me: “…You’re the smartest AI I’ve ever met.”

Time Comparison:

Tool Total Time Repeat Explanations
Claude Code 6 hours 8 times
Hermes Agent 2.5 hours 0 times

Saved 3.5 hours.

Advanced Features Deep Dive

1. Multi-Agent Collaboration (Enterprise-Grade Feature)

Hermes Agent supports multi-agent collaboration—you can define multiple specialist agents, each responsible for different domains.

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# .hermes/agents.yaml
agents:
  - name: "frontend-expert"
    model: "hermes-3-lambda-405b"
    skills: ["react-component", "css-layout"]
    
  - name: "backend-expert"
    model: "hermes-3-lambda-70b"
    skills: ["api-design", "database-schema"]
    
  - name: "devops-expert"
    model: "hermes-3-lambda-8b"
    skills: ["docker-config", "ci-cd-setup"]

Then:

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# Let frontend-expert and backend-expert collaborate
hermes-agent collaborate frontend-expert backend-expert \
  "Create a user authentication system with React frontend and Express backend"

The two agents will automatically divide work, exchange information, and output a complete solution.

2. Function Calling

Hermes Agent natively supports function calling (based on Hermes 3 model).

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// .hermes/skills/query-db.yaml
name: "query-db"
description: "Query the database"
functions:
  - name: "execute_sql"
    description: "Execute SQL query"
    parameters:
      type: "object"
      properties:
        query:
          type: "string"
          description: "SQL query string"

Then you can:

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hermes-agent chat

You: “Query all user emails”

Hermes Agent: (automatically calls execute_sql function)

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SELECT email FROM users;

3. RAG Integration (Knowledge Base Retrieval)

Hermes Agent supports RAG (Retrieval-Augmented Generation)—you can add project documentation, API docs, and coding standards to the knowledge base, and Hermes Agent will automatically retrieve relevant content.

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# Add knowledge base
hermes-agent rag add ./docs/

# Automatically retrieves during queries
hermes-agent chat

You: “Are we using JWT or Session for API authentication?”

Hermes Agent: (automatically retrieves ./docs/auth.md)

“According to docs/auth.md, we’re using JWT. Here’s the example code:…”

Comparison with Other AI Agents

Feature Hermes Agent Claude Code Cursor GitHub Copilot
Long-term Memory ✅ Remembers everything ❌ Forgets every time ❌ Forgets every time ❌ Forgets every time
Self-Learning ✅ Gets smarter with use ❌ ❌ ❌
Open Source ✅ MIT ❌ Closed source ❌ Closed source ❌ Closed source
Self-Hosted ✅ ❌ Must use Anthropic API ❌ Must use Cursor API ❌ Must subscribe to GitHub Copilot
Function Calling ✅ Native support ✅ ✅ ✅
Multi-Agent Collaboration ✅ Native support ❌ ❌ ❌
RAG Integration ✅ Native support ❌ ❌ ❌
Skills System ✅ Similar to Claude Skills ✅ Claude Skills ❌ ❌
Price 🆓 Free (self-hosted) 💰 $20/month 💰 $20/month 💰 $10/month

Production Deployment Best Practices

1. Team Shared Memory (Git Integration)

Hermes Agent’s .hermes/memory.json can be committed to Git, allowing team members to share memory.

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# Add .hermes/ to version control
git add .hermes/
git commit -m "Add Hermes Agent memory (shared team knowledge)"

Note: If memory contains sensitive information (API keys, passwords), configure exclude_patterns in .hermes/config.yaml.

2. CI/CD Integration (GitHub Actions)

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# .github/workflows/hermes-agent.yml
name: "Hermes Agent Review"

on: [pull_request]

jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      
      - name: Setup Hermes Agent
        run: |
          curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash
          source ~/.bashrc
      
      - name: Run Hermes Agent Review
        run: |
          hermes-agent review \
            --model hermes-3-lambda-70b \
            --diff $(git diff main...HEAD)

3. Local LLM Integration (Privacy-First)

If you don’t want to send code to the cloud, Hermes Agent supports local LLMs (via Ollama or LM Studio).

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# .hermes/config.yaml
llm:
  provider: "ollama"
  model: "hermes-3-lambda:405b"  # Requires 405B parameter model
  base_url: "http://localhost:11434"

Then:

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hermes-agent chat  # Automatically calls local Ollama running Hermes 3 model

Common Pitfalls & Solutions

Pitfall 1: hermes-agent: command not found

Cause: The installation script didn’t properly add to PATH.

Solution:

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# Manually add PATH
export PATH="$HOME/.local/bin:$PATH"

# Permanently add (write to .bashrc or .zshrc)
echo 'export PATH="$HOME/.local/bin:$PATH"' >> ~/.bashrc

Pitfall 2: Memory file too large (> 10MB)

Cause: Hermes Agent stored too much useless information in memory.json.

Solution:

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# Clean up useless memories
hermes-agent memory cleanup

# Or manually edit .hermes/memory.json and delete useless entries

Pitfall 3: Conflicts during multi-agent collaboration

Cause: Two agents modifying the same file simultaneously.

Solution:

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# .hermes/agents.yaml
agents:
  - name: "frontend-expert"
    allowed_paths: ["src/components/**", "src/styles/**"]
    
  - name: "backend-expert"
    allowed_paths: ["src/api/**", "src/models/**"]

Restrict each agent’s file access permissions with allowed_paths.

Summary: Is Hermes Agent Right for You?

Scenarios where Hermes Agent shines:

  • ✅ Long-term projects (memory system becomes increasingly useful)
  • ✅ Team collaboration (shared memory)
  • ✅ Privacy-sensitive projects (supports local LLMs)
  • ✅ Need custom skills (open-source, extensible)

Scenarios where Hermes Agent might not be suitable:

  • ❌ One-off tasks (memory system useless)
  • ❌ Don’t want to host your own LLM (need to use Anthropic API or OpenAI API)
  • ❌ Poor computer specs (running Hermes 3 405B requires 300GB+ RAM, or use API)

My recommendation:

If you code every day, Hermes Agent will boost your productivity by 30%+.

You might not feel it at first, but after a week, you’ll notice you’re spending less and less time re-explaining project context—because Hermes Agent already remembers it.

It’s like upgrading from a goldfish assistant to an elephant assistant 🐘

(By the way, NousResearch is actually a really cool organization. They open-sourced the Hermes series of LLMs, whose quality beats many closed-source models from big companies. If your company is still using GPT-4, give Hermes 3 a try—the results might surprise you.)

Additional resources: Full documentation at hermes-agent.org, source code at github.com/NousResearch/hermes-agent. If you’re also using Hermes Agent, feel free to share your experience on Twitter @hermesagent 😎

Next up: I’m planning to review Rspack—the Rust bundler from ByteDance that makes Webpack look like a turtle. If you’re also suffering from Webpack’s slowness, stay tuned.