Hermes Agent: Nous Research's Self-Improving AI Agent with 17 Platform Support

Most AI agents are static – their behavior is fixed at deployment time by their system prompt and model weights. What happens when they encounter a novel situation they were not designed for? They fail, and a developer must manually update the agent. Hermes Agent from Nous Research takes a fundamentally different approach: it learns from its experiences and improves its own behavior over time, without human intervention.

Hermes Agent, available at github.com/NousResearch/hermes-agent, is a self-improving AI agent framework with support for 17 different platforms including Discord, Slack, Telegram, Twitter, and more. It uses a built-in learning loop that captures task outcomes, identifies failure patterns, and updates its own instruction set to avoid repeating mistakes. This creates an agent that gets better at its job the longer it runs.

The project builds on Nous Research’s expertise in open-source LLMs, particularly the Hermes series of fine-tuned models. Hermes Agent is designed to be model-agnostic, however, supporting multiple LLM backends including OpenAI, Anthropic, and local models through Ollama or vLLM. This flexibility, combined with the unique self-learning capability, has made it one of the most talked-about agent frameworks of early 2026.

What is Hermes Agent?

Hermes Agent is a self-improving AI agent framework developed by Nous Research. It features a built-in learning loop that captures outcomes, identifies failure modes, and updates its own behavior without human intervention. The agent supports 17 platforms including messaging apps, social media, and development tools.

How does the self-learning loop work?

The self-learning loop is Hermes Agent’s core innovation, operating as a continuous improvement cycle.

The learning loop runs asynchronously after each task completion, ensuring it does not block ongoing agent operations.

Which platforms does Hermes Agent support?

Hermes Agent supports 17 platforms through a unified adapter interface.

Each platform integration is a self-contained adapter that can be developed and tested independently.

Is Hermes Agent provider agnostic?

Yes. Hermes Agent supports multiple LLM backends and can even use different providers for different types of tasks.

# Configure with Anthropic
hermes config set provider anthropic
hermes config set anthropic.api_key sk-xxx

# Configure with local model via Ollama
hermes config set provider ollama
hermes config set ollama.model hermes-3-8b

# Configure hybrid (planning with powerful model, execution with local)
hermes config set planner.provider anthropic
hermes config set executor.provider ollama

This flexibility allows users to choose the right balance of capability, cost, and privacy.

How do you install Hermes Agent?

Installation is straightforward via pip, with platform-specific extras:

# Base installation
pip install hermes-agent

# With Discord support
pip install hermes-agent[discord]

# With all platforms
pip install hermes-agent[all]

# Initialize
hermes init
hermes run

The hermes init command creates a configuration directory where you define which platforms to connect, which LLM provider to use, and initial behavior guidelines.

Frequently Asked Questions

What is Hermes Agent?

Hermes Agent is a self-improving AI agent framework by Nous Research with a built-in learning loop. It supports 17 platforms and improves its behavior over time by learning from its own successes and failures.

How does the self-learning loop work?

After each task, the agent evaluates the outcome against success criteria, identifies the specific behavior that caused any failure, updates its instruction set to prevent recurrence, then verifies the fix on similar tasks. This runs as a non-blocking background process.

Which platforms does Hermes Agent support?

Discord, Slack, Telegram, Twitter/X, GitHub, GitLab, Email, Reddit, Notion, Linear, Jira, Confluence, Google Drive, Google Calendar, Todoist, Home Assistant, and custom HTTP APIs.

Is Hermes Agent provider agnostic?

Yes. It supports OpenAI, Anthropic, Google, Ollama, vLLM, and other providers. You can mix providers, using a powerful model for planning and a local model for execution.

How do I install Hermes Agent?

pip install hermes-agent for the base package, or pip install hermes-agent[discord] / [all] for platform support. Then run hermes init and hermes run.

Further Reading

• Hermes Agent GitHub Repository
• Nous Research Official Site
• Hermes 3 Model Series
• Self-Improving AI Agents: A Survey
• Building Multi-Platform AI Agents

flowchart TB
    A[Task Received] --> B[Plan Execution]
    B --> C{Task Complete?}
    C -->|Yes| D[Log Success]
    C -->|No| E[Identify Failure]
    E --> F[Update Instructions]
    F --> G[Retry Task]
    G --> B
    D --> H[Background Learning Loop]
    H --> I[Evaluate Outcome]
    I --> J{Improvement Possible?}
    J -->|Yes| K[Generate Instruction Update]
    K --> L[Apply to Agent]
    L --> M[Wait for Next Task]
    J -->|No| M

graph LR
    subgraph Platform Adapters
        A[Discord Adapter]
        B[Slack Adapter]
        C[GitHub Adapter]
        D[Telegram Adapter]
        E[Email Adapter]
        F[17+ More]
    end
    subgraph Core Engine
        G[Task Scheduler]
        H[Learning Loop]
        I[Memory Store]
        J[Instruction Manager]
    end
    subgraph LLM Providers
        K[OpenAI]
        L[Anthropic]
        M[Ollama]
        N[vLLM]
    end
    A --> G
    B --> G
    C --> G
    G --> K
    G --> L
    G --> M
    G --> N
    H --> I
    H --> J