Hermes Agent Fundamentals Training Course
Hermes Agent is an open-source, self-improving AI agent developed by Nous Research. Unlike coding copilots tied to an IDE, Hermes Agent resides on your infrastructure, retains knowledge across sessions, and autonomously develops skills to manage increasingly complex tasks.
This instructor-led live training (available online or onsite) targets developers and DevOps professionals aiming to leverage Hermes Agent to automate development workflows, manage infrastructure, and establish persistent AI processes.
Upon completion, participants will be able to:
- Install and configure Hermes Agent on local or remote infrastructure.
- Interact with the agent via CLI, Telegram, Discord, Slack, and WhatsApp.
- Utilize over 40 built-in tools for web search, file management, terminal commands, vision, and image generation.
- Deploy Hermes Agent using Docker, SSH, or serverless platforms such as Daytona and Modal.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice opportunities.
- Practical implementation in a live-lab environment.
Customization Options
- For customized training, please contact us to arrange your session.
Course Outline
Introduction to Hermes Agent
- Understanding Hermes Agent and its distinction from IDE copilots
- The concept of self-improving agents and closed learning loops
- Architecture overview: backends, platforms, and tools
Installation and Setup
- Installing Hermes Agent locally
- Deploying within Docker containers
- Remote deployment via SSH, Daytona, Singularity, and Modal
- Configuring API keys for OpenAI, Anthropic, OpenRouter, and Nous Portal
Interacting with the Agent
- CLI interface and essential commands
- Setting up and using the Telegram bot
- Integrating with Discord and Slack
- Establishing WhatsApp connectivity
Built-in Tools
- Web search and content extraction
- File operations: reading, writing, editing, and searching
- Executing terminal commands and bash scripting
- Image generation and vision analysis
- Text-to-speech functionality
Persistent Memory
- Cross-session memory using FTS5 recall
- LLM summarization for maintaining long-term context
- Memory search and retrieval techniques
The Skills System
- Defining skills and the creation process
- Maintaining skill persistence across sessions
- Accessing community skills and agentskills.io
MCP Integration
- Connecting to MCP servers
- Programmatically extending tool capabilities
Scheduled Automations
- Utilizing the built-in cron scheduler
- Configuring recurring tasks and reports
- Delivering automation results across platforms
Developer Automation Use Cases
- Autonomously executing terminal commands
- Spawning isolated subagents
- Managing parallel workstreams and batch processing
Security and Best Practices
- Implementing approval modes for commands and edits
- Ensuring data privacy on self-hosted infrastructure
- Maintaining environment isolation
Production Deployment
- Running Hermes Agent on a $5 VPS
- Adopting serverless deployment patterns
- Monitoring agent health and logs
Troubleshooting
- Resolving common installation issues
- Debugging tool failures
- Tuning memory and performance
Summary and Next Steps
- Recap of key capabilities
- Resources for continued learning
- Transitioning to advanced Hermes topics
Requirements
- Basic familiarity with command-line terminals and Linux commands
- Understanding of software development workflows
- General knowledge of AI and large language models
Audience
- Software developers seeking to integrate AI agents into their workflow
- DevOps engineers exploring autonomous tooling
- Technical team leads evaluating AI agent platforms
Open Training Courses require 5+ participants.
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