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Duration 14 hours
Course Outline
Introduction to Hermes Agent
- Defining Hermes Agent and its distinction from IDE-integrated copilots
- The concept of self-improving agents and the closed learning loop
- Architectural overview: backends, supporting platforms, and available tools
Installation and Configuration
- Local installation of Hermes Agent
- Deployment within Docker containers
- Remote deployment via SSH, Daytona, Singularity, and Modal
- Configuration of API keys for OpenAI, Anthropic, OpenRouter, and Nous Portal
Agent Interaction
- CLI interface navigation and fundamental commands
- Setting up and using the Telegram bot
- Integrations with Discord and Slack
- Establishing connectivity via WhatsApp
Native Toolset
- Web searching and content extraction
- File handling: reading, writing, editing, and searching
- Executing terminal commands and bash scripting
- Generating images and performing vision analysis
- Text-to-speech functionality
Long-Term Memory
- Cross-session memory utilization with FTS5 recall
- LLM-based summarization for extended context retention
- Memory searching and data retrieval
The Skills Framework
- Understanding what skills are and how they are generated
- Persisting skills across different sessions
- Accessing community skills and the agentskills.io repository
MCP Integration
- Connecting to Model Context Protocol (MCP) servers
- Programmatically extending tool capabilities
Scheduled Automations
- Utilizing the built-in cron scheduler
- Configuring recurring tasks and automated reports
- Distributing automation results across multiple platforms
Developer Automation Scenarios
- Autonomous execution of terminal commands
- Creating isolated subagents
- Managing parallel workstreams and batch processing
Security and Best Practices
- Approval mechanisms for command execution and edits
- Maintaining data privacy on self-hosted infrastructure
- Implementing environment isolation
Production Environments
- Operating on low-cost VPS instances (e.g., $5/month)
- Applying serverless deployment patterns
- Monitoring agent health and analyzing logs
Troubleshooting
- Addressing common installation challenges
- Diagnosing and resolving tool failures
- Optimizing memory usage and performance
Wrap-Up and Future Directions
- Summary of core capabilities
- Resources for further education
- Pathways to advanced Hermes Agent topics
Requirements
- Foundational knowledge of command-line terminals and Linux utilities
- Comprehension of standard software development processes
- General understanding of AI concepts and large language models
Target Audience
- Software developers aiming to incorporate AI agents into their daily workflows
- DevOps engineers investigating autonomous tooling options
- Technical team leads assessing AI agent platforms for adoption
