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Course Outline
Getting Started with Hermes Agent
- Definition of Hermes Agent and its distinction from IDE copilots
- The concept of self-improving agents and the closed learning loop
- Architectural overview: backends, platforms, and toolsets
Installation and Configuration
- Local installation procedures for Hermes Agent
- Deployment using 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 core commands
- Setting up and using Telegram bots
- Integration with Discord and Slack
- Establishing WhatsApp connectivity
Integrated Tools
- Web search and content extraction capabilities
- File management: reading, writing, editing, and searching
- Executing terminal commands and bash scripts
- Image generation and visual analysis
- Text-to-speech functionality
Persistent Memory
- Cross-session memory utilizing FTS5 recall
- LLM-based summarization for long-term context retention
- Memory search and retrieval mechanisms
The Skills Framework
- Definition of skills and their creation process
- Retaining skills across multiple sessions
- Community contributions and agentskills.io
MCP Integration
- Establishing connections to MCP servers
- Programmatically expanding tool capabilities
Scheduled Automations
- Using the built-in cron scheduler
- Configuring recurring tasks and automated reports
- Cross-platform distribution of automation outcomes
Automation Use Cases for Developers
- Autonomous execution of terminal commands
- Creating isolated subagents
- Managing parallel workstreams and batch processing
Security and Best Practices
- Implementing approval modes for commands and edits
- Maintaining data privacy on self-hosted infrastructure
- Ensuring environment isolation
Production Deployment
- Operating on a $5 VPS
- Serverless deployment strategies
- Monitoring agent health and reviewing logs
Troubleshooting
- Addressing common installation challenges
- Debugging tool-related failures
- Optimizing memory and performance
Conclusion and Future Directions
- Review of core capabilities
- Resources for ongoing professional development
- Progression to advanced Hermes topics
Requirements
- Fundamental understanding of command-line interfaces and Linux operations
- Knowledge of standard software development processes
- General awareness of AI and large language models
Target Audience
- Software developers aiming to incorporate AI agents into their daily workflows
- DevOps engineers investigating autonomous tooling solutions
- Technical leads assessing AI agent platforms
14 Hours
