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Course Outline
Introduction to Hermes Agent
- Understanding what Hermes Agent is and how it differs from IDE copilots.
- Exploring the concept of self-improving agents and the closed learning loop.
- Overview of architecture: backends, platforms, and tools.
Installation and Setup
- Installing Hermes Agent locally.
- Deploying on Docker containers.
- Remote deployment via SSH, Daytona, Singularity, and Modal.
- Configuring API keys for OpenAI, Anthropic, OpenRouter, and Nous Portal.
Interacting with the Agent
- Using the CLI interface and basic commands.
- Setting up and using the Telegram bot.
- Integrating with Discord and Slack.
- Establishing WhatsApp connectivity.
Built-in Tools
- Performing web searches and content extraction.
- Executing file operations: reading, writing, editing, and searching.
- Running terminal commands and bash scripting.
- Utilizing image generation and vision analysis.
- Accessing text-to-speech capabilities.
Persistent Memory
- Implementing cross-session memory with FTS5 recall.
- Using LLM summarization for long-term context management.
- Conducting memory search and retrieval.
The Skills System
- Defining what skills are and how they are created.
- Ensuring skill persistence across sessions.
- Utilizing community skills and agentskills.io.
MCP Integration
- Connecting to MCP servers.
- Programmatically extending tool capabilities.
Scheduled Automations
- Utilizing the built-in cron scheduler.
- Setting up recurring tasks and generating reports.
- Delivering automation results across various platforms.
Developer Automation Use Cases
- Running terminal commands autonomously.
- 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.
- Establishing environment isolation.
Production Deployment
- Running operations on a $5 VPS.
- Adhering to serverless deployment patterns.
- Monitoring agent health and reviewing logs.
Troubleshooting
- Addressing common installation issues.
- Debugging tool failures.
- Tuning memory and performance.
Summary and Next Steps
- Recapping key capabilities.
- Providing resources for continued learning.
- Outlining the transition 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.
Target Audience
- Software developers seeking to integrate AI agents into their workflow.
- DevOps engineers exploring autonomous tooling solutions.
- Technical team leads evaluating AI agent platforms.
14 Hours