Get in Touch

Course Outline

Introduction to Hermes Agent

  • Understanding what Hermes Agent is and how it differs from IDE copilots
  • The concept of a self-improving agent and the closed learning loop
  • 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 navigation and basic 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 functionalities

Persistent Memory

  • Cross-session memory capabilities using FTS5 recall
  • LLM summarization for maintaining long-term context
  • Searching and retrieving stored memories

The Skills System

  • Defining skills and the process of their creation
  • Ensuring skill persistence across different sessions
  • Exploring 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 automated reports
  • Distributing 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

  • Operating the agent on a $5 VPS
  • Implementing serverless deployment patterns
  • Monitoring agent health and reviewing logs

Troubleshooting

  • Addressing common installation issues
  • Debugging tool failures
  • Tuning memory usage and performance

Summary and Next Steps

  • Recapping key capabilities
  • Providing resources for continued learning
  • Transitioning to advanced Hermes topics

Requirements

  • Fundamental knowledge of command-line terminals and Linux commands
  • Understanding of software development workflows
  • General awareness of AI and large language models

Target Audience

  • Software developers seeking to integrate AI agents into their professional workflow
  • DevOps engineers investigating autonomous tooling solutions
  • Technical team leaders assessing AI agent platforms
 14 Hours

Number of participants


Price per participant

Upcoming Courses

Related Categories