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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

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