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Instructor-led training / ai-agentic-herme

Persistent Daemons: Building Continuous AI Agents with Hermes

Learn to build self-improving, continuous background AI agents with Hermes Agent featuring cross-session memory and multi-channel messaging integration.
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Instructor-led

ai-agentic-herme

Duration
1 Days
Format
Live Online
Access
Multiple Timezones

Overview

About this course.

This hands-on workshop dives into building persistent daemon agents using Hermes Agent. Participants learn how to deploy open-source, self-improving background agents designed for continuous execution, cross-session memory accumulation, and real-time messaging integrations. The course focuses on building production-ready long-running processes, using a primary messaging interface (Telegram/Slack) in class alongside boilerplate templates for additional platforms.

Objectives

What you'll learn

  • Understand the architecture of continuous, background persistent AI daemons.
  • Implement cross-session memory and automated skill accumulation in Hermes Agent using persistent storage.
  • Connect and route agent interactions via webhook and socket interfaces using Python and asyncio.
  • Deploy, process-manage, and safeguard continuous self-improving background agents against rate limits and failures.

Audience

Who it's for

  • Software Engineers
  • Backend Developers
  • AI System Engineers

Prerequisites

Before you start

  • Proficiency in Python (including async/await constructs)
  • Basic understanding of REST APIs, Webhooks, and environment configuration
  • Local Docker environment and ngrok (or equivalent tunnel) installed
  • API keys for primary LLM providers (e.g., OpenAI, Anthropic)

Outline

Course outline.

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1. Foundations of Persistent Daemons & Hermes Agent

  • Introduction to Persistent Daemons: Transitioning from ephemeral request-response pipelines to continuous background execution.
  • Hermes Agent Core Architecture: Deconstructing background workers, event triggers, and state loops.
  • Setting Up the TUI Interface: Local deployment, terminal controls, and initial daemon configuration.

2. Cross-Session Memory & Skill Accumulation

  • Implementing Long-Term State: Configuring persistent vector and key-value memory stores across execution cycles.
  • Self-Improving Loops: Mechanizing skill acquisition, feedback processing, and memory indexing.
  • Hands-on Lab: Building an autonomous Python agent that retains contextual knowledge across user sessions.

3. Multi-Channel Messaging Integrations

  • Connecting External Messaging Platforms: Setting up primary webhook integration (e.g., Telegram or Slack).
  • Unified Event Handling: Routing multi-channel inputs and managing concurrent user sessions using boilerplate templates.
  • Hands-on Lab: Deploying a Hermes daemon that routes messages and manages real-time interactions.

4. Deployment, Reliability & Autonomous Execution

  • Daemonization & Process Management: Running agents reliably as system background services using Systemd and Docker containers.
  • Error Recovery & Guardrails: Handling API rate limits, network disruptions, and malformed payloads.
  • Capstone Project: Refactoring and daemonizing the multi-channel agent built in Labs 2 and 3 into a self-improving background monitor.

For teams

Training a whole team?

Request private training for Persistent Daemons: Building Continuous AI Agents with Hermes and we'll follow up with a quote for your group.

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