Hermes Agent Masterclass: Build Autonomous AI Workflows

Build a real AI agent. Not a demo. An agent that runs 24/7, learns from you, and works while you sleep.

Hermes Agent is the fastest-growing AI agent framework in open source — 165,000 GitHub stars in under a year. It ships with persistent memory, a self-improving skills system, voice messaging, 53 built-in tools, a cron scheduler, multi-agent orchestration, and native integrations for Telegram, Discord, and Slack. And until now, there has been exactly zero courses on how to use it.

This course changes that.

In about two hours you will go from zero to a fully operational autonomous AI agent deployed to the cloud, connected to your messaging apps, remembering your preferences across every session, and running scheduled tasks automatically — without you lifting a finger.

WHAT MAKES HERMES DIFFERENT FROM EVERY OTHER AGENT FRAMEWORK

Most agent tools are stateless — every conversation starts from scratch. Hermes has a closed learning loop: when it solves a complex task, it writes a skill so it can do it faster next time. It builds a persistent model of who you are. It updates its own memory. The more you use it, the better it gets at your specific work. This is a course about deploying a production AI agent you will actually use every day.

WHAT YOU'LL BUILD

• A Hermes Agent deployed on Railway (one-click template — live in minutes)

• Telegram, Discord, and Slack integrations from a single agent instance

• Voice message support — talk to your agent, get a reply, no extra setup

• Persistent memory across sessions — your agent remembers you

• Custom skills you write in plain markdown — teach your agent new workflows

• A cron job that delivers an AI news briefing to your Telegram every morning

• A multi-agent Kanban pipeline: spec → implement → review, fully coordinated

• MCP integration — connect Hermes to GitHub (and any other MCP server)

DEPLOY-FIRST PHILOSOPHY

By the end of Section 2, your agent is live on the internet. Every section after that adds a new capability on top of a working system. You are never stuck in setup purgatory waiting to build something real.

WHAT'S COVERED SECTION BY SECTION

Section 1 — Introduction: What you're building, how Hermes works, the self-improving learning loop, and a practical security framework for what to trust your agent with.

Section 2 — Deploy on Railway: One-click deploy with the course template, DeepSeek v4 setup, first conversation via CLI and TUI.

Section 3 — Messaging: Telegram (with voice), Discord, and Slack — step-by-step setup for all three.

Section 4 — The Self-Improving Agent: How the memory + skills + user modeling loop works, and a live demo of Hermes creating its own skill.

Section 5 — Tools: Tour of the 53 built-in tools, Docker isolation for safe terminal execution.

Section 6 — Memory: MEMORY md and USER md, cross-session persistence, session search.

Section 7 — Skills: How skills work, installing from the community hub, writing your first skill in markdown, advanced sharing with taps.

Section 8 — Cron: Schedule jobs in natural language, attach skills, deliver to Telegram.

Section 9 — MCP: Connect Hermes to GitHub (or any MCP server) with a practical walkthrough.

Section 10 — Kanban: Multi-agent task orchestration — the board, dependencies, structured handoffs, crash recovery.

Section 11 — OpenClaw: How OpenClaw compares to Hermes and when to reach for one vs. the other.

WHO THIS COURSE IS FOR

This course is for developers and AI enthusiasts who are comfortable with a terminal and want to go beyond chatbots. You do not need prior experience with agent frameworks. You do need a willingness to build something real, not just follow along.

If you've used ChatGPT or Claude and thought "I wish this worked for me automatically, without me having to ask" — this is how you build that.