Hermes Agent: Build A Self-Improving Ai Agent
Published 5/2026
Created by Arnold Oberleiter
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 50 Lectures ( 6h 4m ) | Size: 6.51 GB
Create OpenClaw-style agents with MCP, skills, Ollama, Docker, VPS, Telegram, Claude Code, automation and Obsidian RAG
What you'll learn

Learn how to install, run, customize, extend, and use Hermes Agent in real AI agent workflows

Hermes Agent Foundations: Understand what Hermes Agent is, how the harness architecture works, and why it matters for open-source AI agents

Installation & Setup: Install Hermes locally, on a VPS, in Docker, or on Windows with WSL2 Ubuntu

LLM & Telegram Setup: Configure language models, connect Telegram, and prepare Hermes for real remote-control workflows

Hermes Commands & Dashboard: Use basic Hermes commands, switch models, manage sessions, and work with the Hermes dashboard

Browser Automation: Test Hermes with tools and browser automation to understand how agents interact with external systems

Agent Onboarding: Configure your agent with user file and teach Hermes important context about you, your work, and your workflows

Memory & Personality: Manage user file, memory, and soul file to create a more personalized AI assistant

Context Management: Save tokens, manage sessions, and understand how Hermes handles context in longer workflows

Skills System: Understand how Hermes skills work and how they allow your agent to perform reusable tasks

Custom Hermes Skills: Build your own skills and extend Hermes with custom capabilities

Self-Improving Skills: Create Hermes skills that can improve over time through research, feedback, and iteration

Slash Commands & Permissions: Use Hermes slash commands, reasoning options, and permissions safely in real projects

Cron Jobs & Scheduled Tasks: Automate recurring work with Hermes using cron jobs and scheduled agent workflows

Voice Mode: Enable speech input and output to interact with Hermes through voice with Elevenlabs

Manage server files with VS Code and SSH while working with Hermes on a remote machine

MCP Integration: Connect Hermes Agent to external tools and systems using the Model Context Protocol

Supabase & SQL Workflows: Build an MCP server example with Supabase and SQL for database-connected agent workflows

Plugins: Bundle skills, tools, hooks, and CLIs into reusable Hermes plugins

Hooks & Logging: Use hooks to automate workflows, trigger actions, and create better logging for your agent

CLI Integration: Connect Hermes to command-line tools like the GitHub CLI for more powerful developer workflows

ComfyUI Automation: Use Hermes skills to automate and manage ComfyUI workflows

RL Training & LoRA Creation: Understand how Hermes can be used in reinforcement learning workflows and LoRA creation

Subagents & Parallel Agents: Use subagents, multi-agent delegation, and parallel agent workflows for more complex tasks

Kanban-Based Agent Workflows: Organize and delegate work with Kanban boards and agent task management

Hermes for Coding: Monitor repositories, delegate coding tasks, and connect Hermes with Claude Code, Codex, and Claude Design

Hermes for Video Editing: See how Hermes can support video editing workflows, including how an agent helped edit this course

Email & Calendar Automation: Manage emails, calendar workflows, and thousands of apps using the Zapier MCP

Smart Home Automation: Use Hermes as a smart home assistant to control devices, cameras, and automations

Obsidian & LLM Wiki: Build knowledge workflows with Obsidian, Claude Code, Hermes Agent, and RAG-style databases

Local Models with Ollama: Connect Hermes to local models using Ollama for more private and flexible AI workflows

Real AI Agent Use Cases: Apply Hermes to fitness, nutrition, research, coding, automation, personal assistance, and creative workflows

AI Agent Security: Understand jailbreaks, prompt injections, tool poisoning, MCP rug pulls, and hidden risks in agentic systems

Permissions & Safe Usage: Learn how to think about safety when giving AI agents access to files, tools, APIs, terminals, and external systems

OpenClaw-Style Agent Workflows: Build and run Hermes workflows similar in spirit to OpenClaw, but with your own setup and tools
Requirements

Basic understanding of AI, APIs, Tokens, and a willingness to use the Command Line (Terminal) is required.
Description
Hermes Agent: Build a Self-Improving Open-Source AI Agent
Hermes is an open-source AI agent that grows with you.
Similar in spirit to OpenClaw, it can run on your computer or server, use tools, execute commands, automate workflows, manage memory, connect to external apps, and work with systems like Telegram, MCP, Ollama, Supabase, GitHub, Claude Code, Codex, ComfyUI, Obsidian, and more.
In this course, you will learn how to install Hermes, configure it, extend it with skills, connect it to tools, automate real workflows, and build self-improving agent systems that can support you in research, coding, productivity, content creation, and personal automation.
This is not a course about simple prompting tricks.
It is a practical, project-based course for people who want to understand how modern AI agents actually work - including tools, skills, memory, permissions, plugins, hooks, MCP servers, local models, subagents, scheduled tasks, and security.
What You Will Build and Learn
The course starts from zero.
First, you will learn what Hermes Agent is, how the harness works, how the architecture is structured, and why Hermes is different from a normal chatbot.
Then you will install Hermes in different ways

locally on Mac, Linux, or Windows with WSL2

on a VPS server

inside a Docker container

on a separate device or sandbox environment
You will configure LLMs, connect Telegram, use the Hermes dashboard, switch models, run basic commands, and understand how to work with Hermes in a real setup.
Hermes Agent Foundations
You will learn the core concepts behind Hermes Agent

installation options and setup workflows

VPS setup with Docker

Windows setup with WSL2 Ubuntu

local installation on Mac, Linux, and Windows

basic Hermes commands

model switching

dashboard usage

documentation structure

the Hermes harness and agent architecture
By the end of this part, you will have Hermes running and understand how the system is built.
Practical Hermes Workflows
After the setup, you will move into real usage.
You will test Hermes with browser automation, manage files on a VPS with VS Code and SSH, onboard your agent, work with the user file, manage memory, customize personality with soul file, and use context management to save tokens.
You will also learn

how Hermes uses tools

how skills work

how to manage permissions

how slash commands work

how to run scheduled tasks with cron jobs

how to enable voice input and output

how to use Hermes as a more personal AI assistant
This turns Hermes from a terminal-based AI tool into a practical agent you can actually use.
Advanced Hermes Agent Systems
The course then moves into more advanced agent workflows.
You will learn how to create your own Hermes skills, build self-improving skills, automate ComfyUI workflows, connect MCP servers, work with Supabase and SQL, bundle tools with plugins, use hooks for automation and logging, and integrate command-line tools like the GitHub CLI.
You will also explore reinforcement learning workflows, LoRA creation, and more advanced ways to extend Hermes beyond the default setup.
Topics include

custom Hermes skills

self-improving skills

ComfyUI automation

MCP server integration

Supabase and SQL

plugins

hooks

CLI integrations

GitHub CLI

reinforcement learning

LoRA creation
Hermes Pro Workflows and Real Use Cases
In the pro section, you will see how Hermes can be used in more complex workflows.
You will explore use cases for fitness and nutrition, email and calendar management, smart home control, video editing, coding, repo monitoring, subagents, multi-agent delegation, Kanban boards, Obsidian, RAG-style knowledge systems, local models with Ollama, and automation through Zapier MCP.
You will learn how Hermes can connect to larger AI systems and work together with tools like Claude Code, Codex, Claude Design, Obsidian, Ollama, and MCP servers.
Use cases include

Hermes as a personal assistant

Hermes for video editing workflows

Hermes for email and calendar automation

Hermes with Zapier MCP and thousands of apps

Hermes as a smart home assistant

Hermes for coding and repo monitoring

Hermes with Claude Code, Codex, and Claude Design

subagents and multi-agent delegation

Kanban-based task management

Obsidian and LLM wiki workflows

RAG-style knowledge databases

local models with Ollama
AI Agent Security
Powerful AI agents are useful, but they also introduce new risks.
That is why the final section covers important security topics for AI agents, including jailbreaks, prompt injections, tool poisoning, MCP rug pulls, hidden instructions, unsafe permissions, and the risks of giving agents access to files, APIs, terminals, tools, and external systems.
You will learn what can go wrong, what to watch out for, and how to think more carefully when building and using agentic systems.
By the End of This Course
By the end of the course, you will understand how to install Hermes Agent, configure it, connect it to tools, customize its memory and personality, build your own skills, automate tasks, work with MCP servers, use plugins and hooks, run scheduled jobs, connect external apps, use local models, delegate work to subagents, and think more clearly about AI agent security.
Hermes Agent should no longer feel like a mysterious open-source project.
It should feel like a practical AI agent system you can run, control, extend, and use for real work.
If you want to stop using AI only as a chatbot and start building your own open-source AI agent workflows with Hermes Agent, this course gives you the practical roadmap.
Who this course is for

Anyone who wants to stop using AI only as a chat window and start building practical open-source AI agents with Hermes Agent

AI Builders & Automation Creators who want to build real AI agent workflows instead of only using AI as a chatbot

Developers & Technical Freelancers who want to run, customize, and extend open-source AI agents with tools, skills, MCP, CLIs, and automation

Workflow Automation Experts who want to connect AI agents with apps, APIs, Telegram, Zapier MCP, databases, and real business workflows

Open-Source AI Enthusiasts who want to understand Hermes Agent, OpenClaw-style agents, local models, Ollama, Docker, VPS setups, and self-hosted AI systems

Content Creators & Knowledge Workers who want to use AI agents for research, video workflows, Obsidian knowledge systems, RAG, and personal productivity

Solopreneurs & Indie Hackers who want to create their own digital AI assistant that can help with coding, automation, research, file management, and daily work

Students & Beginners with technical curiosity who want to learn modern AI agent concepts step by step, from installation to advanced workflows
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