Hermes Agent: Build a Self-Improving AI Agent

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.