New Course: Build Persistent Agents with Hermes Agent
Summary
A new course, "Hermes Agent 101: Persistent Agents, Memory, Skills, and Real Workflows," has been released, focusing on Hermes Agent, a platform designed to overcome the limitations of session-based AI assistants. Unlike temporary chat windows, Hermes enables building persistent agents with identity, memory, skills, profiles, messaging interfaces, and scheduled jobs, making them more useful across repeated developer and research workflows. The course includes a 3-hour practical video, a 150-page companion document, step-by-step setup instructions, and over 70 diagrams. It covers practical developer and research workflows, Telegram integration, and cron-based scheduled tasks. A 30% launch week discount is available using code VBG93V1.
Key takeaway
For AI Engineers and Researchers building complex, multi-session workflows, this course offers a structured approach to developing persistent AI agents using Hermes Agent, moving beyond temporary chat windows. You will learn to define agent identity, manage memory, create skills, and integrate messaging/scheduled tasks, enabling agents to evolve and become more useful over time. Consider utilizing the 30% launch discount (code: VBG93V1) to acquire these capabilities.
Key insights
Hermes Agent enables building persistent AI agents that retain identity, memory, and skills across sessions for complex workflows.
Principles
- Agents can have persistent identity.
- Memory and skills improve agent utility.
- Scheduled tasks enable automation.
Method
Define agent identity with `SOUL.md`, manage memory, create profiles, capture workflows as skills, and integrate messaging/scheduling for persistent, evolving agents.
In practice
- Use `SOUL.md` for agent identity.
- Integrate Telegram for messaging.
- Schedule tasks with Hermes cron.
Topics
- Hermes Agent
- Persistent AI Agents
- Agent Memory
- Agent Skills
- Workflow Automation
- AI Development
- Cron Scheduling
Best for: AI Engineer, AI Scientist, AI Student
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Editorial summary, takeaway, and curation by AIssential. Original article published by To Data & Beyond.