{"slug": "hermes-agent-the-open-source-ai-that-never-forgets-and-actually-learns", "title": "Hermes Agent: The Open-Source AI That Never Forgets (and actually Learns)", "summary": "Nous Research has released Hermes Agent, an open-source AI agent framework designed to run continuously on personal servers or VPS with persistent memory and a closed learning loop. The system, released in 2026, automatically creates reusable \"skills\" from completed tasks to improve future performance, supports over 20 communication platforms, and can execute scheduled workflows and parallel sub-agents. Hermes Agent is model-agnostic, operates under the MIT License, and stores all data locally on the user's machine by default.", "body_md": "*This is a submission for the Hermes Agent Challenge*\n\nAI agents extend traditional LLMs by combining reasoning, memory, and tools to execute tasks autonomously. Instead of only generating responses, they can interact with external systems, maintain context across sessions, and perform multi-step workflows with minimal supervision.\n\nWith dozens of agent frameworks appearing over the past year, the real differentiator is no longer whether an agent can use tools or browse the web—it's how effectively it learns, remembers, and improves over time.\n\nThat is where Hermes Agent stands out.\n\nHermes Agent is an open-source, autonomous, and self-improving AI agent framework developed by Nous Research. Released in 2026, it is designed to run continuously on a personal server or VPS, functioning as a persistent AI assistant that becomes more effective over time.\n\nUnlike many AI assistants that reset context between sessions, Hermes is built around long-term memory, continuous learning, and autonomous execution.\n\n**Repository:**\n\n[[https://github.com/HermesAgent/hermes](https://github.com/HermesAgent/hermes)]\n\nMany AI tools act as conversational interfaces layered on top of language models. Hermes takes a different approach.\n\nIts defining feature is a **closed learning loop**—a system that enables the agent to learn from completed tasks, store successful solutions, and improve future performance without requiring repeated instruction.\n\nInstead of simply responding to prompts, Hermes evolves alongside the user.\n\n**1. Built-In Learning Loop**\n\nMost AI assistants lose context once a conversation ends. Hermes preserves successful solutions by automatically creating reusable code, workflows, and documentation known as **skills**.\n\nWhen a similar task appears in the future, Hermes can reuse these skills instead of solving the problem from scratch.\n\n*Benefit:*\n\nThe agent becomes more capable the longer it is used.\n\n**2. Ultra-Persistent Memory**\n\nHermes maintains long-term contextual memory, including:\n\nThis allows the agent to provide continuity across days, weeks, or even months without requiring repeated explanations.\n\n*Benefit:*\n\nA more personalized and efficient experience.\n\n**3. Multi-Platform Access**\n\nHermes is not restricted to a single dashboard or application.\n\nIt can communicate through more than 20 platforms, including:\n\nFor example, a task can be started from a mobile device via Telegram and continued later from a desktop terminal.\n\n*Benefit:*\n\nFlexible access from virtually anywhere.\n\n**4. Scheduled Automation**\n\nHermes includes a natural-language scheduling system that enables fully automated workflows.\n\nExamples include:\n\n*Benefit:*\n\nRoutine work can be performed without manual intervention.\n\n**5. Parallel Sub-Agents**\n\nFor large-scale workloads, Hermes can create independent sub-agents that operate simultaneously on separate tasks.\n\nThis allows multiple workflows to run in parallel without disrupting the primary conversation history.\n\n*Benefit:*\n\nImproved scalability and task throughput.\n\n**Architecture and Technical Capabilities**\n\nHermes is designed to be model-agnostic, extensible, and privacy-focused.\n\n**Model Compatibility**\n\nHermes supports a wide range of AI providers and deployment options, including:\n\nThis flexibility allows users to choose the model that best fits their requirements.\n\n**Execution Environments**\n\nHermes can safely execute commands across multiple environments, including:\n\n*Benefit:*\n\nGreater control over where and how tasks are executed.\n\n**Web Automation and Tooling**\n\nOut of the box, Hermes supports:\n\nThese capabilities enable the agent to interact directly with digital environments.\n\n**Privacy and Security**\n\nHermes is released under the MIT License and is designed with privacy in mind.\n\nKey characteristics include:\n\nBy default, data is stored on the user's own machine or server under:\n\n~/.hermes/\n\n*Benefit:*\n\nUsers retain full ownership and control of their information.\n\n*Machine Learning and MLOps Support*\n\nHermes includes features aimed at developers and researchers, such as:\n\n*Benefit:*\n\nUseful for both production deployments and AI research workflows.\n\n**Getting Started**\n\nBecause Hermes is self-hosted, setup is typically performed through a terminal.\n\n**Step 1: Install**\n\nRun the official installation script:\n\n```\ncurl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash\n```\n\n**Step 2: Configure**\n\nLaunch the setup wizard:\n\n```\nhermes setup\n```\n\n**Step 3: Connect and Use**\n\n**What I built in 10 minutes**\n\nTo test Hermes for real, I spun up a cheap $6 VPS, installed the agent, and gave it a single natural-language task:\n\n*\"Every morning at 8 AM UTC, fetch the top post from Hacker News, summarize it in two sentences, and append the result to a file called daily-digest.md\"*\n\n**No cron jobs. No Python scripts. Just that prompt.**\n\nHermes figured out the rest: it scheduled itself, fetched the page, called an LLM for the summary, and wrote to the file. The next morning, the file was there.\n\nThat's when I stopped thinking of Hermes as \"another agent framework\" and started seeing it as a persistent teammate. It didn't just answer a question – it performed a recurring job without me touching it again.\n\n**Final Thoughts**\n\nHermes Agent represents a new generation of AI assistants. Rather than acting as a temporary chatbot, it functions as a persistent, self-improving system that learns from experience, develops reusable skills, and maintains long-term memory.\n\nIts combination of autonomous operation, privacy-first design, multi-platform accessibility, and continuous learning makes it a compelling framework for individuals, developers, and organizations seeking a truly adaptive AI assistant.\n\nAs AI agents continue to evolve, Hermes offers a practical glimpse into what long-term human–AI collaboration may look like.\n\n\"Have you tried Hermes or another persistent agent framework? What tasks would you automate first? Let me know in the comments – I'd love to compare notes.\"\n\n\"This post is my submission for the Hermes Agent Challenge on DEV.to.", "url": "https://wpnews.pro/news/hermes-agent-the-open-source-ai-that-never-forgets-and-actually-learns", "canonical_source": "https://dev.to/devyay/hermes-agent-the-open-source-ai-that-never-forgets-and-actually-learns-3nag", "published_at": "2026-05-30 00:57:21+00:00", "updated_at": "2026-05-30 01:12:01.318174+00:00", "lang": "en", "topics": ["ai-agents", "artificial-intelligence", "machine-learning", "ai-tools"], "entities": ["Hermes Agent", "Nous Research", "HermesAgent/hermes"], "alternates": {"html": "https://wpnews.pro/news/hermes-agent-the-open-source-ai-that-never-forgets-and-actually-learns", "markdown": "https://wpnews.pro/news/hermes-agent-the-open-source-ai-that-never-forgets-and-actually-learns.md", "text": "https://wpnews.pro/news/hermes-agent-the-open-source-ai-that-never-forgets-and-actually-learns.txt", "jsonld": "https://wpnews.pro/news/hermes-agent-the-open-source-ai-that-never-forgets-and-actually-learns.jsonld"}}