Even AI needs Hermès! What is OpenClaw: Hermes Agent, which can evolve on its own?

In 2026, as competition among AI agents heats up rapidly, the open-source project Hermes Agent released by Nous Research is becoming a community focal point, built around the core narrative of “an agent system that grows with the user.” Connecting Telegram and Slack features, integrating AI models, and more are similar to OpenClaw, but unlike traditional chatbots, Hermes Agent is positioned as a “persistent Agent operation layer.”

Its design core lies in long-term operation and capability accumulation: the agent can not only execute tasks, but also convert successful experiences into reusable skills, and continuously optimize the decision-making process through a memory system, gradually building an understanding of the user’s behavior and preferences.

This “closed learning loop” is Hermes Agent’s key difference. After a task is completed, the system automatically organizes the workflow, generates a skills file, and directly calls and optimizes it in later similar scenarios. Paired with a long-term memory mechanism based on SQLite and full-text search (FTS5), it has the ability to carry over across conversations, so you don’t have to start from scratch every time.

Cybersecurity expert Yu Cosine says it’s very easy to use. If you already have OpenClaw and run Hermes Agent on the same device, you can import OpenClaw’s configuration and memory into Hermes Agent. In terms of usage, after Hermes Agent fixes a Telegram vulnerability, it automatically creates a Skill. Even in terms of feel, using Hermes Agent with GPT 5.4 is better than using OpenClaw. Features like showing the Tokens used and more also go beyond Claude Code.

Closed learning loop — the key difference with Hermes Agent

Unlike traditional chatbots or IDE assistant tools, Hermes Agent is positioned as a “persistent Agent operation layer.” Its design core lies in long-term operation and capability accumulation: the agent can not only execute tasks, but also convert successful experiences into reusable skills, and continuously optimize the decision-making process through a memory system, gradually building an understanding of the user’s behavior and preferences.

This “closed learning loop” is Hermes Agent’s key difference. After a task is completed, the system automatically organizes the workflow, generates a skills file, and directly calls and optimizes it in later similar scenarios. Paired with a long-term memory mechanism based on SQLite and full-text search (FTS5), it has the ability to carry over across conversations, so you don’t have to start from scratch every time.

Upgraded OpenClaw: What’s special about Heremes Agent

In its deployment architecture, Hermes Agent clearly moves toward “de-localization.” The system can run on VPS, Docker, cloud, or serverless environments, and connects multiple platforms—Telegram, Discord, Slack, WhatsApp, and more—through a single gateway, so users can interact with the agent anytime, while tasks continue to run in the backend. This design shifts AI from “a tool” to “a persistent digital workforce.”

On the model layer, Hermes adopts a fully open strategy, supporting a wide range of inference engines including OpenAI, OpenRouter (200+ models), GLM, Kimi, MiniMax, and more, and even allows integration with self-hosted model endpoints. Users can switch models with simple commands, avoiding vendor lock-in issues.

Hermes Agent breaks complex tasks into parallel workflows

Hermes Agent comes with more than 40 built-in tools, covering web search, browser automation, code execution, and multimedia generation, and supports MCP (Model Context Protocol) extensions. The system also has scheduling capabilities, allowing users to set recurring tasks in natural language—for example, automatically generating reports or running backups.

A sub-agent mechanism allows complex tasks to be split into parallel workflows, each running independently, improving efficiency and reducing context costs. This means Hermes is not just a single assistant—it’s closer to a scalable automation system.

Currently, Hermes Agent has accumulated more than 39k stars on GitHub, making it one of the most talked-about open-source AI Agent frameworks in 2026. The market often compares it to tools like OpenClaw, but compared to systems that rely on manually designed skills, Hermes places more emphasis on the agent’s self-evolution capabilities.

Even this article about AI wants to be like Hermes! Self-evolving OpenClaw: What is Hermes Agent? First appeared on Lian News ABMedia.