Hermes Agent’s Insane New Update Just Broke OpenClaw

Key Concepts

• Hermes Agent: An open-source AI agent framework focused on self-improvement, local-first infrastructure, and procedural memory.
• Open Claw: A previously dominant, widely integrated AI agent platform serving as the primary benchmark for Hermes.
• Do-Learn-Improve Loop: A core design philosophy where the agent reflects on completed tasks to generate reusable "skill files."
• Tenacity (v0.13): A major update to Hermes featuring a durable multi-agent Kanban system and hallucination recovery.
• AIOS (AI Operating System): The evolution of agents from simple chatbots into systems that manage files, code, and workflows directly on a user's machine.
• MCP (Model Context Protocol): A standard allowing agents to connect to external tools and media production pipelines (e.g., Higgsfield).
• Model-Agnosticism: The ability to run Hermes across various providers (OpenRouter, Anthropic, OpenAI, Ollama, etc.) to optimize costs and performance.

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1. Market Dynamics and Growth

Hermes Agent has rapidly emerged as a primary competitor to Open Claw. As of May 10, 2026, Hermes surpassed Open Claw on OpenRouter’s global daily rankings, processing approximately 224 billion tokens per day compared to Open Claw’s 186 billion.

• Velocity: Launched in February 2026 by Nous Research, Hermes reached 147,000 GitHub stars in under 90 days.
• Developer Sentiment: While Open Claw maintains a larger historical footprint (370,000+ stars, 9 trillion cumulative tokens), Hermes’s rapid ascent suggests it is better aligned with current developer needs for adaptive, self-improving tools.

2. Core Methodology: The "Do-Learn-Improve" Loop

Unlike traditional assistants that reset context with every new task, Hermes is designed to compound knowledge:

• Procedural Knowledge: After completing a task, the agent reflects on the process and writes a "skill file" (markdown-based). This allows the agent to perform repeated workflows more efficiently over time.
• Layered Memory System:
  • Session Memory: For immediate, ongoing tasks.
  • Episodic Memory: Utilizes SQLite/SQLite FTS 5 to search through past sessions.
  • Procedural Memory: The library of reusable skills generated by the agent.

3. Technical Infrastructure and "Tenacity" Update

The release of version 0.13 ("Tenacity") marked a shift toward enterprise-grade reliability:

• Durable Kanban System: Manages multiple agents/workers with heartbeat monitoring, retry budgets, and "zombie worker" reclamation.
• Hallucination Recovery: Mechanisms to detect when an agent loses the thread or gets stuck in a loop.
• Goal Persistence: The /goal command ensures the agent remains anchored to a long-term objective, preventing distraction by intermediate, short-term steps.
• Local-First Design: The project is MIT-licensed and designed to run on local machines, VPS, or private cloud environments, ensuring data sovereignty and avoiding vendor lock-in.

4. Integration and Ecosystem

• Higgsfield MCP: A notable integration that allows Hermes to move beyond text-based reasoning into creative execution (generating videos, ads, and landing pages).
• Workflow Orchestration: Hermes can orchestrate multiple agents—one for analytics, one for creative generation, and one for email outreach—creating a closed-loop production pipeline.
• Migration Path: Hermes includes a Hermes Claw migrate command, allowing users to import settings, memories, and API keys directly from Open Claw, significantly lowering the barrier to switching.

5. Security and Safety

Both platforms face challenges regarding security. Open Claw has dealt with high-severity CVEs and malicious entries in its skill repository. Hermes, while younger, addressed several security vulnerabilities in the Tenacity update, including:

• Redaction defaults.
• Role allow-lists.
• Stranger rejection and authentication flow hardening.

6. Synthesis and Conclusion

The rise of Hermes signals a fundamental shift in the AI agent market: the transition from "chat-based" assistants to "agentic operating systems."

Key Takeaways:

• Adaptability over Reach: While Open Claw focused on broad platform integrations (Telegram, Slack, etc.), Hermes is winning by focusing on deep, self-improving workflows.
• Visibility: The move toward interfaces like the Ion UI and Kanban boards reflects a growing need for human oversight in autonomous systems.
• Future Outlook: The success of Hermes suggests that the "next big agent" will not be defined by the number of integrations, but by its ability to learn from user behavior and become more specialized and efficient the longer it is used.