Note: This article is Adapted from the official Phala Network / Clawdi blog. Original content published at clawdi.ai
There are two agents available on Clawdi right now, and they work in fundamentally different ways. OpenClaw is built for execution. You give it a task, it completes the task. Clean, direct, reliable. Hermes takes a different approach. It does the work, but when it finishes, it pauses and evaluates what just happened. What worked, what did not, and how it could do it better. Then it writes a skill document from that experience and carries it forward. The next time a similar task comes up, Hermes already has something to reference. It is not starting from scratch every time.
Why That Distinction Actually Matters
Most tools do not improve through use. You run them, they return a result, and that is the end of the interaction. Hermes is different because it is building a record of its own performance over time. Each completed task adds to what it knows. That means the more you use it, the more capable it becomes at handling the kinds of work you keep throwing at it. It is a practical form of learning built directly into how the agent operates, not a feature added on top.
Where It Runs and Why That Is Worth Knowing
Both agents run inside a TEE-secured cloud environment on Clawdi. TEE stands for Trusted Execution Environment, which is a sealed space where your data is processed without being exposed outside of it. Private by default. Today, the Stock Expert agent was deployed on the platform, running inside that same secure setup. You are not trading privacy for capability here. The infrastructure handles both. That combination, agents that learn and infrastructure that protects your data, is what makes the Agent Store on Clawdi worth paying attention to.
If you want to see how it works for yourself, head over to https://www.clawdi.ai/ and explore the Agent Store. The Stock Expert agent is live and ready to use.
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