Think about AI agents. This here, this loop, is really what we need in an AI agent. We don't want to have to give it all of its memory, give it all of its information. We really need to give it tasks and be able to have it improve itself without a bunch of instruction from the orchestrator. Some of the key features that this entails is skill documents. So, these are structured markdown documents that capture when X try Y patterns from successful tasks. It also has a longer-term memory than Open Claw, tool integration, self-evaluation, and it's model agnostic, which allows us to be able to swap models without changing anything about the agent, which is similar to Open Claw, but we'll we'll dive into that a little bit later in the video once we kind of cover the basics here. But, it's it's really different because it doesn't just execute the tasks, it learns how to do them better.