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Clawloop: Unified AI Agent Learning
Learn how Clawloop unifies AI agent learning from production data and training, improving prompts, memory, tools, and model weights for better agent performance.
Clawloop is the learning from experience layer for AI agents. It turns traces, failures, and user feedback from production traffic and interactions with training environments into updates to an agent’s harness and weights. The harness includes prompt, memory, and tools, so Clawloop can improve not just the model but also how the agent is instructed and equipped. It plugs into stacks like LiteLLM, OpenClaw, and n8n and connects to training backends like SkyRL and Tinker for weight adaptation.