AgentLoop — runtime learning for AI agents

AgentLoop is a runtime learning layer for production AI agents, enabling human corrections to become reusable memory. Corrections are automatically applied before every response, improving the agent without retraining. The system retrieves relevant facts, logs every interaction, and allows for quick corrections. It integrates seamlessly with existing APIs, maintaining the same interface while adding memory retrieval and turn logging. Teams use it to handle edge cases in production, replacing manual system prompt maintenance with structured memory.