Agent Augmentation

In practical terms, Agent Augmentation refers to the use of AI agents to support people by preparing information, performing subtasks, recommending actions, or coordinating routine work. It matters because dependable automation requires clear triggers, tools, state, approvals, error handling, and ownership rather than model output alone. Related concepts often include governance, integration, monitoring, evaluation, and human oversight.