Feedback Loop

A cycle where the output of an AI system is fed back in as new input, allowing the system to learn from or react to its own results. In agentic AI systems, feedback loops enable the agent to adjust its approach based on what worked and what did not. They can also propagate errors or biases over time if the initial outputs are flawed.
See also: agentic AI, reinforcement learning, reward model.