Agentic Loops

Agentic loops refer to a self-reinforcing cycle where autonomous systems, such as AI agents, interact with their environment and adapt to achieve specific goals, often leading to emergent behaviors. As AI becomes increasingly integrated into various industries, understanding agentic loops is crucial for developers and researchers to design and optimize complex systems that can learn, adapt, and interact with humans and other agents effectively.