Agent Loop

An agent loop is the cycle that lets an AI agent keep working toward a goal. First, the agent gathers fresh data from its tools, sensors, or memory. Next, it updates its internal state and decides what to do, often by running a planning or reasoning step. Then it carries out the chosen action, such as calling an API, writing to a file, or sending a message. After acting, it checks the result and stores new information. The loop starts again with the latest data, so the agent can adjust to changes and improve over time. This fast repeat of observe–decide–act gives the agent its power.

Visit the following resources to learn more:

• @article@What is an Agent Loop?
• @article@Let's Build your Own Agentic Loop