An artificial intelligence agent loop is the recurring control cycle that lets an agent work through a task. Each iteration can add context, call a model, invoke a tool, inspect the result and decide whether another step is needed.
Loops enable multi-step work but can run longer than intended when completion conditions are weak or failures repeat. Runtimes should track iterations, cost, progress and side effects, then support steering or termination when behavior becomes unproductive.
