In AI workflows, an agentic loop bottleneck occurs when a system gets stuck repeatedly querying a model or tool without productive progression. This inefficiency slows autonomous agents like chatbots or automation scripts. Developers and data scientists benefit most, using it to diagnose stalls, optimize decision loops, and enhance response speed in production systems.
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