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A prompting technique where the AI model reasons through intermediate steps before producing a final answer. Chain-of-thought improves accuracy on complex tasks like math, logic, and multi-step planning. Agent frameworks use CoT to break down goals into sub-tasks, making decisions more transparent and debuggable.