Chain-of-thought prompting is a prompting technique that asks a language model to work through intermediate reasoning steps or provide a structured explanation before answering.
It can improve performance on some reasoning tasks, but exposed reasoning can be verbose, fragile, or inappropriate for sensitive workflows. Many systems instead provide brief summaries or use private reasoning internally.