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Chain-of-Thought (CoT)

Chain-of-Thought prompting encourages the model to generate intermediate reasoning steps before arriving at a final answer.

Why it Works​

LLMs process tokens sequentially. By asking the model to "think step by step," you provide it with an internal "scratchpad" that prevents it from jumping to a wrong conclusion too quickly.

Implementation​

You can trigger CoT by adding simple phrases like:

  • "Let's think step by step."
  • "Walk me through your reasoning process."
  • "Analyze the problem before providing the solution."

Step-Back Prompting​

A variation where you ask the model to first state the general principles or facts needed to solve a problem before attempting it.