AI Prompt EngineeringModuleLesson 01
Concept of Chain of Thought
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Chain of Thought (CoT) is one of the most powerful discoveries in Prompt Engineering.
If you ask an AI a complex math or logic question and force it to output only the final answer, it will often guess wrong. This is because LLMs do not have an internal 'scratchpad' to calculate things silently. They think by generating tokens.
By forcing the AI to output its step-by-step reasoning before it outputs the final answer, its accuracy skyrockets because it uses its own generated text as context for the next calculation.
You can often trigger this behavior simply by appending the phrase: "Think step by step." to the end of your prompt (Zero-Shot CoT).
However, the professional way to do this is to explicitly dictate an output format where the reasoning must be written out before the conclusion.
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A prompting technique that forces the AI to output its intermediate reasoning steps before providing the final answer.
Why does Chain of Thought prompting improve an LLM's accuracy on logic tasks?
LLMs think out loud. For complex logic, never ask for just the final answer. Always force the AI to write out its step-by-step reasoning first.