What is chain of thought prompting?

Chain of thought prompting is a technique used with AI language models where you encourage the model to work through a problem step by step, explicitly showing its reasoning process before arriving at a final answer, rather than jumping straight to a conclusion. This approach has been shown to significantly improve accuracy on complex tasks that involve logic, math, or multi-step reasoning, since it mimics how humans naturally break down difficult problems into smaller, more manageable pieces rather than trying to solve everything in one mental leap. You can trigger chain of thought reasoning either by providing example prompts that demonstrate step-by-step reasoning, known as few shot chain of thought, or simply by adding a phrase like 'think step by step' or 'explain your reasoning' directly into your prompt, which is called zero-shot chain of thought. This technique works particularly well for tasks like solving word problems, debugging code, analyzing complex scenarios, or answering questions that require weighing multiple pieces of information before reaching a conclusion. Chain of thought prompting has become a foundational technique in prompt engineering because it reduces careless errors and makes the AI's reasoning process more transparent, which also makes it easier for users to spot mistakes in the logic if they occur.