Auto-CoT automatically generates diverse chain-of-thought demonstrations to prompt large language models, removing the need for manual prompt design. It constructs reasoning chains step by step and selects demographically varied examples to cover different reasoning patterns. The approach achieves performance comparable to or exceeding manually designed prompts on GPT-3 across reasoning benchmarks like arithmetic and commonsense questions.