Chain-of-Thought prompting (SOLVED)
Chain-of-Thought prompting remains one of the most frequently asked prompt engineering questions, yet candidates often give surface-level answers. Learn when CoT helps vs hurts, production token costs, and advanced variants like self-consistency and tree-of-thoughts that impress senior interviewers.
TL;DR — Quick Answer
CoT prompts the model to show step-by-step reasoning before the final answer, improving performance on complex reasoning tasks.
The Interview Question
Explain chain-of-thought (CoT) prompting. When is it effective and what are its limitations?
Deep Explanation
CoT can be zero-shot ('think step by step') or few-shot with reasoning examples. Effective for math, logic, multi-hop QA. Limitations: increased latency/tokens, reasoning can still be wrong (confident incorrect steps), and some models don't benefit equally.
Variants: self-consistency (sample multiple CoT paths), tree-of-thoughts for exploration.
Sign in to unlock full answer
Get deep explanations, PDF export & all Prompt Engineering questions