提示工程

题集来源:AMIT SHEKHAR(amitshekhariitbhu)收录项目:ai-engineering-interview-questions查看原题集

题目目录

30 道原题
  1. What is prompt engineering, and why is it critical for AI applications?

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  2. Explain zero-shot, one-shot, and few-shot prompting with examples.

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  3. What is chain-of-thought (CoT) prompting, and when should you use it?

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  4. Explain self-consistency prompting and how it improves reasoning.

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  5. What is tree-of-thought prompting?

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  6. What is ReAct (Reasoning + Acting) prompting, and how does it work?

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  7. What is a system prompt, and how does it influence model behavior?

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  8. How do you structure prompts for consistent structured output (JSON, XML)?

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  9. What is prompt injection, and how do you defend against it?

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  10. What is jailbreaking in LLMs, and what are common jailbreak techniques?

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  11. How do you optimize prompts for cost and latency?

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  12. What is the difference between prompt engineering and prompt tuning?

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  13. What is a prompt template, and how do you design one for production use?

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  14. How do you handle multi-turn conversations with LLMs?

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  15. What is role prompting, and when is it effective?

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  16. What is prompt chaining, and how do you design a chain of prompts for complex tasks?

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  17. How do you evaluate and iterate on prompt quality?

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  18. What are meta-prompts, and how can they be used to generate prompts?

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  19. What are the common failure modes in prompting, and how do you debug them?

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  20. How do you handle edge cases and adversarial inputs in prompt design?

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  21. What is the "lost in the middle" problem in long-context prompting?

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  22. What are output parsers, and why are they needed for production applications?

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  23. How do you handle multi-language prompting effectively?

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  24. Your few-shot prompting gives inconsistent results across similar inputs. How do you stabilize it?

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  25. Your LLM classification system is too sensitive to prompt wording changes. How do you reduce prompt sensitivity?

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  26. Your chatbot's system prompt containing proprietary business logic is being leaked by users. How do you prevent it?

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  27. Your LLM agent is vulnerable to prompt injection that reveals the system prompt. How do you defend it?

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  28. Your chain-of-thought prompting is not improving LLM accuracy on reasoning tasks. What do you fix?

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  29. Your AI system works in English but fails for other languages. How do you add multilingual support?

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  30. Your zero-shot cross-lingual transfer from English fails on other languages. How do you fix it?

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