Prompt Engineering Techniques Quiz

5 questions Pass: 70% +25 pts (50 with Pro)

Quiz covering Optimize Generative AI Systems

What you'll be asked

  1. Which of the following is the most effective way to improve the accuracy of an LLM when performing complex reasoning tasks?
  2. When designing a system prompt for an agent, why is it recommended to use delimiters like triple quotes (""") or XML tags?
  3. What is the primary purpose of 'Few-Shot Prompting' in an AI system?
  4. If an LLM is consistently hallucinating facts in its responses, which prompt engineering strategy should you prioritize?
  5. When implementing a multi-step Agentic workflow, why is it often better to use 'Self-Consistency' (generating multiple reasoning paths and taking the majority vote) over a single Chain-of-Thought pass?

Answers and explanations come after you submit.