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Series 3: Common Patterns and Mistakes

This series identifies common patterns in prompt engineering and helps you avoid frequent mistakes that can limit your effectiveness.

Articles in This Series​

  • Article 26: The Impact of Prompt Length on Response Quality (Coming Soon)
  • Article 27: How to Deal with "I don't know" Responses (Coming Soon)
  • Article 28: Common Prompting Mistakes to Avoid (Coming Soon)
  • Article 29: Techniques for Reducing Bias in LLM Outputs (Coming Soon)
  • Article 30: Understanding and Working with Model Limitations (Coming Soon)

Series Overview​

This series helps you navigate the common pitfalls and challenges in prompt engineering. We'll explore how different factors affect response quality, learn to handle uncertain responses, and discover techniques for reducing bias and working effectively within model limitations.

Learning Objectives​

By the end of this series, you will:

  • Understand how prompt length affects response quality
  • Know how to handle uncertain or incomplete responses
  • Recognize and avoid common prompting mistakes
  • Be able to reduce bias in LLM outputs
  • Understand how to work effectively within model limitations

Prerequisites​

  • Completion of Series 1: Crafting Effective Prompts
  • Some practical experience with prompt engineering
  • Understanding of LLM capabilities and limitations