Your eval says the prompt works. That’s not the same as the prompt being good.
📰 Medium · LLM
Learn to distinguish between a prompt that 'works' and one that's truly 'good', and discover a library to measure the difference
Action Steps
- Evaluate your prompts using metrics beyond just 'works' or 'fails'
- Use a library to measure prompt quality and identify areas for improvement
- Assess the gap between 'works' and 'good' in your prompts
- Refine your prompts based on evaluation results
- Test and iterate on prompt designs to optimize performance
Who Needs to Know This
This article benefits natural language processing engineers and researchers who design and evaluate prompts for LLMs, as it helps them refine their prompt engineering skills and assess prompt quality more effectively
Key Insight
💡 A prompt that 'works' may not be optimal or effective, and measuring its quality is crucial to achieving better results
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️️️ Don't just settle for prompts that 'work' — strive for ones that are truly 'good'! Discover how to measure the difference and refine your prompt engineering skills
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