Advanced Prompt Engineering Principles



AI Nuggets

Outline of Instructions, CLI Commands, Website URLs, and Tips from the Video Transcript

Introduction to Prompt Engineering

  • Importance of creating better prompts:
    • Achieve better results
    • Reduce costs
    • Increase accuracy in software and automation

Resources for Prompt Engineering

  • Resource provided by the Tropic team (creators of CLA)
  • Anthropics documentation for prompt engineering
  • Website URL: Not provided explicitly in the transcript

Prompt Engineering Topics Covered

  • Using multimodels like Vision models
  • Writing better prompts
  • Best practices

Prompt Engineering Principles

  • Understanding that different LMs may require different prompts
  • A prompt is the text given to CL to elicit a relevant output
  • Importance of the context window in LMs

Prompt Development Lifecycle

  1. Develop test cases
  2. Engineer a preliminary prompt
  3. Test the prompts against cases
  4. Refine the prompts
  5. Share or launch the polished prompts

Techniques and Guidelines for Better Prompts

  • Be clear and direct
  • Provide clear instructions and context
  • Include examples
  • Assign roles to guide the response
  • Use XML tags
  • Chain prompts for complex tasks
  • Let CL think step by step
  • Prefill CL’s responses to guide output
  • Control the output format
  • Understand the importance of context order in prompts

Anthropics Prompt Engineering Exercise

  • Google spreadsheet exercise for practicing prompt engineering
  • Requires connecting your CL API
  • URL: Not provided explicitly in the transcript

Anthropics Prompt Library

  • Contains well-structured and detailed prompts
  • URL: Not provided explicitly in the transcript

Examples from the Anthropics Prompt Library

  • Website wizard: Detailed instructions for creating a one-page website
  • Excel formula expert: Advanced Excel formula based on user descriptions
  • Distilling meetings into concise summaries
  • Grading Guru: Compare and evaluate text quality

Best Practices for Using Vision with CLA

  • Apply traditional techniques to multimodel
  • Visual prompting with images as input
  • Transcribing documents and forms
  • Working with charts, graphs, and slide decks
  • Combining CLA with stable diffusion API for image generation

Building Evaluations

  • Importance of offline evaluation for continuous improvement
  • Components of an evaluation:
    • Input prompt
    • Output from the model
    • Golden answer for comparison
    • Score generated by grading methods

Moderation Filters

  • Creating filters to allow or block certain outputs
  • Categories for filtering: Allow or Block

Meta Prompt

  • A long multi-shot prompt with examples of good prompts for various tasks
  • Helps in writing a good prompt for your task
  • URL: Not provided explicitly in the transcript

Additional Tips

  • Use the LLM to assist in writing better prompts
  • Save well-structured prompts for future use

Conclusion

  • Emphasize detailed prompts with examples, context, and role assignments
  • Check out the interactive tutorial provided by Anthropics
  • Best practices for leveraging vision, slide decks, charts, and transcribing text

Video Description

(Note: The transcript did not provide complete exact URLs for the resources mentioned, and the provided link is for the YouTube video itself, not additional resources.)