Advanced Prompt Engineering Principles

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AI Nuggets

Based on the transcript provided, here are the detailed instructions, CLI commands, website URLs, and tips extracted and organized into an easy-to-follow outline:

Prompt Engineering Best Practices

• Resource: Tropic team’s documentation on prompt engineering.
• Goal: Create better prompts to achieve better results, reduce costs, and increase accuracy.

Intro to Prompting

• Key Concept: The quality of prompts affects the quality of outputs from language models (LMs).
• Prompt Definition: A prompt is the text given to an LM to elicit a relevant output.
• Response Definition: The text that the LM responds with.
• Context Window Importance: LMs use the context window to predict the next token; the size of the context window can affect performance.

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 for Creating Better Prompts

• Be clear and direct.
• Provide clear instructions and context.
• Include examples.
• Give the LM a role.
• Use XML tags.
• Chain prompts for complex tasks.
• Let the LM “think” step by step.
• Prefill responses to guide output.
• Control the output format.
• Use rewrites and understand context matters.

Anthropics Resources

• Prompt Engineering Google Spreadsheet: An interactive tool to practice prompt engineering. Requires connecting your Cloud API.
• Prompt Library: A collection of well-structured and detailed prompts. URL not provided in the transcript.

Working with Images and Vision Models

• Apply traditional techniques to multimodal prompts.
• Use images as input and ask text questions about them.
• Embed questions in images.
• Highlight parts of images to focus questions.
• Provide examples to improve accuracy with visual tasks.
• Use multiple images as input.
• Transcribe documents and handwritten text.
• Work with charts, graphs, and slide decks.
• Combine LMs with Stable Diffusion API for image generation.
• Build evaluations for prompts using a grading mechanism.

Moderation Filters

• Create filters to allow or block certain outputs based on categories.

Meta Prompt

• A tool to help generate better prompts by providing examples of good prompts for various tasks.

Tips for Improving Prompt Engineering

• Iterate on prompts and outputs to refine them.
• Save successful prompts for future use.
• Use the LM to help write better prompts.

Additional Notes

• The video description contains links to the Anthropics prompt library and other resources.
• The video emphasizes the importance of detailed prompts with examples, context, and role assignments.

Conclusion

• Prompt engineering is crucial for leveraging LMs effectively.
• Detailed and structured prompts lead to better results and cost efficiency.
• Anthropics provides valuable resources for learning and practicing prompt engineering.

Please note that the exact URLs for the resources mentioned in the transcript were not provided, and the instructions to access the Anthropics prompt library and Google spreadsheet were to look in the video description for links.