• Ep050: Prompt Engineering for Business Performance

  • 2024/08/13
  • 再生時間: 28 分
  • ポッドキャスト

Ep050: Prompt Engineering for Business Performance

  • サマリー

  • Today Anthropic’s Zach Witten takes us on a deep dive into Anthropic’s cutting-edge AI models—Claude Haiku, Sonnet, and Opus—exploring their safety-first approach to generative AI and sharing essential tips for prompt engineering.

    Topics Include:

    • Introductions, about Anthropic
    • 3 models: Haiku, Sonnet and Opus
    • Scaling laws for hardware, data and compute
    • Competing to be safest AI solutions, safety-first organization
    • Leader in jailbreak resistance
    • Interpretability features and breakthroughs for AI models
    • Basics of prompt engineering
    • Improving prompts with Claude
    • Details matter – small changes to spelling, context will greatly improve results
    • System prompt – role setting will improve results (i.e. “You are an expert mathematician…” for math query
    • Be clear and direct – use XML tags where possible
    • Encourage Claude to think step-by-step – answering fast comes with accuracy risk
    • Use examples to provide additional clarity to Claude
    • Bonus tips for image-based prompt engineering
    • Q&A 1) Who wrote the meta-prompts in the cookbook?
    • Q&A 2) Guidance for writing prompts for prompt generator
    • Q&A 3) Best practices for tabular and structured data
    • Q&A 4) Maintaining “tone” across hundreds/thousands of responses
    • Q&A 5) Reverse engineering a prompt
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あらすじ・解説

Today Anthropic’s Zach Witten takes us on a deep dive into Anthropic’s cutting-edge AI models—Claude Haiku, Sonnet, and Opus—exploring their safety-first approach to generative AI and sharing essential tips for prompt engineering.

Topics Include:

  • Introductions, about Anthropic
  • 3 models: Haiku, Sonnet and Opus
  • Scaling laws for hardware, data and compute
  • Competing to be safest AI solutions, safety-first organization
  • Leader in jailbreak resistance
  • Interpretability features and breakthroughs for AI models
  • Basics of prompt engineering
  • Improving prompts with Claude
  • Details matter – small changes to spelling, context will greatly improve results
  • System prompt – role setting will improve results (i.e. “You are an expert mathematician…” for math query
  • Be clear and direct – use XML tags where possible
  • Encourage Claude to think step-by-step – answering fast comes with accuracy risk
  • Use examples to provide additional clarity to Claude
  • Bonus tips for image-based prompt engineering
  • Q&A 1) Who wrote the meta-prompts in the cookbook?
  • Q&A 2) Guidance for writing prompts for prompt generator
  • Q&A 3) Best practices for tabular and structured data
  • Q&A 4) Maintaining “tone” across hundreds/thousands of responses
  • Q&A 5) Reverse engineering a prompt

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