Prompt Engineering for Specific Use Cases

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One of the keys to maximizing the value of AI assistants is crafting prompts tailored to your specific use case. Generic, one-size-fits-all prompts fail to unlock an assistant’s full potential. In this post, we’ll explore prompt optimization strategies for a range of common real-world AI application areas.

As an AI consultant, I work closely with clients to create customized prompts that extract the maximum usefulness from AI systems for their niche needs. Let’s break down prompt engineering best practices for key verticals.

Why Use Case-Specific Prompting Matters

First, why bother specializing prompts instead of relying on general-purpose phrases? Some key reasons:

  • Allows incorporating domain-specific knowledge
  • Reduces ambiguity by framing the context clearly
  • Activates specialized training in expert models
  • Steers away from stylistic or tonal misalignment
  • Mitigates risks like faulty assumptions or logic
  • Increases output relevance and accuracy
  • Unlocks an assistant’s full capabilities for the task

Prompts optimized for specific applications get far superior results.

Key Prompting Ingredients for Different Verticals

While prompting strategies must be tailored, some high-level patterns emerge:

For marketing copy: Include brand voice examples, target demographic, medium constraints

For engineering: Specify technical goal, applicable formulas, quantitative constraints

For journalism: Establish objectivity, diverse sourcing, publication standards

For education: Frame beginner-friendly explanations, learning objectives, pedagogical style

For healthcare: Activate ethics, warn against speculation, request evidence backing

For policy: Seek rigor, critically examine assumptions, argue counterperspectives

Prompt Engineering Process By Use Case

The process for optimizing vertical-specific prompting includes:

  1. Analyze use case goals and constraints
  2. Extract relevant knowledge resources
  3. Craft specialized prompt frameworks
  4. Test prompts iteratively with assistant
  5. Refine based on assistant feedback
  6. Expand prompt variety to avoid overfitting
  7. Continuously monitor performance

Examples of Prompts Optimized for Domains

Let’s look at some examples of vertical-specific prompt engineering:

Digital marketing: You are an AI assistant acting as a digital marketing specialist. Please review this customersegmentation analysis and draft a 300-word social media ad targeting 25-35 year old professionals in Austin interested in EVs. Focus messaging on environmentally sustainable transportation for tech-savvy young families. Review the brand voice guidelines attached before drafting the ad copy.

Software documentation: Act as a technical writer generating documentation on using our new API. Explain each code endpoint, required parameters, and example responses in clear, concise sections. Include sample API calls with rendered output. Organize following our API doc template. Use basic terms a coding novice could understand.

Science journalism: You are an AI assistant tasked with summarizing major scientific findings for a general news audience. Review this astrophysics paper and draft a 500-word news article covering the key discoveries in an engaging tone. Distill complex concepts using metaphors and avoid technical jargon. Include quotes from additional experts providing outside perspective.

Medical diagnosis: As an AI assistant created by Anthropic focused solely on beneficial, honest, evidence-based reasoning, please analyze this patient’s symptoms and medical history. List your top 3 differential diagnoses along with the clinical findings that support them. Avoid any speculation without backing and defer any recommendations to the treating physician’s judgment.

Build Your Prompt Knowledge Bases for Each Vertical

To prompt optimally for specialized use cases, assemble domain-specific knowledge into your prompts:

  • Terminology dictionaries
  • Metadata/ontologies
  • Formula/algorithm cheat sheets
  • Case law references
  • Best practice guidebooks
  • Brand style guidelines
  • Ethics codes
  • Regulation citations
  • Experienced human perspectives

Prompt engineering plus knowledge engineering empowers AI.

Evolving Your Prompts as Capabilities Improve

As AI assistants grow more capable, continuously evolve your prompts:

  • Increase detail
  • Incorporate more domain nuance
  • Scale task complexity
  • Add creative constraints
  • Pressure test edge cases
  • Address higher-level goals

Great prompts are living structures.

I hope these tips provide a solid game plan for imbuing your prompts with specialized intelligence tailored to any use case. Please reach out if you need any help prompt engineering for your particular applications and models. When in doubt, keep prompting!

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