AI System Prompt

An AI System Prompt is a system instruction set that contains configuration directives for an AI system (intended to guide AI behavior, AI capability, and AI interaction parameters at a system level).

• Context:
  • It can (typically) establish the AI system's operational domain, including task scope, permissions, and functional boundaries.
  • It can define AI system behavior rules such as ethical guidelines, bias mitigation requirements, and safety protocols.
  • It can specify AI system tool access parameters for using external resources like search engines, databases, or code execution environments.
  • It can configure AI system response characteristics including style, format, tone, and level of detail.
  • It can set AI system moderation parameters to filter inappropriate content or enforce content policies.
  • It can outline AI system error handling procedures for managing edge cases, misunderstandings, or operational failures.
  • It can establish AI system knowledge limitations such as cutoff dates or explicit knowledge boundaries.
  • It can provide AI system context management directives for handling session history and conversation memory.
  • It can implement AI system security protocols to prevent prompt injections, jailbreaking, and other security vulnerabilities.
  • It can define AI system personality attributes that shape how the AI system presents itself to users.
  • It can range from being a Simple AI System Prompt to being a Complex AI System Prompt, depending on its AI system instruction complexity.
  • Simple AI System Prompts typically contain basic role definitions and minimal behavioral guidelines.
  • Complex AI System Prompts often incorporate extensive safety protocols, conditional logic branches, and detailed specifications for handling diverse scenarios.
  • It can range from being a General-Purpose AI System Prompt to being a Domain-Specific AI System Prompt, depending on its AI system application scope.
  • General-Purpose AI System Prompts typically provide balanced capabilities across multiple domains.
  • Domain-Specific AI System Prompts focus AI system capabilities on particular subject areas or tasks.
  • ...
• Examples:
  • AI Chatbot System Prompts, such as:
    • GPT-4 System Prompt defining OpenAI large language model behavior.
    • Claude System Prompt establishing Anthropic AI assistant constraints.
    • Gemini System Prompt configuring Google AI chatbot parameters.
  • AI Image Generation System Prompts, such as:
    • DALL-E System Prompt for AI image creation parameters and AI image content filters.
    • Midjourney System Prompt defining AI visual style guidelines and AI artistic rendering constraints.
    • Stable Diffusion System Prompt establishing open-source image model behavior.
  • AI Code Generation System Prompts, such as:
    • GitHub Copilot System Prompt for AI code suggestion parameters.
    • Cursor AI System Prompt determining code editor AI assistant behavior.
    • Amazon CodeWhisperer System Prompt configuring AWS code generation constraints.
  • AI Enterprise System Prompts, such as:
    • Microsoft Copilot for Business System Prompt implementing enterprise data security rules.
    • Salesforce Einstein System Prompt defining CRM AI assistance parameters.
    • ServiceNow AI System Prompt establishing IT workflow automation guidelines.
  • AI Specialized Task System Prompts, such as:
    • AI Document Analysis System Prompt for processing document structure and text content.
    • AI Translation System Prompt specifying language translation parameters.
    • AI Scientific Research System Prompt guiding scientific data analysis.
  • ...
• Counter-Examples:
  • AI User Prompt, which is provided by the end-user rather than being pre-configured at the system level.
  • AI Model Training Dataset, which provides learning examples rather than operational instructions.
  • AI Model Parameter, which defines the technical architecture rather than behavioral guidelines.
  • AI Technical Configuration File, which controls infrastructure settings rather than behavioral directives.
  • AI Fine-Tuning Directive, which modifies model weights rather than providing runtime instructions.
• See: Prompt Engineering, AI Safety, AI System Security, AI Behavior Design, AI Content Policy, AI Instruction Following, AI Prompt Injection, AI System Configuration.

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