LLM Power User

An LLM Power User is a power user that is an advanced system actor who excels at large language model utilization through sophisticated interaction patterns and system integration methods.

• AKA: Large Language Model Power User, LLM Expert User, Advanced LLM Practitioner.
• Context:
  • It can typically craft Advanced LLM Prompts using prompt engineering techniques.
  • It can typically mitigate LLM Hallucination Patterns through output verification strategys.
  • It can typically optimize Token Usage via context window management.
  • It can typically chain Multiple LLM Calls for complex reasoning tasks.
  • It can typically integrate LLM APIs into automated workflows.
  • ...
  • It can often employ Few-Shot Learning and in-context learning techniques.
  • It can often utilize System Prompt Engineering for behavior customization.
  • It can often implement Retrieval-Augmented Generation with vector databases.
  • It can often develop Custom LLM Applications using framework librarys.
  • ...
  • It can range from being a Prompt-Focused LLM Power User to being an Integration-Focused LLM Power User, depending on its LLM power user specialization.
  • It can range from being a Single-Model LLM Power User to being a Multi-Model LLM Power User, depending on its LLM power user model diversity.
  • It can range from being a GUI-Based LLM Power User to being an API-Based LLM Power User, depending on its LLM power user interface preference.
  • It can range from being a Domain-Specific LLM Power User to being a General-Purpose LLM Power User, depending on its LLM power user application scope.
  • It can range from being a Cost-Conscious LLM Power User to being a Performance-Focused LLM Power User, depending on its LLM power user optimization priority.
  • ...
  • It can leverage LLM-Centric System Architectures for scalable deployments.
  • It can implement Modular AI Prompt Development Techniques for maintainable solutions.
  • It can apply Chain of Draft Prompting Methods for efficient reasoning.
  • It can utilize Subject Matter Expert Text-to-Text AI Prompts for domain expertise.
  • ...
• Example(s):
  • Human LLM Power Users, such as:
    • Software Developer LLM Power Users using code generation prompts.
    • Data Scientist LLM Power Users employing analysis automation techniques.
    • Content Creator LLM Power Users crafting creative generation workflows.
  • AI Agent LLM Power Users, such as:
    • AutoGPT Agents orchestrating multi-step reasoning.
    • LangChain Agents managing tool integration.
    • Research Assistant Agents conducting literature synthesis.
  • Research LLM Power Users, such as:
    • Academic Researcher LLM Power Users conducting literature synthesis.
    • Market Researcher LLM Power Users performing trend analysis.
    • Legal Researcher LLM Power Users executing case law reviews.
  • Domain Expert LLM Power Users, such as:
    • Medical LLM Power Users analyzing clinical documentation.
    • Financial LLM Power Users processing market intelligence.
    • Education LLM Power Users developing personalized curriculums.
  • Simon Willison, self-described LLM power user and software developer.
  • Ethan Mollick, academic LLM power user researching AI applications.
  • ...
• Counter-Example(s):
  • Casual LLM Users, who use basic prompts only.
  • LLM Developers, who build language models rather than use them.
  • AI Researchers, who study model architectures without practical application.
• See: Power User, Large Language Model, Prompt Engineering, LLM Hallucination Pattern, LLM System Architecture, AI System User, Token Optimization, System Prompt, Retrieval-Augmented Generation.

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