LLM-Based Agent

An LLM-Based Agent is an AI agent that is an LLM-based system (uses a large language model as its core reasoning component to support autonomous task execution).

• AKA: Language Model Agent, LLM Agent, Large Language Model Based Agent.
• Context:
  • It can typically process Natural Language Inputs through LLM-based agent language understanding.
  • It can typically generate Contextual Responses through LLM-based agent text generation.
  • It can typically maintain Conversation State through LLM-based agent memory management.
  • It can typically perform Task Decomposition through LLM-based agent planning capability.
  • It can typically execute Tool Calling through LLM-based agent function invocation.
  • ...
  • It can often exhibit Emergent Reasoning through LLM-based agent inference capability.
  • It can often handle Multi-Modal Inputs through LLM-based agent perception system.
  • It can often adapt Behavioral Strategys through LLM-based agent learning mechanism.
  • It can often coordinate Multi-Agent Interactions through LLM-based agent communication protocol.
  • ...
  • It can range from being a Simple LLM-Based Agent to being a Complex LLM-Based Agent, depending on its LLM-based agent architecture sophistication.
  • It can range from being a Single-Task LLM-Based Agent to being a Multi-Task LLM-Based Agent, depending on its LLM-based agent capability breadth.
  • ...
  • It can utilize Large Language Models for LLM-based agent intelligence core.
  • It can implement Agent Architecture Patterns for LLM-based agent behavior structure.
  • It can leverage Prompt Engineering Techniques for LLM-based agent instruction optimization.
  • It can employ Tool Integration APIs for LLM-based agent capability extension.
  • ...
• Examples:
  • Conversational LLM-Based Agents, such as:
    • ChatGPT Agent for LLM-based agent dialogue interaction.
    • Claude Assistant for LLM-based agent helpful conversation.
    • Gemini Agent for LLM-based agent multi-modal interaction.
  • Task-Specific LLM-Based Agents, such as:
    • LLM-Based Code Agents, such as:
      • Claude Code Agent for LLM-based agent code development.
      • Copilot Agent for LLM-based agent code completion.
    • LLM-Based Research Agents for LLM-based agent information synthesis.
    • LLM-Based Writing Agents for LLM-based agent content creation.
  • Enterprise LLM-Based Agents, such as:
    • Customer Service LLM Agents for LLM-based agent support automation.
    • Analytics LLM Agents for LLM-based agent data interpretation.
    • Workflow LLM Agents for LLM-based agent process automation.
  • ...
• Counter-Examples:
  • Rule-Based Agents, which use predefined rules rather than LLM-based reasoning.
  • Reinforcement Learning Agents, which learn through reward signals rather than LLM-based understanding.
  • Expert Systems, which use knowledge bases rather than LLM-based generation.
• See: AI Agent, Large Language Model, Autonomous Agent, Intelligent Agent, Natural Language Processing System.

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