{
  "id": "ai-agent",
  "code": "PTL-0063",
  "term": "AI Agent",
  "aliases": [
    "LLM agent",
    "agentic system",
    "autonomous agent"
  ],
  "category": "agents",
  "definition": "An AI agent is a system in which a language model dynamically directs its own process and tool use in a loop, deciding what actions to take based on environment feedback until a task is complete.",
  "description": "Anthropic's widely cited taxonomy distinguishes agents from workflows, in which model calls and tools follow predefined code paths. Agents trade predictability and cost for flexibility on open-ended tasks.",
  "example": null,
  "broader": [],
  "narrower": [],
  "related": [
    "react",
    "agentic-workflow",
    "orchestrator-workers",
    "agent-memory",
    "context-engineering"
  ],
  "introduced": null,
  "sources": [
    {
      "title": "Building effective agents",
      "authors": "Anthropic",
      "year": 2024,
      "url": "https://www.anthropic.com/research/building-effective-agents"
    }
  ],
  "url": "https://protologue.com/t/ai-agent/",
  "citation": "Protologue. (2026). AI Agent. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0063). https://protologue.com/t/ai-agent/"
}