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Courses/Production agents with LangGraph and n8n/State, memory, and controlled loops

State, memory, and controlled loops

A reliable agent doesn't "remember" by intuition—it stores state. It knows what task it's solving, what it has tried, what's missing, and when it should stop.

  • Separate context, memory, and execution state.
  • Design loops with limits, exit criteria, and recovery.
  • Avoid agents that repeat actions or lose track of the thread.

Recommended minimum state

TerminalCode
{
  "task_id": "inbox-2026-07-02-001",
  "intent": "crear_borrador_respuesta",
  "risk": "medium",
  "customer": "cliente@example.com",
  "attempts": 1,
  "approved": false,
  "next_action": "draft_email",
  "evidence": ["email original", "politica devoluciones"]
}

Healthy loops

  • Attempt limit: never retry forever.
  • Exit criterion: know when a response is sufficient.
  • Escalation: request human help when there's no confidence.
  • Idempotency: don't repeat external actions if the step has already been executed.