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Courses/Production agents with LangGraph and n8n/LangGraph vs CrewAI vs n8n in 2026

LangGraph vs CrewAI vs n8n in 2026

These three tools don't solve the same problem. LangGraph is stateful control, CrewAI is role-based collaboration, and n8n is visual automation connected to the business.

  • Choose the tool based on the problem, team, and risk.
  • Avoid pretty prototypes that break in production.
  • Design a hybrid architecture with code and visual automation.

Straightforward summary

  • LangGraph: best if you need explicit state, loops, memory, branches, checkpoints, and fine-grained control.
  • CrewAI: best if you want to prototype agent teams with roles and understandable tasks.
  • n8n: best if you need to connect business tools without writing integrations from scratch.

Decision table

TerminalCode
Necesitas ramas, bucles y memoria persistente -> LangGraph
Necesitas roles tipo investigador/redactor/revisor -> CrewAI
Necesitas Gmail, Sheets, CRM, webhooks y aprobaciones visuales -> n8n
Necesitas producción real para pyme -> n8n + LangGraph
Necesitas demo rápida para explicar una idea -> CrewAI o n8n
Necesitas permisos estrictos y logs -> LangGraph + n8n con human-in-the-loop

Recommended architecture for Aulafy

TerminalCode
n8n:
  - recibe email, formulario o webhook
  - normaliza datos
  - llama al agente
  - crea borrador, ticket o aviso
  - guarda logs visibles

LangGraph:
  - clasifica intención y riesgo
  - mantiene estado
  - decide siguiente paso
  - pide aprobación si hace falta

CrewAI:
  - prototipa roles
  - explora tareas creativas
  - ayuda a validar la idea antes de endurecerla

Migration mental model

Start simple and increase control only when it hurts:

TerminalCode
1. Prompt manual
2. Workflow n8n que crea borrador
3. AI Agent de n8n con herramientas limitadas
4. LangGraph para decisiones con estado
5. Human-in-the-loop para acciones sensibles
6. Evals + logs antes de ampliar autonomía