A workflow node is enough AI.
You are wiring systems together and the LLM steps stay simple. Many teams keep n8n for the glue.
Mobius vs. n8n
n8n sees the model as one step in a workflow you draw. Mobius sees the agent as the worker: it reasons, acts, and remembers, on a backend built to survive production.
| Decision point | n8n | Mobius |
|---|---|---|
| Best fit | No-code workflow automation with LLM steps | Durable AI agents as a managed backend |
| The agent | An LLM node inside a workflow graph | A first-class agent runtime with reasoning loops |
| Durability | A crash mid-run loses progress | Durable runs resume after restarts and retries |
| Model runtime | One LLM per node, configured by hand | Model-agnostic runtime, swap per step |
| Memory | Bolt on your own store | Agent memory with recall and ranking, across runs |
| Cost control | Track token spend yourself | Per-run budgets and spend visibility |
| Integrations | 400+ nodes for workflow steps | Managed integrations as agent tools, auth handled |
| Human approval | A basic pause-for-approval node | First-class approval gates that suspend the run |
Which one fits.
A node runs, returns text, and the graph moves on. An agent reasons, acts, and remembers. That difference decides the tool.
The node has become an agent.
The AI has outgrown its step in the graph and needs a real backend, without your team maintaining one.
Graduate from the workflow node.
Start free and give the agent a backend built for production, without maintaining it yourself.