COMPARISON

N8N vs Lazarus: Why Workflow Automation Falls Short for AI Agents

N8N is great for workflows. But AI agents need something different: human oversight built in.

December 15, 2025•COMPARISON

If you're building AI agents, you've probably looked at N8N. It's a powerful workflow automation tool—open source, flexible, with hundreds of integrations.

But here's the problem: N8N was built for workflows. AI agents are different.

When AI makes mistakes, it makes them at scale. And without human oversight, those mistakes compound.

The human oversight problem

AI agents are incredibly capable. They can analyze data, write content, manage tasks, and interact with dozens of tools. But they're not perfect—and when they get something wrong, the consequences can be expensive.

Common AI agent mistakes:

Sending emails to the wrong recipients

Updating CRM data with incorrect information

Creating reports based on misinterpreted data

Taking actions based on ambiguous instructions

Escalating routine issues or ignoring important ones

With traditional workflow tools like N8N, you have two choices: let the automation run unsupervised, or manually review every action. Neither scales.

What you actually need is selective human oversight—approval for high-stakes decisions, autonomy for routine tasks.

Feature comparison: N8N vs Lazarus

Feature	N8N	Lazarus
Human-in-the-Loop	Manual workarounds	Built-in approval workflows
Human Contact Methods	None native	Email, Slack, Discord, in-app
Guardrails	No native concept	Set rules for when agents escalate
Design Philosophy	Workflow-first, bolted-on AI	Agent-first from day one
Agent Builder	Complex node setup	Describe in plain English
Team Collaboration	Limited	Shared workspace for agents + humans
Persistent Memory	Stateless workflows	Agents remember and build on work

How human-in-the-loop works in Lazarus

In Lazarus, human oversight isn't an afterthought—it's built into how agents work.

1. Set the guardrails

Define when your agent should ask for approval. "Always check with me before sending emails to clients." "Run reports automatically, but flag anything unusual." You set the rules in plain English.

2. Agent reaches out when needed

When an agent hits a decision point you care about, it contacts you—via email, Slack, Discord, or Lazarus Chat. You get the context you need to make a decision quickly.

3. Approve, reject, or modify

Review the agent's proposed action and approve it, reject it, or give it new instructions. The agent learns from your feedback and continues working.

4. Autonomous for the rest

Everything else runs automatically. Your agent handles routine tasks at machine speed while you focus on the decisions that actually need human judgment.