Create ideal customer profiles from LinkedIn data with Airtop and Claude AI
Needs changesNeeds changes. This template uses 1 thing(s) that n8n 3.0 removes: AI Agent v1 (old agent modes). 1 breaking item(s) found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 7 nodes and runs when a chat message arrives. Along the way it connects Anthropic Chat Model, Airtop and Google Docs.
How it runs
Trigger: When a chat message arrives.
- AI Agent: runs an AI agent, with model: Anthropic Chat Model; 1 tool (Airtop Data Enrichment); memory: Simple Memory
- Google Docs: uses Google Docs
- Google Docs: update
Services it uses
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in AI Agent (v1.9): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) AI Agent (v1.9) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (6)
- Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - AI Agent
@n8n/n8n-nodes-langchain.agent - Anthropic Chat Model
@n8n/n8n-nodes-langchain.lmChatAnthropic - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Airtop Tool
n8n-nodes-base.airtopTool - Google Docs
n8n-nodes-base.googleDocs
From the author
Define Your ICP from Customer LinkedIn Profiles Use Case This automation helps marketing and sales teams define their Ideal Customer Profile (ICP) using real LinkedIn profiles of current high-fit customers. By enriching and analyzing profile data, it…