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Building an AI-Powered LinkedIn Message Auto-Reply System with n8n

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Overview

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Learn to build an AI-powered inbox automation system that automatically categorizes and routes LinkedIn messages while maintaining human oversight. Follow along as two developers create a complete workflow solution using n8n to tackle the common startup problem of being overwhelmed by direct messages and requests. Discover how to set up webhook integrations with Unipile, create dynamic knowledge bases in Notion, implement AI message classification and response generation, and integrate Slack for team collaboration with human-in-the-loop approval processes. Master the technical implementation including webhook configuration, database setup, AI prompt engineering, LinkedIn API integration, Slack Block Kit Builder usage, and troubleshooting common workflow issues. Gain practical experience with automation tools while building a scalable solution that can route requests to appropriate team members and generate contextual responses based on your organization's knowledge base.

Syllabus

00:00 - Intro
00:59 - Problem: overload of inbound requests
01:40 - Solution: Request router AI workflow
04:10 - Rundown of the plan
05:14 - Create webhook in Unipile & n8n
07:40 - Set up Notion database
10:05 - Transform Request Router data for AI
11:40 - Message classifier and AI reply generation
15:05 - Map request data to system prompt and structure output
18:06 - Set up LinkedIn message sending
22:07 - Intermission
22:35 - Human in the loop with Slack
24:04 - Slack Block Kit Builder
25:56 - Hook up Block UI in n8n
33:40 - Testing & troubleshooting slack + n8n
38:20 - Testing approve button
41:44 - Forgot to activate webhook trigger
45:50 - Try to get LinkedIn messages marked as read
46:41 - Wrap up

Taught by

n8n

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