Generate Social Media Content from Video Transcripts with Gemini AI & Airtable

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Built by Kurt Bijl Kurt Bijl
Created on July 13, 2025

Description

🎬 Social Media Content Generator

Workflow Overview
Automated social media content creation from video transcripts

🎯 Trigger: Airtable Webhook
Action**: Receives webhook from Airtable automation
Data**: RecordId and action type (e.g., "post-ig")
Purpose**: Starts the content generation pipeline

πŸ“Š Step 1: Fetch Record
Node**: Airtable (Get Record)
Action**: Retrieves full record data using RecordId
Data**: Name, transcript, and other fields

πŸ“ Step 2: Create Google Drive Folder
Node**: Google Drive (Create Folder)
Action**: Creates blue folder in /tutorials directory
Name**: Uses record Name field
Updates**: Stores folder ID back to Airtable

πŸ€– Step 3: AI Content Analysis
Node**: AI Agent with Google Gemini 2.5 Flash
Input**: Video transcript from Airtable
Structured Output**: JSON with all social formats:
YouTube title & description
YouTube thumbnail text
Twitter thread (array)
LinkedIn post
Instagram caption
TikTok caption
YouTube Shorts caption
Relevant tags

πŸ’Ύ Step 4: Save Transcript File
Node**: Google Drive (Create from Text)
Action**: Saves transcript as text file
Location**: Inside the created folder
Name**: Uses record Name field

πŸ“‹ Step 5: Update Airtable Results
Node**: Airtable (Update Record)
Data**: All AI-generated social media content
Special**: Twitter thread array joined with newlines

🎯 Result: Complete social media content suite ready for multi-platform publishing, organized in Google Drive with all data stored in Airtable.

This workflow was created by Kurt Bijl and shared publicly on the n8n community template library. n8nFind indexes it for discovery — the workflow remains the property of its original creator.

Nodes Used (5)

AI Agent
@n8n/n8n-nodes-langchain.agent
Airtable
n8n-nodes-base.airtable
Google Drive
n8n-nodes-base.googleDrive
Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini
Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured