Monitor LinkedIn posts & create AI content digests with OpenAI and Airtable

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Automatically monitor LinkedIn posts from your community members and create AI powered content digests for efficient social media curation. This template is perfect for community managers, content ...

Best for

AI Summarization automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.scheduletrigger, n8n-nodes-base.httprequest, n8n-nodes-base.code, n8n-nodes-base.wait, n8n-nodes-base.splitinbatches, n8n-nodes-base.if, n8n-nodes-base.noop, n8n-nodes-base.set

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Anna Bui.

Original n8n.io source

1.1 Workflow description

Title: Monitor LinkedIn posts & create AI content digests with OpenAI and Airtable
Workflow name: Monitor LinkedIn posts & create AI content digests with OpenAI and Airtable

Automatically monitor LinkedIn posts from your community members and create AI-powered content digests for efficient social media curation.

This template is perfect for community managers, content creators, and social media teams who need to track LinkedIn activity from their network without spending hours manually checking profiles. It fetches recent posts, extracts key information, and creates digestible summaries using AI.

Good to know

API costs apply - LinkedIn API calls ($0.01-0.05 per profile check) and OpenAI processing ($0.001-0.01 per post)
Rate limiting included - Built-in random delays prevent API throttling issues
Flexible scheduling - Easy to switch from daily schedule to webhook triggers for real-time processing
Requires API setup - Need RapidAPI access for LinkedIn data and OpenAI for content processing

How it works

Daily profile scanning - Automatically checks each LinkedIn profile in your Airtable for posts from yesterday
Smart data extraction - Pulls post content, engagement metrics, author information, and timestamps
AI-powered summarization - Creates 30-character previews of posts for quick content scanning
Duplicate prevention - Checks existing records to avoid storing the same post multiple times
Structured storage - Saves all processed data to Airtable with clean formatting and metadata
Batch processing - Handles multiple profiles efficiently with proper error handling and delays

How to use

Set up Airtable base - Create tables for LinkedIn profiles and processed posts using the provided structure
Configure API credentials - Add your RapidAPI LinkedIn access and OpenAI API key to n8n credentials
Import LinkedIn profiles - Add community members' LinkedIn URLs and URNs to your profiles table
Test the workflow - Run manually with a few profiles to ensure everything works correctly
Activate schedule - Enable daily automation or switch to webhook triggers for real-time processing

Requirements

Airtable account - For storing profile lists and managing processed posts with proper field structure
RapidAPI Professional Network Data API - Access to LinkedIn post data (requires subscription)
OpenAI API account - For intelligent content summarization and preview generation
LinkedIn profile URNs - Properly formatted LinkedIn profile identifiers for API calls

Customising this workflow

Change monitoring frequency - Switch from daily to hourly checks or use webhook triggers for real-time updates
Expand data extraction - Add company information, hashtag analysis, or engagement trending
Integrate notification systems - Add Slack, email, or Discord alerts for high-engagement posts
Connect content tools - Link to Buffer, Hootsuite, or other social media management platforms for direct publishing
Add filtering logic - Set up conditions to only process posts with minimum engagement thresholds
Scale with multiple communities - Duplicate workflow for different LinkedIn communities or industry segments

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Schedule Trigger

Type / Role: n8n-nodes-base.scheduleTrigger - scheduleTrigger
Config choices: Version 1.2

Block 2 - Get Daily LinkedIn Post

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 3 - Extract Info

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 4 - Random Delay

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 5 - Wait

Type / Role: n8n-nodes-base.wait - wait
Config choices: Version 1.1

Block 6 - Loop Over Items

Type / Role: n8n-nodes-base.splitInBatches - splitInBatches
Config choices: Version 3

Block 7 - If

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.2

Block 8 - No Operation, do nothing

Type / Role: n8n-nodes-base.noOp - noOp
Config choices: Version 1

Block 9 - No Operation, do nothing2

Type / Role: n8n-nodes-base.noOp - noOp
Config choices: Version 1

Block 10 - Set Date Variables

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 11 - Daily Check

Type / Role: n8n-nodes-base.airtable - airtable
Config choices: Version 2.1

Block 12 - Lookup CB Community

Type / Role: n8n-nodes-base.airtable - airtable
Config choices: Version 2.1

Block 13 - If2

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.2

Block 14 - No Operation, do nothing3

Type / Role: n8n-nodes-base.noOp - noOp
Config choices: Version 1

Block 15 - Clean Profile Data1

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 16 - OpenAI Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 17 - Structured Output Parser

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.2

Block 18 - Check if post exist?

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.2

Block 19 - Lookup Post

Type / Role: n8n-nodes-base.airtable - airtable
Config choices: Version 2.1

Block 20 - Formatting

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 21 - LinkedIn Digestion

Type / Role: @n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices: Version 1.6

Block 22 - No Operation, do nothing1

Type / Role: n8n-nodes-base.noOp - noOp
Config choices: Version 1

Block 23 - Create Digestion

Type / Role: n8n-nodes-base.airtable - airtable
Config choices: Version 2.1

Block 24 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Showing the first 24 of 30 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow	Monitor LinkedIn posts & create AI content digests with OpenAI and Airtable
Complexity	advanced
Nodes	30
Categories	AI Summarization
Author	Anna Bui
Published	24 Sept 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/8895/8895.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source AI Summarization workflows

Frequently asked questions

What does Monitor LinkedIn posts & create AI content digests with OpenAI and Airtable do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your AI Summarization use case.

Anna Bui

6 workflows

Nodes

n8n-nodes-base.scheduletrigger n8n-nodes-base.httprequest n8n-nodes-base.code n8n-nodes-base.wait n8n-nodes-base.splitinbatches n8n-nodes-base.if n8n-nodes-base.noop n8n-nodes-base.set

Complexity

advanced

Published 24 Sept 2025

Likes 0

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Install path: /data/workflows/8895/8895.json

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Monitor LinkedIn posts & create AI content digests with OpenAI and Airtable

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Good to know

How it works

How to use

Requirements

Customising this workflow

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Schedule Trigger

Block 2 - Get Daily LinkedIn Post

Block 3 - Extract Info

Block 4 - Random Delay

Block 5 - Wait

Block 6 - Loop Over Items

Block 7 - If

Block 8 - No Operation, do nothing

Block 9 - No Operation, do nothing2

Block 10 - Set Date Variables

Block 11 - Daily Check

Block 12 - Lookup CB Community

Block 13 - If2

Block 14 - No Operation, do nothing3

Block 15 - Clean Profile Data1

Block 16 - OpenAI Chat Model

Block 17 - Structured Output Parser

Block 18 - Check if post exist?

Block 19 - Lookup Post

Block 20 - Formatting

Block 21 - LinkedIn Digestion

Block 22 - No Operation, do nothing1

Block 23 - Create Digestion

Block 24 - Sticky Note1

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions