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LetsVibeAI

Autonomous GTM & Sales Automation Engine/Lab 2

LinkedIn Content Automation with ChatGPT & Make.com

Build a complete content pipeline from ideation to posting.

Learning Objectives

  • Build a complete content pipeline from ideation to posting
  • Automate LinkedIn post generation using AI + no-code automation
  • Implement a review-and-post workflow with safety checks
  • Scale content production without sacrificing quality

What You'll Build

A content automation pipeline:

ChatGPT → 30-Day Content Calendar → Google Sheets → Make.com → LinkedIn Post

Step-by-Step

Step 1: Generate a 30-Day Content Calendar in ChatGPT

Prompt ChatGPT:

"Generate a 30-day LinkedIn content calendar for [your niche/topic]. Each day should include: date, topic, post draft (within 2700 characters), 3-5 relevant hashtags. Format as a table."

Review and customize the output for your voice and audience.

Step 2: Set Up Google Sheets

Create a folder in Google Drive (e.g., "Content Automation").

Create a spreadsheet with columns:

Date Topic Post Draft Hashtags Status Date Posted

Paste your 30-day calendar into the sheet.

Step 3: Build the Make.com Scenario

Modules:

  1. Schedule — Set to run daily at 9:00 AM
  2. Google Sheets → Search Rows — Find rows where Date = today AND Status is empty
  3. Filter — Ensure content hasn't been posted yet
  4. LinkedIn → Create Post — Connect LinkedIn account, map Post Draft to content
  5. Google Sheets → Update Row — Set Status to "Posted" and Date Posted to {{now}}

Step 4: Test and Refine

Run a manual test with a single row. Check:

  • Does the post format correctly on LinkedIn?
  • Is the character count under 2700?
  • Are hashtags included?

Step 5: Add AI Content Generation (Optional)

Instead of pre-writing all 30 posts, add an AI module between Sheets and LinkedIn:

Sheet (topic only) → ChatGPT/Claude → Generate Post → LinkedIn

This gives you fresh content daily with the latest context.

Best Practices

Practice Why
Keep posts under 2,700 characters LinkedIn's hard limit
Use Search Rows with filters Prevents duplicate posting
Test with multiple AI providers Different tones for different content types
Always include a human review step AI-generated content needs quality control
Schedule at consistent times Build audience expectations

Troubleshooting

Problem Solution
Post too long Add a Make.com text aggregator module to truncate
Wrong post format Use LinkedIn's API doc to check allowed formats
Duplicate posts Check your filter conditions
Authentication expired Reconnect your LinkedIn account in Make.com

Key Takeaways

  • A content automation pipeline removes the daily "what do I post?" friction
  • Pre-generating a calendar gives you consistency; AI daily generation gives you freshness
  • The review step remains critical — AI-generated content should never post without oversight
  • This same pattern works for Twitter/X, Instagram, and other platforms

Extension Ideas

  • Multi-platform distribution (LinkedIn + Twitter + blog)
  • Performance tracking (engagement metrics back to the sheet)
  • A/B testing different post styles
  • Comment reply automation for engagement
  • Content repurposing (long-form → thread → post → carousel)