Lecture Notes: Building an AI-Powered LinkedIn Content System

Introduction

• Objective: To create an AI-driven content system for LinkedIn using make.com.
• Request-driven project aiming to automate content sourcing and repurposing for LinkedIn growth.

System Overview

• Source: Gather high-quality posts from LinkedIn using scrapers.
• Repurpose: Use AI to rewrite posts into a unique tone of voice.
• Publish: Post on LinkedIn to boost engagement and growth.

Initial Steps & Considerations

• Unscripted Development: Demonstrates raw development process, including live problem-solving.
• Scraping Posts: Utilize various available scrapers for pulling posts from LinkedIn.
• Data Storage: Suggests using Google Sheets to store posts, facilitating future content checks and updates.

System Workflow

Scraping LinkedIn Posts

• Use Appify for scraping to avoid the hassle of building a custom scraper.
• Focus on obtaining post text and relevant metadata. Exclude personal posts and repeated use of images.

Data Management

• Google Sheets as Database: Store retrieved posts with unique IDs to track new vs. old posts.

AI Repurposing with GPT

• Filtering Posts: Identify evergreen posts suitable for repurposing using AI filtering.
• Rewriting Posts: Employ GPT models to rewrite posts, maintaining similar length and thematic content.
• Prompt Design: Include system prompts, user prompts, and example transformations to aid AI in style adaptation.

Post Scheduling & Publishing

• Scheduling Posts: Implement logic to distribute posts evenly over time, leveraging Google's scheduling features.
• Posting Automation: Connect make.com to LinkedIn to automate the posting process.

Practical Implementation

• AI Setup: Use set variables to streamline AI inputs and maintain clean data flow.
• Error Handling: Demonstrates error management within the automation system.
• User Interaction: Includes viewer engagement and request handling.

Challenges & Solutions

• Formatting and Tokens: Address issues with post formatting and new line implementations.
• Schedule Management: Sort posts by scheduled time to ensure timely posting.

Conclusion

• Offers a robust, scalable system for LinkedIn content automation.
• Encourages viewer interaction for further customization and expansion of content systems.

Additional Notes

• Ethical Considerations: Discuss the ethical implications of content repurposing.
• Future Enhancements: Potential to add image generation/modification and enhanced personalization features.