Turn all your meetings into viral content

Key Concepts

• Meeting transcription and content repurposing
• Thought leadership content creation
• AI-powered content generation
• Automation workflows (Make.com, Zapier)
• Cloud API for natural language processing
• Social media posting automation (LinkedIn, Twitter)
• Webhooks and Mailhooks for data transfer
• JSON data format

1. Introduction: The Problem and Solution

The speaker discusses the difficulty of consistently creating content and sharing thoughts publicly, contrasting it with the ease of articulating ideas in conversations. He introduces a workflow that automates the process of turning meeting discussions into social media posts. The core idea is to leverage AI to extract key insights from meeting transcripts and generate content drafts, which are then refined and posted to social media.

2. Workflow Overview

The workflow consists of the following steps:

1. Meeting Recording: Use a meeting recording tool (e.g., Tactic) to transcribe meetings.
2. AI-Powered Content Generation: Automatically generate social media posts from meeting transcripts using AI.
3. Content Refinement: Receive the generated posts via email, allowing for manual editing and customization.
4. Automated Posting: Reply to the email with modifications and attachments to trigger automated posting to social media platforms (e.g., Twitter, LinkedIn).

3. Detailed Breakdown of the Automation Workflow

3.1. Meeting Recording and Transcription

• Tool: Tactic is the preferred tool, but any meeting recording tool with Zapier or Make.com integration (or webhook support) can be used.
• Requirement: The tool must be able to send meeting transcripts and titles to a webhook.

3.2. Data Transfer with Zapier

• Purpose: Used as a bridge between Tactic and Make.com due to the lack of direct integration.
• Function: Triggers when a new transcript is available in Tactic and sends the transcript content and meeting title to a webhook in Make.com.

3.3. Content Generation with Make.com and Cloud API

• Platform: Make.com is used to orchestrate the automation.
• Blueprint: A blueprint for the Make.com scenario is provided, allowing users to easily replicate the workflow.
• Cloud API: Cloud API is used for natural language processing and content generation.
  • Model: The latest model from Cloud API is recommended for writing human-like content.
  • Tokens: The concept of tokens (pieces of words) is explained, and the maximum token limit for the output is set.
• System Prompt: A detailed system prompt is used to guide Cloud API in generating relevant and engaging content.
  • Role Definition: Defines Cloud API as an expert in thought leadership content analysis and creation.
  • Personal Information: Includes information about the speaker's expertise and background.
  • Insight Identification: Specifies criteria for identifying valuable insights, personal opinions, unique methodologies, and practical examples.
  • Content Style Guidelines: Provides guidelines for leading with a compelling hook, presenting a common problem, offering actionable solutions, and including real-world examples.
  • Output Format: Defines the desired output format as JSON, including fields for the main idea, title (short and long versions), and content.
  • Examples: Includes examples of good thought leadership posts to guide Cloud API's writing style.

3.4. Data Processing and Email Delivery

• Data Structure Validation: A module is used to ensure the data structure is correct and in the desired format (an array of collections).
• Email Notification: An email is sent to the speaker with the generated content for each identified insight.
  • Content: The email includes the meeting title, participant list, and short and long versions of the generated content.

4. Social Media Posting Automation

4.1. Mailhook Trigger

• Mailhook: A Mailhook is used to trigger the automation when an email is received.
• Function: The speaker replies to the email containing the generated content, modifies it, and sends it to the Mailhook email address.

4.2. LinkedIn Posting

• Integration: Direct integration with LinkedIn allows for easy posting.
• Attachments: Attachments to the email are posted as images in the LinkedIn post.

4.3. Twitter Posting

• Complexity: Twitter posting is more complex due to API limitations.
• API Versions: Requires using the older V5 API to upload images.
• Developer Account: Requires creating a Twitter developer account and generating API keys and tokens.
• Process: Uploads the image using the V5 API, retrieves the media ID, and then uses the media ID and the text from the email to create the tweet.

5. Tools and Accounts Required

• Meeting recording tool (e.g., Tactic)
• Zapier account
• Make.com account
• Cloud API account
• OpenAI API account
• Gmail account (or other email provider)
• LinkedIn account
• Twitter developer account

6. Notion File and Blueprints

• Access: A Figma file is provided with a link to a Notion page containing the prompts and blueprints.
• Content: The Notion page includes:
  • Text prompt (in markdown format)
  • JSON files for importing the Make.com scenario blueprint

7. Key Arguments and Perspectives

• Efficiency: The workflow significantly increases content output with minimal effort.
• Personalization: The system allows for manual refinement of AI-generated content, ensuring it aligns with the speaker's style and voice.
• Actionability: The email-based workflow ensures that content ideas are not forgotten and are actively considered for posting.
• Scalability: The system can be adapted to different social media platforms and content types.

8. Conclusion

The speaker presents a comprehensive workflow for automating the creation and distribution of thought leadership content. By leveraging AI, automation tools, and a well-defined system prompt, users can efficiently transform meeting discussions into engaging social media posts, saving time and increasing their online presence. The provided blueprints and resources make it easy for others to implement and customize the workflow to their specific needs. The speaker acknowledges that the system can be further optimized for even better results, but the current implementation provides a significant improvement in content creation efficiency.