Building and Monetizing an AI-Powered Chrome Extension Using GPT-01

Introduction

• Objective: Building a monetized AI-powered copilot Chrome extension using GPT-01 system.
• Example: LinkedIn Genie - reads comments on a post and generates responses.

System Operation

• Validates if a user has purchased the extension through Stripe on a subscription basis (e.g., £5, £10, £50, £100 per month).
• Users sign up, receive a unique API key via email.
• API key is used to validate user access without repeated entry.

Data Management

• Record creation in Airtable for all purchasers, storing names, emails, and subscription validation.
• Automation checks subscription status, providing access only to paying subscribers.

Building the AI Co-pilot

• Concept: Create AI co-pilots for varied applications, e.g., summarizing YouTube videos, chatting with videos.
• Monetization: Charge a monthly subscription fee (e.g., £10/$10) for access.

Technical Setup

• System Components:
  • Chrome Extension: Upload files (manifest.json, content.js, style.css, popup.html) creating a structured setup.
  • Webhook Connection: Data sent via a webhook to services like make.com for processing.
  • Stripe Integration: Set up product pricing and subscription models in Stripe.
  • API Key Usage: Use API keys for validation, linked to Stripe subscription status.

Automation Process

• Event Handling: Stripe watches for new subscriptions to retrieve customer details.
• Airtable Integration: Logs customer data, generates unique ID functioning as an API key.
• Email Notifications: Automatically send API key to new subscribers via email.
• Validation: Check if user API key is valid, providing access to the extension.

Creating the Chrome Extension

• Design: User interface involving chat windows, gradient headers, and animation styles.
• Functionality: Add chat buttons, send messages to webhook with chat history and transcript.
• Customization: Modify styles, header size, chat window dimensions, and animations.

Finalizing and Testing

• Debugging and Iteration: Update code based on UI/UX requirements and feedback.
• Ensuring Functionality: Validate subscription status before enabling chat features.
• Continuous Testing: Run modules to ensure correct data processing and automation flow.

Conclusion

• Outcome: Successfully built an AI-powered extension that monetizes conversations with YouTube videos.
• Feasibility: Demonstrated potential for income generation through subscription models using AI and Chrome extensions.
• Future Directions: Explore further applications and automation enhancements with GPT-01 and its upcoming versions.