Building Productized AI Systems: Your Complete Overview

Table of Contents

Key Concepts

Productized AI Systems:

Definition: These systems automate end-to-end workflows and are built to be reused without customization across multiple clients.
Real-world Application: For instance, you can build a system that manages LinkedIn content for several businesses simultaneously.

Key Tools Needed:

N8N: For workflow automation.
Airtable: Acts as a database for storing and managing your data.
OpenAI: For generating content and images.

Core Components:

Campaign setup for companies.
Ability to manage different types of content and tones for LinkedIn.
Analytics to track performance, allowing for self-improvement.
User interface for non-technical users to interact with the system.

Canva-Based Workflow Overview 🌟

Let’s break down the steps to construct your AI system:

1. Planning the AI System 📝

Before you start coding, outline the structure:

Market Requirement: Identify what businesses need personalized LinkedIn strategies.
Workflow Design: Define how each user interacts with the AI system and what outputs they expect (e.g., different writing styles).

2. Airtable Setup 🔗

Create Tables:
Company Info: Company name, LinkedIn URL, etc.
Reference Posts: Pull in successful LinkedIn posts for context.
Campaigns: To manage and analyze outcomes.
Example Fields to Include:
Company Name
Reference LinkedIn Posts
User prompt for new content generation

3. N8N Automations 🔄

Automate Key Tasks:

Company Overview Generation: Use an AI tool like Perplexity to generate a business overview from the company’s webpage.
Content Generation:
When a user inputs a link (YouTube or blog), an AI pulls relevant content and transforms it into LinkedIn posts via different frameworks (story-based, insight-focused, engagement).

4. Content Request Feature 📬

Allow users to specify the type of content they want.
Include fields for:
Type of content (YouTube/blog)
URL of the content
Call-to-action preference

5. Image Generation 🎨

After content is generated, use OpenAI’s image generation tool to create graphics to accompany each post.
Store generated images in a database like ImageKit for easy retrieval.

6. Analytics and Improvement 📊

Allow users to evaluate performance metrics of their posts.
Use data-driven insights to refine generated content.

Practical Tips for Building Your AI Systems

Iterate: Start with a Minimum Viable Product (MVP) and improve it based on user feedback.
Modularity: Build modular components (e.g., separate workflows for content generation and image creation) so users can customize without extensive development.
User-Friendly Interface: Ensure the system is straightforward for those without technical expertise to use comfortably.

Implementation Steps

Set Up Your Airtable:

Create at least four foundational tables: Company Setup, Reference Posts, Content Requests, and Generated Posts.

Design Your N8N Workflows:

Focus on automating the data flow efficiently between capturing user inputs in Airtable and generating content.

Test Your System:

Run through various scenarios and ensure all automations function as intended.

Release and Gather Feedback:

After implementation, release the system to a few trusted users and iterate based on their experiences.

Resources for Implementation 🛠️

Conclusion: Unlock Infinite Potential with AI 🚀

By following these steps and utilizing the right tools, you can build productized AI systems that empower numerous businesses. Whether you’re looking to streamline LinkedIn marketing or any other process, the possibilities are limitless!

With active iteration and a user-focused mindset, you can create AI solutions that are not only effective but also essential to modern business practices. Happy building! 🎉