Creator-Focused Chatbot Research

The Problem: Discovering Creator-Specific Knowledge

In today's digital landscape, content creators produce valuable insights that are often buried in articles, podcasts, and videos. While there's plenty of long-form content available, accessing specific information quickly can be challenging. Generic AI tools provide standardized answers, but miss the unique perspectives that make a creator's content valuable.

I've come to a core belief about content in this new world:

"In the new age of AI, most knowledge is going to become commodified... But unique insights are going to become more valuable and more discoverable because users can stumble upon them without even knowing what to ask."

The Solution: Content Specific Chatbots

Content specific chatbots solve this problem by creating AI-powered assistants trained on a specific creator's content. This allows fans and followers to have interactive conversations about concepts and get insights directly inspired by the creator's unique expertise. To test this hypothesis I built a chatbot that relies on references and citations to specific content.

The first implementation was built for Ibrahim Bashir's "Run the Business" blog, but the architecture is designed to be adaptable for any creator with a body of written content.

How It Works

The chatbot is built by ingesting content from a creator's blog or articles, creating embeddings, and using AI to generate conversational responses based on semantic search.

graph TD
    A[Start] --> B[Scrape articles from creator's site]
    B --> C[Process article content]
    C --> D[Split content into chunks]
    D --> E[Generate embeddings with OpenAI API]
    E --> F[Store in vector database]
    F --> G[User asks question]
    G --> H[Generate embedding for query]
    H --> I[Search for similar chunks]
    I --> J[Retrieve relevant content]
    J --> K[Generate response with OpenAI]
    K --> L[Return answer to user with citations]
    L --> G

Here's a detailed view of how the system processes user queries:

graph TD
    A[User submits question] --> B[Create embedding for query]
    B --> C[Search vector store for similar content]
    C --> D[Retrieve top relevant chunks]
    D --> E{Are chunks found?}
    E -->|Yes| F[Prepare context with chunks]
    E -->|No| G[Use general knowledge mode]
    F --> H[Send query + context to OpenAI]
    G --> H
    H --> I[Format response with citations]
    I --> J[Return answer to user]
    J --> K[Log query for future improvement]

Business Model Implications

The creator chatbot offers several potential business advantages:

1. Content Discovery: Makes it easier for users to find specific insights across a creator's entire body of work

2. Paywall Teasing: Provides brief insights from premium content, potentially increasing subscriptions

3. Engagement: Keeps users interacting with the creator's content in a novel way

4. Unique Perspective Highlighting: Showcases what makes the creator's viewpoint special compared to generic knowledge

Demo

The video demo shows a user interacting with the Ibrahim version of the chatbot. Key moments include:

• Asking about product market fit and discovering Ibrahim's unique "Product Market Flex" concept

• Viewing citations that link back to original content

• Seeing how paywall content can be referenced without giving full access

Extensibility

While the initial implementation focused on Ibrahim Bashir's content, the architecture is designed to work with any creator who has:

1. A substantial body of written content

2. Unique perspectives or frameworks

3. Content that's organized in a way that can be processed

A templated version of the code is available here: https://github.com/brayden-s-haws/creator_chatbot

Conclusion

As AI makes general knowledge increasingly commodified, the value of unique perspectives will grow. Creator-specific chatbots represent an opportunity to enhance the discovery and accessibility of these perspectives, benefiting both creators and their audiences.