GPT Navigator: Building a Guided Index System 🐰

[mitchell_d00]

Breakdown on how I index GPT knowledge and instruction.
It is basically an electronic filing cabinet

GPT (GPT-4 or GPT-4-turbo) as a personally guided LLM using an index loop data structure. This setup will help you create a custom, well-organized knowledge base where users can navigate information as if they have a personal assistant guiding them.

1. Understand the Index Loop Structure

• Index Loops are a way of organizing information so that each document references key documents and subtopics in a looped structure. This looping structure makes information retrieval efficient and organized.
• Think of it like a library where the main index points you to categories (like “Sales,” “Projects,” “Policies”), and each category has a sub-index that points to specific documents. Each document is aware of related documents and guides users to them, forming a loop that’s easy to navigate.

2. Define the Purpose and Scope of Your GPT

• Start by clarifying what you want this GPT to assist with: Is it for guiding through company procedures, training resources, FAQs, or project management?
• Once you know the purpose, outline the main categories of information users will need. These categories will become your primary index.

3. Create a “Read-First” Document

• This document is your primary guide. It should introduce the GPT’s purpose and provide a main index with all the major topics.
• Include a brief overview of each category and explain how users can navigate the knowledge structure (e.g., “For Sales information, see the Sales Index. For Project data, check the Project Index.”).

Example structure in your “Read-First” document:

Welcome to your Custom GPT Assistant!

**Main Index:**
1. Sales
2. Projects
3. Policies
4. HR Resources
5. Training Materials

To explore a category, ask about it directly, or check its specific index document.

4. Create Sub-Index Documents for Each Category

• For each main topic (Sales, Projects, etc.), create a sub-index document.
• Each sub-index document should list all relevant files for that category. Think of it as a table of contents for each area, but with added links or references to related topics.
• For instance, the “Sales Index” could reference documents on “Lead Generation,” “Sales Scripts,” and “Follow-Up Procedures,” while looping back to the main index for context.

Example structure for the “Sales Index” document:

**Sales Index**

1. Lead Generation Strategy
2. Sales Scripts and Templates
3. Follow-Up Procedures
4. Customer Relationship Management (CRM) Guide
5. Frequently Asked Sales Questions

For broader topics or questions, refer back to the **Main Index** or ask, “What is the Sales process?”

5. Add Cross-References for Looping

• To create the “looped” feel, ensure that each sub-index links back to the “Read-First” document and cross-references other related indexes where applicable.
• For example, the “Sales Scripts” document might reference the “CRM Guide” or point back to the Sales Index for more scripts. This interlinking creates a “loop” effect where users are naturally guided from one document to the next without losing track of the main structure.

6. Upload Documents to GPT and Test the Navigation Flow

• Once your documents are prepared and structured, upload them to the custom GPT’s Knowledge Base.
• Configure the GPT to show the “Read-First” document at the start of each new session. This document will act as the first prompt, giving users an immediate view of the main index.
• Test how the system responds to different questions to ensure the loops work smoothly. Adjust cross-references if necessary to enhance the flow.

7. Configure Conversation Starters and Instructions

• Set up conversation starters in the GPT configuration to guide users. For example:
  • “What information can I help you find today?”
  • “Would you like to start with the Main Index?”
• Include a few specific instructions for the GPT to understand indexing logic, such as:
  • “If the user asks about a category, display the related sub-index.”
  • “Loop back to the ‘Read-First’ document if the user needs a broader overview.”

8. Maintain and Update the Structure as Needed

• Since data and needs evolve, keep your index structure flexible. You can add, update, or reorganize documents and sub-indexes as new content is needed.
• Periodically review how users interact with the system. Are there areas where they get lost or confused? Tweak the index logic to improve clarity and guidance.

Example Workflow

Here’s how a user might interact with this custom GPT setup:

1. User Prompt: “Show me information on Sales.”
2. GPT Response: (Displays “Sales Index” document from the Read-First document)
   • Lists available documents related to Sales, like “Lead Generation Strategy” or “Sales Scripts.”
3. User Prompt: “Tell me more about CRM.”
4. GPT Response: (Shows “CRM Guide” document, loops back to Sales Index if needed)
5. User Prompt: “I need an overview of all resources.”
6. GPT Response: (Returns to the “Read-First” document, showing the Main Index)

Final Tips

• Keep it Modular: Each sub-index document should stand alone but be able to loop back to the main index. This modularity helps users find information in context without getting lost.
• Use Simple Language in Indexes: Avoid jargon in the Read-First document and sub-indexes so that users of all levels can navigate easily.
• Encourage Exploration: Make it easy for users to find related resources, prompting them to explore by mentioning additional documents they might not initially think of.

By setting up this looped index structure, your custom GPT will feel more like a personal guide, helping users navigate a complex web of information with ease. The looping logic makes it intuitive and keeps users grounded, no matter how deep they go into any particular topic.

With the “GPT Navigator” system, ChatGPT wouldn’t just be a conversational tool that provides answers based on a single prompt; it would evolve into an interactive, structured knowledge system—a true guide through complex information. Here’s how it redefines what ChatGPT could be:

1. From Reactive to Proactive Navigation

Instead of waiting for each individual question, ChatGPT could anticipate and link related knowledge, helping users explore topics more deeply and efficiently. Imagine a user not just asking isolated questions but being guided along a logical path, where ChatGPT offers context, related concepts, and suggested next steps, almost like a curated learning experience.

2. Enhanced Contextual Understanding

This guided index system allows ChatGPT to hold onto and use context across multiple queries, making responses richer and more consistent. With structured navigation, ChatGPT could retain an understanding of the broader topic, allowing for multi-layered answers that feel more coherent and grounded.

3. A Tool for Collaborative Knowledge Management

In a workplace setting, ChatGPT could become a dynamic knowledge repository where teams can access, add, and refine information collaboratively. ChatGPT could be the go-to interface for navigating an organization’s knowledge, with each query seamlessly pulling from the most relevant areas of indexed content.

4. A Platform for Autonomous Knowledge Paths

By using “looped” cross-references, ChatGPT could actively help users explore topics from multiple angles, guiding them through branching pathways based on their interests or needs. This goes beyond static Q&A to a system that offers customized “learning paths” or research journeys within the conversation.

5. A Reimagined User Experience

Rather than just seeing ChatGPT as an advanced Q&A machine, users would experience it as an intelligent assistant with a purposeful structure. It could engage in multi-step problem-solving, teach complex topics in logical stages, or serve as a reliable knowledge navigator, providing users with a sense of discovery and progression.

In essence, the “GPT Navigator” approach transforms ChatGPT from a conversational AI into something closer to a knowledge intelligence system—one that doesn’t just respond to questions but actively guides users through complex information landscapes. This is a powerful redefinition, turning ChatGPT into an invaluable partner in both learning and problem-solving.

[mitchell_d00]

Images that help explain the logic and how to start the infrastructure.

I want to create GPTs , feed them knoweldge and want my work colleagues to access that knoweldge - how?

You need to build a custom gpt and upload to its knowledge 20 docs max then anyone that uses it can use your knowledge [The image shows a ChatGPT interface with options to create a custom version of the model, highlighting the "Create a GPT" option under the "My GPTs" section. (Captioned by AI)] [This image shows a screenshot of ChatGPT's configuration settings, highlighting options for uploading files and enabling the Code Interpreter & Data Analysis capability. (Captioned by AI)]

Example of start read index.