Enhancing Custom-GPTs with Simple Inheritance

Current State: Custom-GPTs are configured individually, leading to repetitive tasks and a lack of a unified structure. This results in inefficiencies in both development and management.

Proposal for Improvement with Simple Inheritance:

  1. Utilizing Existing Custom-GPT Configurations for New Custom-GPTs: By inheriting from a higher-level or reference Custom-GPT configuration, new Custom-GPTs can leverage pre-established settings. This method reduces the need to build or copy each configuration from the ground up, enhancing efficiency.
  2. Organized Display of Custom-GPTs in a Directory-like Format: Simple inheritance enables a more structured arrangement of Custom-GPTs, akin to a file system in an operating system like Windows. This organization aids in easily identifying and managing different GPT variants.
  3. Concurrent Configuration Updates in Subsequent Custom-GPTs When Modifying a Parent Configuration: Altering the configuration of a higher-level Custom-GPT automatically updates all related Custom-GPTs derived from it. This feature ensures uniformity and streamlines the process of maintaining and updating multiple Custom-GPTs.

This approach aims to streamline the creation and administration of Custom-GPTs, making it more coherent and user-friendly.


Great idea!

Currently I have a lot of training files. When I want to build a new Custom GPT at t-sql.app, I “feed” my training files manually to the new GPT… Saves time, but inheritance sounds much better.