LLM-Driven User Interface Customization for Mixed Skill Levels
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Solution Overview
Problem
Existing user interfaces are unable to automatically configure to fit the specific desires and needs of individual users, as each user is unique and may lack programming experience to adjust the interface, leading to frustration and reduced usability.
Innovation Solution
A combination of a large language model and a binder generates consumable user interface components and artifacts, using pre-engineered prompts and user customization data to modify the interface based on individual user preferences and skill levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a user interface provides advanced features and complex technical information, then the application functionality is improved, but non-expert users become frustrated and unable to use the application
Solution Approach 1:
The user interface dynamically adapts its complexity and content based on the user's skill level. The system transitions from a static interface to a dynamic one that reconfigures itself according to user characteristics, allowing the same application to serve both experts and non-experts effectively.
Solution Approach 2:
Different portions of the user interface are customized according to the user's expertise. Non-expert users receive simplified views with essential functions only, while expert users access comprehensive features and technical details. This local customization ensures each user experiences appropriate complexity in relevant areas.
2Ease of operation
If a user interface is simplified for non-expert users, then ease of operation is improved, but advanced features and complex functionality become inaccessible
Solution Approach 1:
The interface maintains dynamic adaptability, allowing users to transition between simplified and advanced modes as needed. Non-expert users start with simplified interfaces but can access advanced features when required, while expert users have direct access to all functionality.
Solution Approach 2:
The simplified user interface contains within it the capability to access advanced features. The basic interface serves as a container that can reveal or access more complex functionality when needed, allowing non-expert users to start simple and progressively access advanced features as they develop expertise or require them.
3Adaptability or versatility
If a user interface is customized for each individual user, then user-specific needs are met, but the complexity of configuring and maintaining the interface increases
Solution Approach 1:
The system automatically configures user interfaces based on user profiles and characteristics without requiring manual intervention from developers or administrators. The interface generation process is self-service, using algorithms to create customized interfaces automatically, thereby reducing the complexity of configuration and maintenance.
Solution Approach 2:
A single interface generation system serves multiple user types and scenarios. The same underlying mechanism generates interfaces for both expert and non-expert users, handling diverse customization requirements through a unified approach, which reduces overall system complexity compared to maintaining separate interface configurations.
4Manufacturing precision
If manual configuration of user interfaces is required, then precise customization is achieved, but users without programming experience cannot adjust the interface
Solution Approach 1:
The system automatically generates customized user interfaces based on user profiles without requiring users to manually configure or program the interface. This self-service approach eliminates the need for programming knowledge while still achieving precise customization tailored to each user's needs and expertise level.
Solution Approach 2:
An automated interface generation system acts as an intermediary between user characteristics and interface configuration. Instead of users directly configuring interfaces (which requires programming skills), the system mediates this process by automatically translating user profiles into appropriately customized interfaces, preserving precision while improving accessibility.
Data Source
AI summary
A method including generating a revised prompt from user customization data for customizing a user interface of an application, a pre-engineered prompt, and an application artifact from the application. The method also includes generating an output by executing a large language model on the revised prompt. The method also includes receiving a modified template generated from the user customization data and at least one of a set of templates. The method also includes transforming the output of the large language model and the modified template into both a consumable user interface component and a user interface artifact. The method also includes modifying a user interface of the application by applying the consumable user interface component and the user interface artifact to the application.