AI Model-Based Task Management With Automatic Prompt Composition
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Solution Overview
Problem
Conventional task management methods utilizing generative AI require users to manually search for and compose prompts, leading to decreased efficiency and inconvenience due to the difficulty in managing vast amounts of task information across multiple channels.
Innovation Solution
A method and system that utilizes generative AI to automatically generate a task list, items, and processing results by inputting user information into multiple models, allowing users to select tasks and items without manual prompt composition, and includes security and license authentication for enhanced efficiency and convenience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually search for and compose prompts for task management, then users have control over task details, but task execution efficiency decreases and user convenience deteriorates
Solution Approach 1:
The system enables self-service task management by automatically generating task lists, extracting relevant items, and composing prompts using AI models. The system processes user information autonomously to create structured task outputs without requiring manual user intervention for each task detail, thereby improving both efficiency and convenience
Solution Approach 2:
The system performs preliminary actions by pre-generating comprehensive task lists and identifying relevant items before the user needs to execute specific tasks. This advance preparation of task structures and prompt compositions eliminates the need for users to manually search and compose prompts during task execution, resolving the contradiction between efficiency and ease of operation
2Quantity of substance
If users manage vast amounts of task information across multiple channels, then comprehensive task data is available, but managing this information becomes difficult and time-consuming
Solution Approach 1:
The system segments vast amounts of task information into structured task lists with distinct tasks and related items. By dividing comprehensive task data into organized, manageable units, the system enables efficient processing and retrieval without requiring users to manually handle large volumes of unstructured information across multiple channels
Solution Approach 2:
The AI-based task management system acts as an intermediary between raw task information from multiple channels and the user. It automatically processes, structures, and presents task data in a unified format, eliminating the need for users to manually manage and navigate vast amounts of information across different sources, thereby reducing time consumption
3Productivity
If users directly search for and navigate to necessary information, then accurate information retrieval is achieved, but task execution efficiency decreases
Solution Approach 1:
The system performs preliminary information organization by automatically generating task lists and extracting relevant items before task execution. This advance structuring of information ensures that when users need specific task details, the information is already prepared and accessible, eliminating the need for users to manually search and navigate through information sources
Solution Approach 2:
The system provides feedback by presenting structured task lists and relevant items to users based on their information needs. This automated information delivery mechanism ensures users receive the necessary task information directly without manual searching, improving task execution efficiency while maintaining accurate information retrieval through AI-based matching
Data Source
AI summary
A method for task management and a system therefor are provided. The method according to some embodiments may include generating a task list by inputting user information of a user into a first model, the task list including a plurality of tasks expected to be processed by the user, generating a plurality of items related to the plurality of tasks by inputting the user information into the first model, receiving, from the user, a selection of a task to be processed by the user from among the plurality of tasks, receiving, from the user, a selection of an item related to the selected task from among the plurality of items, composing a first prompt by inputting the selected item into a second model, the first prompt requesting the selected task to be processed based on the selected item and outputting a processing result for the selected task by inputting the first prompt into a third model.