AI Task Generation With Parameter Validation for System Execution

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Solution Overview

Problem

Conventional system management approaches rely on manual efforts that are error-prone and resource-intensive, leading to latencies in task execution.

Innovation Solution

An AI-based system for automated task generation and execution using RAG techniques, LLMs, and rule-based logic to process user queries, validate parameters, and initiate task execution.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual efforts are used for system task execution, then flexibility and adaptability are maintained, but error rates increase and resource consumption increases

Engineering Contradiction:

Improveerror rateVSAvoidmanual effort

Core Design Contradiction:

ReliabilityVSExtent of automation

Solution Approach 1:

The system enables self-service through automated task generation and execution. The task generation engine automatically creates executable tasks from natural language inputs without requiring manual intervention, and the task execution engine autonomously manages task scheduling and monitoring, reducing both error rates and manual resource consumption.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical operations with an automated computational system. Natural language processing substitutes for manual task interpretation, automated task generation replaces manual task creation, and programmatic execution substitutes for manual task implementation, thereby reducing errors while maintaining adaptability through flexible input processing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If manual efforts are used for system task execution, then complex task logic can be handled, but execution time and resource intensity increase

Engineering Contradiction:

Improveexecution speedVSAvoidresource consumption

Core Design Contradiction:

ProductivityVSQuantity of substance

Solution Approach 1:

The system substitutes manual task execution with automated computational processes. The task execution engine programmatically carries out tasks based on generated specifications, eliminating the time and resource overhead associated with manual intervention while maintaining the ability to handle complex task logic through structured processing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system performs preliminary actions by automatically generating complete task specifications and validation rules before execution. This pre-processing of task logic into structured formats enables faster execution without requiring manual intervention during the actual task performance, thereby improving productivity while reducing resource consumption.

Inventive Principle:

Principle #10Preliminary action

3Loss of time

If automated task generation is implemented, then execution speed improves, but system complexity increases

Engineering Contradiction:

Improvetask execution latencyVSAvoidsystem architecture

Core Design Contradiction:

Loss of timeVSDevice complexity

Solution Approach 1:

The system segments the automated task management process into distinct functional modules: a task generation engine that creates task specifications from natural language inputs, a task execution engine that manages task scheduling and monitoring, and a validation component that ensures task correctness. This segmentation reduces system complexity by making each component independent and manageable while maintaining fast execution through optimized modular processing.

Inventive Principle:

Principle #1Segmentation

4Measurement precision

If AI-based processing is used, then task accuracy improves, but computational resource requirements increase

Engineering Contradiction:

Improveparameter validation accuracyVSAvoidcomputational energy

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system applies partial AI-based processing by using natural language processing and validation logic only for critical task parameters rather than processing entire task workflows with full AI complexity. This selective application of AI techniques maintains high accuracy for parameter validation while reducing overall computational energy requirements compared to comprehensive AI-based task execution.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS20260017087A1Automated task generation and execution using artificial intelligence-based data structure processing

Publication Date: 2026.01.15 DELL PROD LP

AI summary

Methods, apparatus, and processor-readable storage media for automated task generation and execution using artificial intelligence-based data structure processing are provided herein. An example computer-implemented method includes obtaining a user query related to executing at least one system task in connection with one or more user-provided system task parameters; determining contextual information pertaining to the at least one system task by processing at least portions of one or more task-related data structures using a set of one or more artificial intelligence techniques; validating the one or more user-provided system task parameters by processing the user query and at least a portion of the determined contextual information; generating instructions for executing the at least one system task based at least in part on the validating of the one or more user-provided system task parameters; and initiating automated execution of the at least one system task based on the generated instructions.