Published Paper Details:

Traditional enterprise task management systems often suffer from rigid user interfaces, excessive DOM rendering loads, and slow development lifecycles. This paper presents the design and implementation of an AI-Augmented Task and Project Management System engineered to optimize both the developer workflow and the end-user experience. The proposed framework utilizes AI-driven prototyping tools, specifically Whisk and Stitch, to rapidly generate responsive UI grids and accessibility-compliant color palettes within the Antigravity IDE. To address performance bottlenecks associated with massive datasets, the system implements client-side caching and an Intersection Observer-based infinite scroll mechanism, reducing dashboard rendering latency to under 200ms. Furthermore, the architecture integrates a native HTML5 drag-and-drop Kanban board and a deterministic hashing algorithm for visual week-view scheduling. Secure data transit is maintained via JSON Web Tokens (JWT) and centralized RESTful API routing. Experimental deployment demonstrates significant improvements in UI performance, development speed, and overall system scalability