OPTIMIZING USER WORKFLOW IN AI EMAIL AUTOMATION VIA BROWSER-RESIDENT DOM MUTATION

Abstract: Professional email management consumes 28% of the workweek and causes 2.6 hours of daily task-switching loss. While Large Language Models optimize text synthesis, standalone dashboards mandate high-friction application toggling and manual clipboard operations. This paper presents a browser-resident architecture using Google Chrome Manifest V3 and a decoupled Spring Boot backend to embed generative AI directly within the communication viewport. By leveraging the native MutationObserver API for real-time DOM mutation monitoring, the system automates context extraction and eliminates manual copy-paste loops. Empirical evaluations confirm an optimized end-to-end latency of 2.0–4.0 seconds, a stable 4.2 MB browser memory footprint, a 65% network payload compression factor, and near-zero measurable CPU utilization during idle monitoring states, significantly mitigating the context-switching dilemma.

Keywords: MutationObserver, Chrome Extension, Browser-Resident Architecture, Context-Switching Optimization, Spring Boot Microservices, Gemini API.