Design and Implementation of a MERN-Based AI Code Generation and Browser-Sandboxed Execution Platform Using Large Language Models

The integration of Large Language Models (LLMs) into software development environments has significantly enhanced developer productivity through intelligent code generation. However, securely and efficiently executing AI-generated code remains a challenge due to potential security risks and infrastructure overhead. This paper presents the design and implementation of a MERN-based web application that integrates the Gemini LLM for multi-language code generation and utilizes browser-based Web Containers for secure sandboxed execution. The proposed system eliminates the need for local setup and server-side execution by leveraging client-side isolated runtime environments. Performance evaluation demonstrates reduced backend load and reliable multi-user execution.