How AI Accelerates Frontend Development: Building an Auto‑Switch Proxy Browser Extension

1 Background

Rapid AI development is reshaping frontend work. Tools such as Cursor and Trae act as a second brain, offering powerful code completion, context understanding, automatic refactoring, and documentation generation. In our daily development we use Whistle as a network proxy, and to avoid frequent manual configuration switches we built an automatic proxy‑switching browser extension.

2 Feature Implementation

2.1 Core Features

Automatic proxy switching : When accessing pre‑configured domains, the plugin automatically matches and switches to the corresponding Whistle rule.

Manual fallback selection : Users can manually override the current proxy and enable/switch the Default rule.

Rules parsing : Syntax parsing of Rules so users can view and manipulate each proxy rule in the UI.

2.2 Technology Selection and Project Initialization

AI is used to research frameworks, compare GitHub activity, community health, and generate a concise recommendation report.

AI then generates a complete project scaffold—including directory structure, basic configuration, and dependencies—in about five minutes.

2.3 Whistle API Parsing

The plugin interacts with a local Whistle service to fetch and switch rules. Instead of manually reading source code, Cursor’s AI automatically analyzes the API and produces a structured internal documentation.

2.4 Page Design and Documentation

AI assists in writing requirement and interaction documents, suggesting page structure, data flow, and test points. Templates for product‑manager, UI/UX, and design specifications are provided.

3 Feature Effects

Early versions revealed issues such as undefined edge cases, incomplete interaction logic, and context loss. Iterative AI optimization combined with manual review quickly resolved most problems.

4 Recommendations

Using Rules to inject project conventions into AI prompts dramatically reduces miscommunication. Different rule scopes (User, Project, Team, AGENTS.md) are described with typical content and usage advice.

5 Summary and Outlook

AI boosts coding efficiency but still lacks continuous context memory and engineering awareness, leading to challenges in understanding, frequent prompt tuning, and inconsistent model behavior.