Transforming B‑End Admin UI into a C‑Style Experience with GPT‑Image‑2.0

AI‑powered UI redesign pipeline

Generate a basic functional web page (or start from an open‑source project) as a rough scaffold.

Take a screenshot of the scaffold and feed it to GPT‑Image‑2.0 , which redraws the interface with higher visual quality and modern aesthetics.

Extract a complete UI specification (colors, typography, spacing) from the AI‑enhanced image.

Submit the screenshot together with the extracted spec back to the AI model, which then generates implementation code.

Iterate: review, adjust, and continuously improve the UI.

Example: creating a Vue 3 + ElementUI Plus backend management project with ClaudeCode. claude --dangerously-skip-permissions Prompt used:

做个关于Vue3+ElementUI Plus的后台管理系统项目，
这个项目是智慧养老后台管理系统，
通过该平台可全面管理用户健康信息及健康数据，
提高运营及服务效率。
目前只有一个演示功能用户管理和首页和登录也，帮我创建个项目吧。

ClaudeCode returns a scaffold; screenshots of the generated login and admin pages are uploaded to the API易 service (https://imagen.apiyi.com/) for high‑resolution regeneration with GPT‑Image‑2.0.

Design‑spec extraction

The AI‑enhanced image is prompted to produce a diagram that lists only the design specifications (color palette, font sizes, spacing). The extracted spec is saved as DESIGN.md and later used to guide code generation.

Component‑library comparison

Element Plus – mature ecosystem, best for stable, legacy projects.

Naive UI – TypeScript‑first, excellent performance, flexible theming, ideal for SaaS dashboards.

Ant Design Vue – comprehensive enterprise design system, rich components for complex financial/ERP apps.

Shadcn‑Vue – “style‑less” approach, copy‑paste component code, suited for highly custom UI.

Arco Design Vue – ByteDance’s open‑source design system, modern look, strong component set, documentation primarily in Chinese.

For the demonstration project the author selects Element Plus, builds the initial scaffold, and runs the AI pipeline described above.

Full end‑to‑end example

After the scaffold is created, the author captures screenshots of the login and admin pages:

These images are sent to GPT‑Image‑2.0, which returns higher‑fidelity UI mockups:

Design‑spec extraction from the mockup sometimes produces hallucinations (missing small text). The author notes that alternative models such as Google Stitch can be used when GPT‑Image‑2.0 fails to capture details.

Prompt for Google Stitch:

请基于我提供的图片做个完全一致的UI界面，保持相同的配色规范、字体规范、间距规范等等

The resulting specification document (DESIGN.md) contains color palette, font sizes, spacing, and other style rules.

Code generation from spec

With the screenshot and DESIGN.md in hand, the author prompts the AI model to reconstruct the backend homepage:

请基于ui文件夹下的design.md设计规范、devui.md的文字性规范说明、homeui这个设计稿原型，将当前项目的后台首页界面给我完整还原出来和开发，确保质量高保真UI效果图

The AI produces production‑ready Vue code that matches the extracted design.

Iterative refinement

The workflow can be repeated: if certain UI elements lack inspiration, a new prompt can be sent to GPT‑Image‑2.0 to generate alternative NavBar styles or other components.

Example NavBar prompt:

请基于我当前提供的参考图片，我做的系统，我想设计8组不同风格和交互系统NavBar效果，给我设计一下吧，交互体验要好，符合C端场景

Resulting designs are reviewed and integrated back into the codebase.

Closed‑loop pipeline summary

Idea → Rough page → AI‑enhanced mockup → Design spec → Production‑ready code . The AI‑assisted loop eliminates repetitive alignment steps between designers, developers, and product managers, enabling rapid iteration and higher‑quality UI for traditionally “B‑end” admin systems.