A LOW-CODE APPLICATION DEVELOPMENT PLATFORM INTEGRATING AI-ASSISTED DEVELOPMENT

Abstract

In the era of large language models, AI-assisted programming has substantially reduced the coding cost of application software, yet difficulties in communicating with clients and inefficiencies in deployment and maintenance persist. Rework and even project failure in real-world projects often stem from discrepancies between the client and the vendor in their understanding of the business, rather than from technology itself. To address this, this paper designs and implements a low-code application development platform that integrates AI-assisted development. Targeting three technical difficulties of current low-code platforms (front-end and back-end fields and rules are hard to configure dynamically, the security of online scripts is hard to constrain, and the reliability of AI-generated output is hard to guarantee), we propose three solutions: (1) a unified metadata model that automatically links front-end and back-end configurations; (2) a sandbox mechanism that restricts data sources, execution permissions and runtime; and (3) purpose-built Skills that constrain the steps and output format of AI generation. The platform is built on an improved RuoYi-Vue-Plus framework with an enhanced permission system, integrates the magic-api script engine, a visual design engine and sandbox technology, and builds its AI-assisted development capability on ByteDance's TRAE. Application in a manufacturing client's MES project shows that the development time of a conventional module fell from one week to 1–2 days, an efficiency gain of about 78%. The platform supports rapid on-site deployment and timely response to changing client requirements, effectively improving software delivery efficiency and success rate.