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arXiv · 2508.02470

AIAP: A No-Code Workflow Builder for Non-Experts with Natural Language and Multi-Agent Collaboration

Hyunjn An·Yongwon Kim·Wonduk Seo·Joonil Park·Daye Kang·Changhoon Oh·Dokyun Kim·Seunghyun Lee
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Abstract

While many tools are available for designing AI, non-experts still face challenges in clearly expressing their intent and managing system complexity. We introduce AIAP, a no-code platform that integrates natural language input with visual workflows. AIAP leverages a coordinated multi-agent system to decompose ambiguous user instructions into modular, actionable steps, hidden from users behind a unified interface. A user study involving 32 participants showed that AIAP's AI-generated suggestions, modular workflows, and automatic identification of data, actions, and context significantly improved participants' ability to develop services intuitively. These findings highlight that natural language-based visual programming significantly reduces barriers and enhances user experience in AI service design.

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Hyunjn An, Yongwon Kim, Wonduk Seo, Joonil Park, Daye Kang, Changhoon Oh, Dokyun Kim, Seunghyun Lee. 2025-08-04. AIAP: A No-Code Workflow Builder for Non-Experts with Natural Language and Multi-Agent Collaboration. https://arxiv.org/abs/2508.02470

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