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

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arxiv 2508.02470 v1 pith:NBJH6B44 submitted 2025-08-04 cs.HC cs.AIcs.CLcs.MAcs.SE

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 This is my paper
classification cs.HC cs.AIcs.CLcs.MAcs.SE
keywords aiapnaturaluserlanguagemodularmulti-agentno-codenon-experts
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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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