🤖 AI Summary
This work addresses the challenges faced by resource-constrained software startup teams with limited user experience (UX) expertise in efficiently creating and evaluating low-fidelity prototypes. To this end, we propose SoftBoard, a web-based multi-agent system that integrates large language model–driven intelligent agents into the prototyping workflow for the first time, enabling an end-to-end pipeline from requirement elicitation to automated generation of low-fidelity prototypes. The system incorporates an embedded evaluation mechanism based on usability heuristic rules and unifies prototype editing, team collaboration, and AI-assisted functionalities within a single platform, substantially reducing reliance on specialized UX knowledge. Preliminary feasibility studies demonstrate that SoftBoard effectively standardizes and streamlines the minimum viable product (MVP) development process.
📝 Abstract
User Experience (UX) is recognized as a critical factor for the success of digital products, particularly in software startups, environments marked by time constraints, limited resources, and low maturity in design practices. Building Minimum Viable Products (MVPs) through low-fidelity prototyping represents a well-established strategy for rapid validation cycles at reduced cost. A systematic literature mapping, however, revealed gaps in the ecosystem of available tools: a predominance of general-purpose solutions adapted for prototyping, the absence of integrated methodological guidance, and the incipient use of Artificial Intelligence in the design process. This paper presents SoftBoard, a web-based tool for the creation and evaluation of low-fidelity prototypes in the context of MVP development. The tool integrates a prototype editor, team-based project organization, and a multi-agent system based on large language models that supports requirements elicitation and refinement, automates prototype generation, and evaluates interface quality based on usability heuristics. This integration aims to reduce reliance on prior UX expertise, standardize the prototyping process, and support teams in building MVPs aligned with user needs. As future work, a feasibility study with software professionals is currently underway.