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Collabagents Plateforme de collaboration multi-agents by Jiahui Yu and Xudong Xing

Collabagents Plateforme de collaboration multi-agents by Jiahui Yu and Xudong Xing is a highly esteemed winner of the very prestigious 2026 A' Design Award de Bronze in Design d'Interface Competition Category.


BronzeInterface· 2026

Collabagents Plateforme de collaboration multi-agents

by Jiahui Yu and Xudong Xing

Client: CollabAgents

A' Design Award de Bronze Winner in Interface Category

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Verified Award Winner

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The Design

About Collabagents Plateforme de collaboration multi-agents

CollabAgents est une plateforme de collaboration multi-agents conçue pour les flux de travail complexes. Les utilisateurs créent un flux de travail et attribuent des rôles aux personnes impliquées. Lorsqu'un rôle n'est pas pourvu, un agent d'intelligence artificielle l'endosse afin que le processus se poursuive. Le travail est organisé sous forme de nœuds reliés entre eux, et la modification d'un nœud met à jour les étapes suivantes. Une communication structurée, fondée sur le code, permet de transmettre l'information avec précision et de réduire toute ambiguïté. CollabAgents transforme les flux de travail linéaires en systèmes adaptatifs capables de réagir au changement.

The Recognition

About the A' Design Award de Bronze

Collabagents Plateforme de collaboration multi-agents est lauréat de l'A' Design Award de Bronze, une reconnaissance hautement prestigieuse décernée à des designs remarquables qui se distinguent par leur créativité, leur ingéniosité et leur sagacité. Les lauréats Bronze sont des artefacts amplement habiles et d'une créativité frappante, qui authentifient la vaste expérience, l'imagination et l'ingéniosité de leurs concepteurs. Collabagents Plateforme de collaboration multi-agents est censé être un objet très estimé, admiré et chéri, remarquablement professionnel et innovant. Ce design lauréat de l'A' Design Award de Bronze intègre les meilleures pratiques de l'art, de la science, du design et de la technologie, et est excellent par son souci du détail. Collabagents Plateforme de collaboration multi-agents satisfait admirablement les besoins, touche les désirs, charme les sentiments et attire la curiosité.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties
CollabAgents is a multi-agent collaboration system that simulates missing roles with AI agents to ensure continuous workflows. Node-level editing enables targeted updates, reducing rework by over 85%, while code-based communication improves precision and speed. It transforms linear workflows into adaptive, resilient systems.
Dimensions & Packaging
The system features a node-based workflow structure, role simulation modules, and dynamic process propagation. It supports real-time updates, modular task execution, and scalable multi-agent coordination. Key capabilities include node-level editing, automatic downstream updates, and role auto-completion to maintain continuous workflow execution.
Tags
multi-agent, collaboration, workflow, AI system, interaction design, role simulation, automation, UX, decision system
Production Technology
CollabAgents is built using AI-driven multi-agent architecture, workflow modeling, and structured data exchange. The system leverages role-based agent simulation, node-level state management, and real-time synchronization to enable adaptive collaboration. Code-based communication ensures precise information transfer and reduces ambiguity across processes.
Design Challenge
The main challenge was designing a system that balances automation with user control in complex workflows.

Traditional collaboration relies heavily on human coordination, making it difficult to handle missing roles, dynamic changes, and process interruptions. The challenge was to create a system that allows targeted intervention without breaking the overall workflow.

This was addressed through node-level editing and role simulation, enabling flexible adjustments while maintaining system stability and continuity.
Research
The project is based on research into cross-functional collaboration challenges, including workflow inefficiencies, role dependency, and communication breakdowns.

Methods included workflow analysis, scenario mapping, and observation of real-world team processes. The research identified key issues such as delays caused by missing roles and the need for more adaptive systems.

The design explores how multi-agent systems can simulate roles, improve coordination, and reduce rework, resulting in more efficient and resilient collaboration.
Inspiration
CollabAgents is inspired by the complexity of cross-functional collaboration, where delays often result from missing roles and fragmented communication. It explores how AI agents can simulate expertise and fill capability gaps in real time, transforming collaboration into a more adaptive and efficient process.
Project Duration
The project was developed between 2025 and 2026 in the United States as an independent concept design focused on future collaboration systems.
Operation Flow
Users start by selecting or creating a workflow and assigning roles. If roles are missing, AI agents automatically step in to continue the process.

Users can interact with specific steps, make changes, and instantly see updates applied to the rest of the workflow. Instead of restarting the entire process, only affected parts are adjusted.

This enables smoother collaboration, faster decision-making, and reduces delays caused by miscommunication or missing inputs.
Patents
No patents or trademarks are registered for this project.
Team Members
Jiahui Yu
Xudong Xing
Image Credits
Image #1: Creators Jiahui Yu and Xudong Xing, CollabAgents, 2025.
Image #2: Creators Jiahui Yu and Xudong Xing, CollabAgents, 2025.
Image #3: Creators Jiahui Yu and Xudong Xing, CollabAgents, 2025.
Image #4: Creators Jiahui Yu and Xudong Xing, CollabAgents, 2025.
Image #5: Creators Jiahui Yu and Xudong Xing, CollabAgents, 2025.

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