Collabagents 多智能体协作平台 by Jiahui Yu and Xudong Xing

Collabagents 多智能体协作平台 by Jiahui Yu and Xudong Xing is a highly esteemed winner of the very prestigious 2026 A' Design Award 铜奖 in 界面、交互与用户体验设计 Competition Category.

铜界面· 2026

Collabagents 多智能体协作平台

by Jiahui Yu and Xudong Xing

Client: CollabAgents

A' Design Award 铜奖 Winner in 界面 Category

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Verified Award Winner

Verify Award Status for #183243

View at A' Design Award Press Release Award Badge

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The Design

About Collabagents 多智能体协作平台

CollabAgents 是一个专为复杂工作流打造的多智能体协作平台。用户创建工作流,并为参与其中的人员分配角色。当某一角色出现空缺时,人工智能智能体将承担该角色,使流程得以持续推进。工作以相互关联的节点形式组织,编辑其中一个节点即可自动更新后续步骤。平台采用结构化的代码式通信方式,精准传递信息并减少歧义。CollabAgents 将线性工作流转变为能够响应变化的自适应系统。

The Recognition

About the A' Design Award 铜奖

Collabagents 多智能体协作平台是 A' Design Award 铜奖得主，这是授予以创造力、独创性和敏锐见长的杰出设计的极具声望的认可。铜奖得主是技艺娴熟、创意惊人的作品，印证了其设计师丰富的经验、想象力与机智。预计Collabagents 多智能体协作平台将成为一件备受推崇、令人钦佩且被珍爱的物品，兼具显著的专业性与创新性。这件赢得 A' Design Award 铜奖的设计融入艺术、科学、设计和技术领域的最佳实践，并因注重细节而出类拔萃。Collabagents 多智能体协作平台出色地满足需求，触动渴望，迷住情感，并吸引好奇心。

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.