Collabagents 멀티 에이전트 협업 플랫폼 by Jiahui Yu and Xudong Xing

Collabagents 멀티 에이전트 협업 플랫폼 by Jiahui Yu and Xudong Xing is a highly esteemed winner of the very prestigious 2026 A' Design Award 동상 in 인터페이스, 인터랙션 및 사용자 경험 디자인 Competition Category.

동인터페이스· 2026

Collabagents 멀티 에이전트 협업 플랫폼

by Jiahui Yu and Xudong Xing

Client: CollabAgents

A' Design Award 동상 Winner in 인터페이스 Category

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View at A' Design Award Press Release Award Badge

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The Design

About Collabagents 멀티 에이전트 협업 플랫폼

CollabAgents는 복잡한 워크플로를 위해 설계된 멀티 에이전트 협업 플랫폼입니다. 사용자는 워크플로를 생성하고 참여자에게 역할을 배정합니다. 특정 역할이 비어 있을 경우 인공지능 에이전트가 그 역할을 대신 수행하여 프로세스가 중단 없이 이어집니다. 작업은 서로 연결된 노드 형태로 구성되며, 하나의 노드를 수정하면 이후 단계들이 자동으로 갱신됩니다. 정보는 구조화된 코드 기반 커뮤니케이션을 통해 정확하게 전달되어 모호함을 줄입니다. CollabAgents는 선형적인 워크플로를 변화에 반응하는 적응형 시스템으로 전환합니다.

The Recognition

About the A' Design Award 동상

Collabagents 멀티 에이전트 협업 플랫폼, 이 작품은 A' Design Award 동상 수상작으로, 창의성, 독창성, 영민함으로 돋보이는 뛰어난 디자인에 수여되는 높은 권위의 인정입니다. 동상 수상작은 충분히 숙련되고 인상적으로 창의적인 작품으로, 디자이너의 폭넓은 경험, 상상력, 기지를 입증합니다. Collabagents 멀티 에이전트 협업 플랫폼, 이 작품은 높이 평가받고 감탄과 사랑을 받는 사물로서 두드러지게 전문적이고 혁신적일 것으로 기대됩니다. 이 동상 수상 디자인은 예술, 과학, 디자인, 기술의 모범 사례를 담고 있으며 세부에 대한 주의로 훌륭합니다. Collabagents 멀티 에이전트 협업 플랫폼, 이 작품은 필요를 훌륭하게 충족하고 욕망에 닿으며 감정을 매료하고 호기심을 불러일으킵니다.

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.