Collabagents マルチエージェント・コラボレーションプラットフォーム by Jiahui Yu and Xudong Xing

Collabagents マルチエージェント・コラボレーションプラットフォーム by Jiahui Yu and Xudong Xing is a highly esteemed winner of the very prestigious 2026 A' Design Award 銅賞 in インターフェース・インタラクション・UXデザイン Competition Category.

銅インターフェース· 2026

Collabagents マルチエージェント・コラボレーションプラットフォーム

by Jiahui Yu and Xudong Xing

Client: CollabAgents

A' Design Award 銅賞 Winner in インターフェース Category

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View at A' Design Award Press Release Award Badge

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The Design

About Collabagents マルチエージェント・コラボレーションプラットフォーム

CollabAgentsは、複雑なワークフローのために設計されたマルチエージェント・コラボレーションプラットフォームです。ユーザーはワークフローを作成し、関係者に役割を割り当てます。担当者が不在の役割がある場合は、人工知能エージェントがその役割を担い、プロセスが滞りなく進行します。作業は相互に接続されたノードとして構成され、一つのノードを編集すると後続のステップが自動的に更新されます。構造化されたコードベースのコミュニケーションにより、情報を正確に伝達し、曖昧さを低減します。CollabAgentsは、直線的なワークフローを、変化に応答する適応型システムへと変えます。

The Recognition

About the A' Design Award 銅賞

Collabagents マルチエージェント・コラボレーションプラットフォームは、創造性、独創性、鋭い洞察力で際立つ傑出したデザインに授与される、高い権威をもつ評価である A' Design Award 銅賞の受賞作品です。銅賞の受賞作品は、十分に巧みで印象的なほど創造的な工芸品であり、デザイナーの豊富な経験、想像力、機知を裏づけています。Collabagents マルチエージェント・コラボレーションプラットフォームは、高く評価され、称賛され、愛される品であり、顕著にプロフェッショナルで革新的であることが期待されます。この A' Design Award 銅賞を受賞したデザインは、芸術・科学・デザイン・技術のベストプラクティスを取り入れており、細部への配慮に優れています。Collabagents マルチエージェント・コラボレーションプラットフォームは、ニーズを見事に満たし、欲求に触れ、感情を魅了し、好奇心を引きつけます。

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.