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Collabagents Àrd-ùrlar Co-obrachaidh Ioma-Àidseant by Jiahui Yu and Xudong Xing

Collabagents Àrd-ùrlar Co-obrachaidh Ioma-Àidseant by Jiahui Yu and Xudong Xing is a highly esteemed winner of the very prestigious 2026 Duais Umha A' Design Award in Dealbhadh Eadar-aghaidh, Eadar-obrachaidh agus Eòlas Cleachdaiche Competition Category.


UmhaEadar-aghaidh· 2026

Collabagents Àrd-ùrlar Co-obrachaidh Ioma-Àidseant

by Jiahui Yu and Xudong Xing

Client: CollabAgents

Duais Umha A' Design Award Winner in Eadar-aghaidh Category

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The Design

About Collabagents Àrd-ùrlar Co-obrachaidh Ioma-Àidseant

'S e àrd-ùrlar co-obrachaidh ioma-àidseant a th' ann an CollabAgents a chaidh a dhealbhadh airson sruthan-obrach iom-fhillte. Cruthaichidh luchd-cleachdaidh sruth-obrach agus sònraichidh iad dreuchdan dhan fheadhainn a tha an sàs ann. Nuair a tha dreuchd a dhìth, gabhaidh àidseant inntleachd fhuadain an dreuchd sin gus an lean am pròiseas air adhart. Tha an obair air a cur air dòigh mar nòdan ceangailte, agus nuair a thèid nòd a dheasachadh, thèid na ceumannan a leanas ùrachadh. Thathar a' cleachdadh conaltradh structarail stèidhichte air còd gus fiosrachadh a ghluasad le mionaideachd agus gus mì-shoilleireachd a lùghdachadh. Tha CollabAgents a' tionndadh sruthan-obrach sreathach gu siostaman sùbailte a fhreagras ri atharrachadh.

The Recognition

About the Duais Umha A' Design Award

Tha Collabagents Àrd-ùrlar Co-obrachaidh Ioma-Àidseant air Duais Umha A' Design Award a bhuannachadh, aithneachadh gu math urramach a bheirear do dhealbhaidhean sònraichte a tha air an comharrachadh le cruthachalachd, innleachd agus geurchuis. Tha buannaichean Umha nan obraichean gu math sgileil agus gu sònraichte cruthachail a dhearbhas eòlas farsaing, mac-meanmna agus tapachd an luchd-dealbhaidh. Thathar an dùil gum bi Collabagents Àrd-ùrlar Co-obrachaidh Ioma-Àidseant na nì air a bheil mòran meas, ion-mholta agus gràdhach, a tha gu sònraichte proifeiseanta agus ùr-ghnàthach. Tha an dealbhadh seo a bhuannaich Duais Umha A' Design Award a' cur nan cleachdaidhean as fheàrr ann an ealain, saidheans, dealbhadh agus teicneolas an gnìomh, agus tha e sàr-mhath airson an aire do mhion-fhiosrachadh. Bidh Collabagents Àrd-ùrlar Co-obrachaidh Ioma-Àidseant a' sàsachadh fheumalachdan gu h-iongantach, a' suathadh ri miannan, a' tàladh faireachdainnean agus a' togail fiosrachd.

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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