Collabagents Fjölþátta samstarfsvettvangur by Jiahui Yu and Xudong Xing is a highly esteemed winner of the very prestigious 2026 A' Design Award í bronsi in Viðmóts-, samskipta- og notendaupplifunarhönnun Competition Category.
BronsViðmót· 2026
Collabagents Fjölþátta samstarfsvettvangur
Client: CollabAgents
A' Design Award í bronsi Winner in Viðmót Category
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The Design
About Collabagents Fjölþátta samstarfsvettvangur
CollabAgents er fjölþátta samstarfsvettvangur hannaður fyrir flókin verkferli. Notendur búa til verkferli og úthluta hlutverkum til þeirra sem koma að vinnunni. Þegar hlutverk vantar tekur gervigreindarfulltrúi það hlutverk að sér svo ferlið haldi áfram. Vinnan er skipulögð sem tengdir hnútar, og breyting á einum hnút uppfærir skrefin sem á eftir koma. Skipulögð, kóðabundin samskipti eru notuð til að miðla upplýsingum af nákvæmni og draga úr tvíræðni. CollabAgents breytir línulegum verkferlum í aðlögunarhæf kerfi sem bregðast við breytingum.
The Recognition
About the A' Design Award í bronsi
Collabagents Fjölþátta samstarfsvettvangur vann A' Design Award í bronsi, mjög virta viðurkenningu sem veitt er framúrskarandi hönnunarverkum sem einkennast af sköpunargáfu, hugvitssemi og skarpskyggni. Sigurvegarar í bronsi eru ríkulega leiknir og áberandi skapandi gripir sem staðfesta víðtæka reynslu, ímyndunarafl og útsjónarsemi hönnuða sinna. Þess er vænst að Collabagents Fjölþátta samstarfsvettvangur sé mjög metinn, dáður og elskaður hlutur sem er einstaklega fagmannlegur og nýstárlegur. Þetta hönnunarverk sem vann A' Design Award í bronsi felur í sér bestu starfsvenjur í list, vísindum, hönnun og tækni og er framúrskarandi fyrir athygli sína á smáatriðum. Collabagents Fjölþátta samstarfsvettvangur fullnægir þörfum á dásamlegan hátt, snertir langanir, heillar tilfinningar og vekur forvitni.
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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