Collabagents Dandalin Haɗin Gwiwa na Wakilai Masu Yawa by Jiahui Yu and Xudong Xing

Collabagents Dandalin Haɗin Gwiwa na Wakilai Masu Yawa by Jiahui Yu and Xudong Xing is a highly esteemed winner of the very prestigious 2026 Kyautar A' Design Award ta Tagulla in Fuskar Amfani Competition Category.

TagullaFuskar Amfani· 2026

Collabagents Dandalin Haɗin Gwiwa na Wakilai Masu Yawa

by Jiahui Yu and Xudong Xing

Client: CollabAgents

Kyautar A' Design Award ta Tagulla Winner in Fuskar Amfani Category

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The Design

About Collabagents Dandalin Haɗin Gwiwa na Wakilai Masu Yawa

CollabAgents dandali ne na haɗin gwiwa na wakilai masu yawa wanda aka tsara don ayyukan aiki masu sarƙaƙiya. Masu amfani suna ƙirƙirar tsarin aiki kuma suna ba da matsayi ga mutanen da abin ya shafa. Idan wani matsayi ya ɓace, wakilin basirar wucin gadi (artificial intelligence) yana ɗaukar wannan matsayin domin aikin ya ci gaba. Ana tsara aiki a matsayin nodes masu haɗe da juna, kuma gyara node ɗaya yana sabunta matakan da ke biye. Ana amfani da sadarwa mai tsari bisa lambar shirye-shirye (code) don isar da bayanai daidai da rage rashin fahimta. CollabAgents yana mayar da tsarin aiki na layi zuwa tsare-tsare masu daidaitawa da ke amsa canji.

The Recognition

About the Kyautar A' Design Award ta Tagulla

Zanen Collabagents Dandalin Haɗin Gwiwa na Wakilai Masu Yawa ya lashe Kyautar A' Design Award ta Tagulla, wata karramawa mai tsananin daraja da ake bai wa zane-zane na musamman waɗanda ke da ƙirƙira, basira da hikima. Waɗanda suka lashe kyautar Tagulla kayayyakin fasaha ne masu ƙwarewa da ƙirƙira mai ban mamaki waɗanda ke tabbatar da babban gogewa, tunani da dabarun masu zanensu. Ana sa ran zanen Collabagents Dandalin Haɗin Gwiwa na Wakilai Masu Yawa ya zama abu da ake girmamawa sosai, ake sha'awa da ƙauna, mai ƙwarewa da ƙirƙire-ƙirƙire. Wannan zane da ya lashe Kyautar A' Design Award ta Tagulla yana haɗa mafi kyawun ayyuka a fasaha, kimiyya, zane da fasahar zamani, kuma yana da kyau saboda kulawarsa ga cikakkun bayanai. Zanen Collabagents Dandalin Haɗin Gwiwa na Wakilai Masu Yawa yana biyan buƙatu da kyau, yana taɓa sha'awa, yana jan hankalin zukata kuma yana jawo sha'awar sani.

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.