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Collabagents Köp Agentli Hyzmatdaşlyk Platformasy by Jiahui Yu and Xudong Xing

Collabagents Köp Agentli Hyzmatdaşlyk Platformasy by Jiahui Yu and Xudong Xing is a highly esteemed winner of the very prestigious 2026 A' Design Award Bürünç Baýragy in Interfeýs, Özara Täsir we Ulanyjy Tejribesi Dizaýny Competition Category.


BürünçInterfeýs· 2026

Collabagents Köp Agentli Hyzmatdaşlyk Platformasy

by Jiahui Yu and Xudong Xing

Client: CollabAgents

A' Design Award Bürünç Baýragy Winner in Interfeýs Category

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Verified Award Winner

Verify Award Status for #183243

Colors

The Design

About Collabagents Köp Agentli Hyzmatdaşlyk Platformasy

CollabAgents çylşyrymly iş akymlary üçin döredilen köp agentli hyzmatdaşlyk platformasydyr. Ulanyjylar iş akymyny döredip, oňa gatnaşýan adamlara rollary belleýärler. Haçan-da bir rol boş galsa, emeli aň agenti şol roly öz üstüne alýar we şeýlelikde proses dowam edýär. Iş özara baglanyşykly düwünler görnüşinde guralýar we bir düwüni üýtgetmek ondan soňky ädimleri hem täzeleýär. Maglumatlary takyk geçirmek we düşnüksizligi azaltmak üçin gurluşly, kod esasly aragatnaşyk ulanylýar. CollabAgents göni çyzykly iş akymlaryny üýtgeşmelere jogap berýän uýgunlaşýan ulgamlara öwürýär.

The Recognition

About the A' Design Award Bürünç Baýragy

Collabagents Köp Agentli Hyzmatdaşlyk Platformasy A' Design Award Bürünç Baýragynyň ýeňijisidir; bu döredijilik, ussatlyk we ýiti akyl bilen tapawutlanýan tapawutly dizaýnlara berilýän aşa abraýly ykrarnamadyr. Bürünç ýeňijileri dizaýnerleriniň giň tejribesini, hyýalyny we tapawutlylygyny tassyklaýan örän ussat we geň galdyryjy derejede döredijilikli eserlerdir. Collabagents Köp Agentli Hyzmatdaşlyk Platformasy uly baha berilýän, haýran galynýan we söýülýän, üns çekiji derejede hünärmenlikli we täzelikçi zat bolmagy garaşylýar. A' Design Award Bürünç Baýragyny gazanan bu dizaýn sungatda, ylymda, dizaýnda we tehnologiýada iň oňat tejribeleri öz içine alýar we jikme-jiklige edýän üni bilen ajaýypdyr. Collabagents Köp Agentli Hyzmatdaşlyk Platformasy zerurlyklary ajaýyp derejede kanagatlandyrýar, isleglere degýär, duýgulary özüne çekýär we gyzyklanmany çekýär.

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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