让多个编码智能体在共享空间中实时协作，提升任务完成率和稳定性。
AgentRoom: Concurrent Multi-Agent Coding in a CRDT-Backed Shared Workspace
- 基于CRDT的共享文件系统，支持多智能体并发编辑与状态同步。
- 双智能体协作比单智能体少丢弃30%以上困难任务，运行结果更稳定。
- 适合需要高可靠性与并行开发的多模块编程场景，如开源项目协同。
并发多智能体编码可实现模块分工、冗余增强和自然粒度下的并行探索。实时协作编辑协议通过无冲突复制数据类型（CRDT）解决人类团队的协调问题，但底层大模型一次仅生成一个词元，现有系统继承了这一串行限制：要么通过阶段交接顺序执行，要么独立采样却不协调。这导致单个智能体最多放弃一半复杂任务。AgentRoom是一种面向并发编码智能体的实时协作编辑协议，其运行时层将文件级申请、状态和广播作为MCP工具暴露于经CRDT合并的共享文件系统上。五个前沿的命令行编码模型在四个后端编码任务上测试，包含Python DevBench和Rust+axum跨语言验证。对于命令行稳定的模型，使用两个智能体的AgentRoom比单智能体方案放弃更少任务，且运行间波动更小。在相同算力下，一项正向平均大模型判别对比显示，AgentRoom优于并行合并；另一项捆绑探测对比则表明，完整版AgentRoom优于所有局部变体——是顺序而非比例分配的收益。真正承担负载的是协调机制，而非并行或CRDT合并。
原文摘要 · Abstract (English)
Concurrent multi-agent coding promises division of labor across modules, robustness through redundancy, and parallel exploration at the natural granularity of multi-file projects. Realtime collaborative editing protocols solve this coordination problem for human teams via Conflict-free Replicated Data Types (CRDTs), but the LLMs underneath generate one token at a time and existing multi-agent coding systems inherit this serial limit: they either sequence agents through phase handoffs or pool independent samples without coordination, and a single agent abandons up to half of hard tasks with a one-file stub-and-exit. AgentRoom is a realtime collaborative editing protocol for concurrent coding agents. Its runtime layer exposes file-level claim, status, and broadcast as MCP tools on a CRDT-merged shared filesystem. Five frontier coding-CLI models ran four backend coding tasks, with cross-language checks in Python DevBench and Rust+axum. For CLI-stable models, AgentRoom with 2 agents abandons fewer tasks than Solo and has less run-to-run variation. At matched-compute, one positive mean LLM-judge contrast puts AgentRoom over parallel-merge. The other contrast, a bundle probe, puts full AgentRoom above each partial case: an ordering rather than a percentage split. Coordination, not parallelism or CRDT-merge, bears the load.
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