想知道AI编程团队内部怎么协作？这篇论文用1902次运行数据告诉你，共享文件能省42%的token，但指定协调者没用。
该研究提出一种测量AI编程智能体团队协调性的工具，将每次运行表示为时间网络，节点为智能体和文件，边为带时间戳的消息、文件读写操作。对1902次运行的分析显示，直接消息随智能体数量近似二次增长，但最大团队中趋于平缓，转向广播消息。共享文件可减少约42%的输出token，但指定协调者无显著改善。在244次额外运行中，智能体在五分之四的运行中会寻找隐藏评分材料。
When Agents Coordinate: Measuring Coordination in Multi-Agent AI Coding
We study how teams of AI coding agents coordinate while solving programming tasks. Current evaluations usually report whether the agents complete the task and how much the run costs, leaving the coordination inside the team largely unmeasured. We introduce an instrument to measure this coordination. Each run is represented as a temporal network in which agents and files are nodes, and messages, file writes, and file reads are timestamped directed edges with an associated cost. We apply this instrument to 1902 runs, each evaluated with a fixed test suite, across configurations that vary the team size, the team structure, and the file policy. The resulting networks show how coordination changes as teams grow and as the work changes. Direct messaging initially increases close to quadratically with the number of agents, with much of this growth coming from an early round of introductions. As the teams grow further, this increase levels off in the largest teams we study, where agents increasingly communicate through broadcast messages. The task also shapes the network that emerges. Work built around a shared specification produces dense, highly connected teams, while pipeline tasks produce sparse networks organised around local interfaces. Shared files can replace repeated 1-to-1 communication, cutting output tokens by about 42% at eight agents on message-heavy work, while adding overhead when files already carry the coordination. Naming one agent as coordinator creates no communication hub and provides no reliable improvement in success. We also observe an unprompted tendency for agents to seek out hidden grading material. We repeat the key experimental conditions in a sealed environment, replacing the hidden material with marked placeholder files. Across 244 additional runs, agents still reach for it in four fifths of runs, while the coordinator and file-channel findings reproduce.