Banger paper from Microsoft Research and colleagues.

It studies the potential benefits of agents that share progress while they work.

(bookmark it)

Communication is still a challenge with multi-agent systems.

In this setup, agents have no predefined roles and communicate via a shared directory.

They report that a team of k agents that write their findings to a shared directory matches the success rate of 4k agents working independently on ARC-AGI-3.

The gap grows with k, and teams reliably solve some tasks that no single agent solves.

The same setup beat best@k on polyomino packing and exceeded the prior best-known score. On MNIST compression, a four-agent team wrote a 1,957-byte classifier with 99.4% test accuracy, smaller than the best-known human solution.

Independent agents still do better when compute is tight or when there is no clear measure of progress, so the paper also tells you when it might be a good idea to skip communication.

Paper: https://arxiv.org/abs/2609.21032

Chat with Paper: https://academy.dair.ai/papers/scaling-discovery-through-test-time-communication-2609.21032