NeuroMAS introduces a novel approach to multi-agent systems by treating them as scalable neural networks, enhancing communication and coordination among agents through reinforcement learning. This method shows significant improvements over traditional multi-agent designs, suggesting a promising direction for scaling large language models (LLMs).