Latent Briefing: Efficient Memory Sharing for Multi-Agent Systems via KV Cache Compaction (14 minute read)

Multi-agent systems are often highly token inefficient. A lot of redundant intermediate reasoning can emerge, especially as the task grows, and this causes token usage to compound rapidly. Latent Briefing is an approach to solving this problem that uses a model's attention patterns to identify which parts of context are important and discards the rest at the representation level. It shares relevant memory between agents, resulting in improved accuracy and token savings.