Why AI Collaboration Requires One Shared Memory File

As organizations deploy multiple AI agents on the same codebase, fragmented memory and unsynchronized decision-making create silent conflicts and operational overhead. Without a single authoritative source of truth—including explicit ownership and activity tracking—users become the synchronization layer, repeating instructions and manually resolving collisions that a proper coordination system should prevent. This infrastructure gap turns apparent efficiency into hidden cost.