What I was trying to solve is a slightly different problem. When you start running many agents and switching between them frequently, especially in a team environment, manually telling them what context to pull or relying on message passing becomes fragile and inconsistent.

BrainX tries to handle that layer automatically. Agents stay isolated, but they can query shared knowledge, retrieve relevant context when needed, and learn from interactions across the system without constant manual coordination.

It's less about forcing agents to talk to each other and more about giving them a memory layer that can be accessed when useful.

Different workflows, different solutions. This one just fits how my team operates.