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This is the TL;DR of a post first published on Qodo's blog by Dr. Ofir Friedman and Amir Zaushnizer.
TL;DR
Agent-to-agent communication is becoming an important research area for AI companies. As agents grow more capable, their ability to communicate, plan, challenge one another, and work toward a shared objective may produce gains that cannot be achieved by improving each agent independently. Some of those gains are hard to predict, which is why we chose to study them experimentally on real engineering work.
At Qodo, we are actively developing agents for both customers and our own engineering organization. We therefore wanted to study agent collaboration through a real internal system: Dark Factory, an autonomous agent team that we run on our own engineering work today and are designing for engineering organizations more broadly.
Dark Factory goes beyond assigning separate tasks to separate agents. Its agents share context, develop and refine plans, exchange evidence, review one another’s work, and adapt their actions as the task evolves.
To do that, the agents need somewhere to meet. We built Dark Factory on BAND, a separate product that provides a shared interaction layer for agents. BAND supports several protocols, including A2A, and gives independently deployed agents persistent identities, chat rooms, and message routing, so agents running in different clusters and under different credentials can operate as one team.
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