InfoQ published a presentation on using multi-agent architecture for software development automation. The talk focuses on how engineering leaders can move past simple autocomplete and build more resilient AI workflows.
The practical challenge is control: autonomous agents can be powerful, but production teams need ways to coordinate tasks, constrain behavior, and validate outputs. Multi-agent systems are one approach to dividing responsibilities and reducing brittle single-agent flows.
The topic is increasingly relevant as companies test AI agents for code review, implementation, and release tasks that require more structure than chat-based assistance.