@mmoise Multi Agent Supervisor (MAS) is an orchestrator agent, so it depends on: 1) how many agents it orchestrates, 2) how complex those agents are, and 3) how complex the user prompt is.
I would encourage you to review the MLflow experiment traces for the MAS agent to identify bottlenecks and determine how you can optimize the connected agents or provide additional context for MAS to correctly orchestrate. I have seen the biggest improvement when I provide sufficient context for MAS to leverage individual agents.
Lastly, provide examples in the "Examples" and provide guidelines for MAS to execute. This should improve quality and speed. Reference: https://docs.databricks.com/aws/en/generative-ai/agent-bricks/multi-agent-supervisor#step-4-improve-...