If you are building enterprise Generative AI, you know the pain of the "Monolithic Agent Bottleneck": passing dozens of tools to a single AI supervisor leads to hallucinated routing, massive context bloat, and security nightmares.
With the recent May update to Databricks Agent Bricks, there is a better way. You can now nest Supervisor Agents as subagent tools. Instead of one massive chatbot, you can build a scalable "Manager of Managers" architecture. An overarching Enterprise Triage Supervisor routes requests strictly to domain experts, like an IT Helpdesk Supervisor or an HR Assistant Supervisor.
I just published a new article on Medium breaking down exactly how to build this architecture today. I cover:
✅ The day-to-day enterprise use cases for nested agents.
✅ The Python code to link parent and child agents.
✅ Pro Tip: How to bypass the current Python SDK lag using direct REST API calls so you don't have to wait for the next patch.
Check out the full guide on Medium here, and feel free to clone the open-source repo to test it in your own workspace! 👇
click here
Are you building multi-agent systems on Databricks yet? Let me know your biggest orchestration challenges in the comments!
#Databricks #GenerativeAI #AgenticAI #DataEngineering #MachineLearning #DatabricksMVP #MultiAgentSystems
