Sponsored by: Nimble Gravity | When Agents Should Ask for Help: Designing Human Escalation in Agent Bricks

Autonomous agents can handle a lot, until they can't. The real challenge isn't building an agent that runs, it's building one that knows when to stop and who to ask. In this session, we walk through a practical pattern for connecting AI agents to the humans they work alongside, without pulling those people out of their day. Using Agent Bricks, Databricks-native AI functions, and MLflow evaluation, we show how an agent can assess its outputs, escalate to colleagues when needed (via Teams or Slack), and continue autonomously once it has what it needs. Through a live demo, you'll see the full cycle: an agent processes and reasons over documents, evaluates its own work, routes targeted questions to people, handles partial and non-responses gracefully, and logs timing and feedback for future improvement. You'll leave with a reusable pattern for building agents that augment human decision-making and a clear picture of how Databricks makes the oversight layer part of the platform.