Databricks

The Production AI Playbook: Deploying Agents at Enterprise Scale — Sandipan Bhaumik, Databricks

The Production AI Playbook: Deploying Agents at Enterprise Scale — Sandipan Bhaumik, Databricks

Sandipan Bhaumik presents a five-pillar framework for successfully moving AI systems from demos to production, inspired by a retail bank's failed chatbot PoC. The framework covers defining numerical success (Evaluation), tracing every AI decision (Observability), building robust data pipelines (Data Foundation), managing multiple AI interactions (Multi-agent Orchestration), and ensuring accountability and security (Governance). He illustrates these concepts with a banking chatbot case study, emphasizing continuous evaluation, data quality, and a proactive incident playbook.

From Chaos to Choreography: Multi-Agent Orchestration Patterns That Actually Work — Sandipan Bhaumik

From Chaos to Choreography: Multi-Agent Orchestration Patterns That Actually Work — Sandipan Bhaumik

Sandipan Bhaumik from Databricks explains that scaling from one to many AI agents is a distributed systems problem, not an AI one. He details common architectural anti-patterns like shared mutable state that cause race conditions and silent failures. The talk provides a practical framework based on distributed systems engineering, covering crucial patterns like choreography vs. orchestration, immutable state management with versioning, data contracts, and failure recovery using circuit breakers and compensation (Saga) patterns. Bhaumik illustrates how to build a robust, production-grade multi-agent architecture using tools like Databricks, LangGraph, and MLflow.

Ben Horowitz and Ali Ghodsi: How to Run a Billion-Dollar Business

Ben Horowitz and Ali Ghodsi: How to Run a Billion-Dollar Business

In a conversation with a16z, Databricks CEO Ali Ghodsi and co-founder Ben Horowitz share pivotal stories and lessons from building Databricks. They cover Ali's transition to CEO, the strategies behind scaling an intense yet sustainable culture, the art of high-stakes dealmaking with giants like Microsoft, and the mindset required to turn down lucrative acquisition offers to build a trillion-dollar company.

Advancing the Cost-Quality Frontier in Agentic AI // Krista Opsahl-Ong // Agents in Production 2025

Advancing the Cost-Quality Frontier in Agentic AI // Krista Opsahl-Ong // Agents in Production 2025

Krista Opsahl-Ong from Databricks introduces Agent Bricks, a platform designed to overcome the key challenges of productionizing enterprise AI agents. The talk covers common use cases, the difficult trade-offs between cost and quality, and how Agent Bricks uses automated evaluation and advanced optimization techniques to build cost-effective, high-performance agents.

MLflow 3.0: The Future of AI Agents

MLflow 3.0: The Future of AI Agents

Eric Peter from Databricks outlines the evolution from the traditional MLOps lifecycle to the more complex Agent Ops lifecycle. He details the five essential components of a successful agent development platform and introduces MLflow 3.0, a new release designed to provide a comprehensive, open-standard solution for building, evaluating, and deploying AI agents.