Atlanta showed up for AI.
Databricks AI Day drew > 150 practitioners, a sold-out agent training session, and a keynote anchored in one theme: AI in production is hard.
Shoutout to David Meyer for an outstanding keynote — great clarity on the Databricks strategy. The agent training session was sold out, the energy in the room was electric, and the momentum around agentic AI is very real. Atlanta felt like a city ready to build.
Databricks framed the production agent challenge around three questions:
• How do I manage agent quality?
• What's the right AI technique to use?
• How do I balance cost vs. quality?
Those are exactly the right questions. And Databricks is building serious answers — Agent Bricks, Lakebase, Unity Catalog extended to govern AI artifacts and agent code. The platform story is compelling.
Here's the reality most enterprises are actually living in right now:
🔴 Data siloed across SaaS, AWS, Azure, GCP, Snowflake, on-prem systems, and cloud object stores
🔴 Security policies fragmented across every one of those systems
🔴 Multiple vectors where data can be exfiltrated
🔴 Fragmented AI and data estates with no unified view
🔴 IT governance that hasn't caught up with any of it
Enterprises aren't waiting for a 5-year data cleanup before rolling out AI. Agents are being unleashed right now — into this complexity, into these silos, into this chaos.
AI projects shouldn't slow down because the enterprise is messy. As a Built on Databricks partner, LangGuard removes the friction of siloed data, fragmented security, and scattered governance — so enterprises can accelerate AI into production on Databricks and realize ROI faster.
The agents are already running. Governance can't wait.
#AIDays #Databricks #BuiltOnDatabricks #AgenticAI #AIGovernance #LangGuard #EnterpriseAI
That’s great news! 🎉