Operationalizing AI Agents: From Experimentation to Production // Databricks Roundtable

About this episode

The episode discusses the challenges of deploying AI agents at scale and explores new approaches required for generative and agent-based systems.

Databricks Roundtable episode: Operationalizing AI Agents: From Experimentation to Production. Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter MLOps GPU Guide: https://go.mlops.community/gpuguide Big shout-out to Databricks for the collaboration! // Abstract This panel discusses the real-world challenges of deploying AI agents at scale. The conversation explores technical and operational barriers that slow production adoption, including reliability, cost, governance, and security. The panelists also examine how LLMOps, AIOps, and AgentOps differ from traditional MLOps, and why new approaches are required for generative and agent-based systems. Finally, experts define success criteria for GenAI frameworks, with a focus on robust evaluation, observability, and continuous monitoring across development and staging environments. // Bio Samraj Moorjani Samraj is a software engineer working on the Agent Quality team. Previously, Samraj worked at Meta on ads/product classification research and AppLovin on MLOps. Samraj graduated with a BS+MS in Computer Science from UIUC, advised by Professor Hari Sundaram, where he…

People in this episode

Host: Demetrios

Guest: Samraj Moorjani

Topics covered

• AI Agents
• MLOps
• LLMOps
• AIOps
• AgentOps
• Generative AI
• Deployment
• Production

Keywords

• Databricks
• collaboration
• production adoption
• reliability
• cost
• governance
• security
• evaluation
• observability
• continuous monitoring

Mentioned in this episode

Products: AIOps, AgentOps, AppLovin, Databricks

Books & works: Operationalizing AI Agents: From Experimentation to Production, Master's degree

Places: St. Louis

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