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Building Durable AI Agents

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Building Durable AI Agents

What does it take to move AI agents from demos to reliable production systems? In this episode, Hamza Tahir explores how MLOps principles are shaping the future of generative AI, covering workflows, agent harnesses, fleets, and the infrastructure needed to build durable, scalable systems.  The conversation dives into open source tools, production challenges, and how ZenML's new project, Kitaru, helps developers build resilient, replayable, and observable agent systems.

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00:00:00Welcome to Practical AI!
00:00:41Introducing the Guest
00:02:48The Evolution of MLOps and Agent Technology
00:04:35Understanding Workflows in AI and Agents
00:08:43Challenges of Durability in AI Agents
00:10:59The Future of Agents in Cloud Environments
00:13:00The Role of Harnesses in Agent Development
00:16:13The Tension Between Open and Proprietary Harnesses
00:20:45Sponsor: Framer
00:21:49Understanding Agent Architectures
00:25:15Building Durable Agent Systems
00:29:48Challenges in Agent Development
00:34:20The Future of Agent Infrastructure
00:39:03Optimizing Agent Performance
00:42:00Looking Ahead: Opportunities and Challenges
00:45:58Outro

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