Building Durable AI Agents

2026-07-09 · 47 min · episode 363 · 6 entities

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→ hosted by Daniel Whitenack and Chris Benson person

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→ discusses Technology company

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→ hosted by Practical AI LLC company

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Entities found in this episode

companys 4

mentioned Practical AI LLC company

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evidence rules-v5
Feed author/publisher: Practical AI LLC
mentioned Technology company

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discusses Technology company

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evidence rules-v5
Feed category: Technology
hosted by Practical AI LLC company

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evidence rules-v5
Feed author/publisher: Practical AI LLC

persons 2

mentioned Daniel Whitenack and Chris Benson person

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evidence rules-v5
Feed author/publisher: Daniel Whitenack and Chris Benson
hosted by Daniel Whitenack and Chris Benson person

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evidence rules-v5
Feed author/publisher: Daniel Whitenack and Chris Benson

Episode description as stored

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. Featuring: Hamza Tahir – LinkedIn Daniel Whitenack – Website , GitHub , X Links: ZenML Kitaru Machine Learning Tools Landscape v2 (+84 new tools) Sponsors: Framer: The enterprise-grade website builder that lets your team ship faster. Get 30% off at framer.com/practicalai Upcoming Events: Register for upcoming webinars here ! Midwest AI Summit 2026