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Building Durable AI Agents
DW

Daniel Whitenack and Chris Benson

· 47 Minutes

PodcastPractical AI

Building Durable AI Agents

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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

Original source

This story was published by Practical AI and written by Daniel Whitenack and Chris Benson. SyncAI.news shows a preview; the complete article is on the publisher's site.

Read the full story on share.transistor.fm

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