ABOUT THIS EPISODE
Building Predictable Conversational AI: Bridging Design, Engineering & Control at Scale
In this episode of the CDI Expert Series: Unprompted, we sit down with Yam Marcovitz, former software architect at Microsoft and Apex.AI, and co-founder of the open-source AI framework Parlant. With a background in real-time systems and enterprise software, Yam brings a systems-level perspective to one of AI's biggest challenges: getting LLMs to consistently do what you want.The conversation explores the gap between design and engineering in conversational AI, why current tools fall short, and how open source plays a crucial role in responsible AI development. Yam shares practical insights on building agent behavior that's not just intelligent but reliable and predictable at scale.
The episode also explores:
- How team collaboration and clear communication impact AI behavior as much as the technology itself
- The limitations of current conversation design toolsSeparating design and engineering workflows to improve efficiency and clarity
- Creating flexible agents without sacrificing controlMoving beyond "prompt and pray" to systematic testing and validation
- Managing updates/fixing issues without retraining models from scratchDesigning for multilingual, multichannel interactions
- How linguistic precision directly impacts agent performance
- Why open source and transparency are key to building responsible, scalable AI systems
Throughout the episode, Yam offers a practical, behind-the-scenes look at how robust AI systems are actually built; balancing flexibility with control, and creativity with structure. So, after reflecting on this episode: how can you build AI systems that are not just intelligent, but truly reliable, testable, and scalable?
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Yam Marcovitz,
https://il.linkedin.com/in/yam-marcovic
CEO, Parlant.io
TRANSCRIPT 🔗
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