In this episode of AI Explained, we are joined by Jeff Dalton, Head of AI and Chief Scientist at Valence.

Jeff has spent two decades at the intersection of research and industry, from building early conversational search benchmarks at Carnegie Mellon and Microsoft to leading the AI behind Nadia, Valence's purpose-built enterprise coaching assistant. He discusses the fundamentals of agentic system design that still hold from classical AI theory, why evaluation has to come before the prompt, how he approaches memory as a first-class object in coaching systems, and the defense-in-depth approach to guardrails that keeps complex agents safe across diverse enterprise deployments.

In this episode of AI Explained, we are joined by David Kenny, Executive Chairman of the Board of Nielsen and veteran AI leader.

He discusses how to prevent AI agents from going rogue, sharing insights from Nielsen's "Ask Nielsen" platform and emphasizing the importance of compound AI systems, real-time control planes, "generally accepted trust principles" (GATP) for AI, fit-for-purpose models, production cost management, and change management in moving from pilot to production.

In this episode of AI Explained, we are joined by Gary Stafford, Principal Solutions Architect at AWS Strands Agents.

He delves into how enterprises choose between AI/ML and agentic approaches, patterns for multi-agent systems, and the role of MCP. Gary also shares real-world use cases and practical guidance on safety, scaling, and delivering enterprise-ready agent systems.

In this episode of AI Explained, we are joined by Jayeeta Putatunda, Director of AI Center of Excellence at Fitch Group.

She discusses essential lessons learned from building and deploying AI agent systems, including challenges in moving from concept to production, key evaluation metrics, and the importance of observability and guardrails in ensuring reliable AI systems.

In this episode of AI Explained, we are joined by Nate B. Jones, AI strategist.

He explores high-level advice for organizations, technical ideas such as prompting and application architecture, and the current state of agent adoption. Key topics include challenges in building production-ready agents, architectural decisions, and ensuring ROI from these agents.

In this episode of AI Explained, we are joined by Karthik Bharathy, General Manager, AI Ops & Governance for Amazon SageMaker AI at AWS.

He discusses the critical aspects of AI security and observability for agentic workflows. He covers the evolution of AI Ops, end-to-end observability, human oversight, the current state of AI in enterprises, and the ways agentic AI systems are transforming business operations. He also dives into the challenges of implementing AI security, evaluating AI decisions, and ensuring transparency and compliance.

In this episode of AI Explained, Dr. Girish Nadkarni from Icahn School of Medicine at Mount Sinai.

He discusses the implementation and impact of AI, specifically generative AI, in healthcare. He covers topics such as clinical implementation, risk prediction, the interplay between predictive and generative AI, the importance of governance and ethical considerations in AI deployment, and the future of personalized medicine.

In this episode of AI Explained, we are joined by Navrina Singh, Founder and CEO at Credo AI.

We will discuss the comprehensive need for AI governance beyond regulated industries, the core principles of responsible AI, and the importance of AI governance in accelerating business innovation. The conversation also covers the challenges companies face when implementing responsible AI practices and dives into the latest regulations like the EU AI Act and state-specific laws in the U.S.