AI Explained

Fiddler AI
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AI Explained is a series hosted by Fiddler AI featuring industry experts on the most pressing issues facing AI and machine learning teams. Learn more about Fiddler AI: www.fiddler.ai

  1. 5月20日

    AI Agents Have an Identity Complex With Jeff Malnick

    In this episode of AI Explained, we are joined by Jeff Malnick, VP of Engineering for Developer and AI Products at 1Password. Jeff brings deep expertise in distributed systems, secrets management, and security infrastructure from his work at 1Password and previously HashiCorp, with a focus on making the secure path the default for developers and now AI agents.  He explains why agent identity has suddenly become urgent: AI agents are machine workloads with reasoning capabilities, which breaks the assumption behind traditional OAuth flows where permissions only need to be granted once. He walks through 1Password's framework of three agent identity models (delegated, bounded, and fully autonomous), why the laptop is the hardest environment to secure now that file system access effectively hands an unlocked machine to a reasoning stranger, and why bearer tokens and passwords are the wrong primitive for agents. He also shares how policy decision and enforcement points need to evolve to pull human intent through to just-in-time authorization, why credentials should never enter LLM context, and where federated versus distributed identity is heading over the next three to five years.

  2. 4月23日

    Lessons from a Physician-CIO on AI Governance with Dr. Stacey Johnston

    In this episode of AI Explained, we are joined by Stacey Johnston, MD, Chief Information and Digital Execution Officer at Beacon Health System. Dr. Johnston brings a rare dual perspective to healthcare AI. She trained as a physician and hospitalist before moving into health informatics, giving her firsthand insight into where technology helps clinicians and where it gets in the way. She discusses how Beacon built its AI governance council from scratch, the policies and vendor risk assessments that gate every new tool, and why requiring a defined ROI before approval has become a forcing function for disciplined adoption. She also shares how agentic AI is already delivering results in scheduling, autonomous benefits verification, and colon cancer screening, why ambient listening drove $10,000 in additional per-physician revenue over 12 months, how clinician trust is earned incrementally through seamless workflow fit and real time savings, and what a federated but centrally monitored AI model could look like as health systems scale.

  3. 4月10日

    The Agentic Gap: What Enterprises Think vs. What Actually Works With Jeff Dalton

    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.

  4. 2月6日

    How to Prevent AI Agents from Going Rogue With David Kenny

    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.

  5. 2025/09/25

    Building Agents at Scale: Lessons from the Front Lines With Gary Stafford

    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.

  6. 2025/08/16

    Lessons Learned from Building Agentic Systems With Jayeeta Putatunda

    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.

  7. 2025/07/24

    Agent Wars: The Hype, Hope, and Hidden Risks with Nate B. Jones

    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.

  8. 2025/03/20

    AI Observability and Security for Agentic Workflows with Karthik Bharathy

    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.

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簡介

AI Explained is a series hosted by Fiddler AI featuring industry experts on the most pressing issues facing AI and machine learning teams. Learn more about Fiddler AI: www.fiddler.ai

資訊

  • 創作者
    Fiddler AI
  • 活躍年代
    2023年 - 2026年
  • 集數
    21
  • 年齡分級
    兒少適宜
  • 版權
    © Copyright 2024 All rights reserved.
  • 節目網站
    AI Explained

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