Agent Sense | Agentic Workflows & Operational AI

Monika Aggarwal, Operational AI, IBM and Frank Chavez, Technical Architect, IBM
  • 5.0(2개의 평가)
  • 과학 기술
  • 매주 업데이트

You are listening to Agent Sense. Where we keep AI simple, practical, and grounded.” I am Monika Aggarwal, AI Technical Practitioner. I specialize in Operational Al and building agentic workflows grounded in clear rules, good data, and governance. I am joined by my colleague Frank Chavez. He is a Technical Architect and hands-on builder specializing in multi-agent orchestration and AI integration patterns. I bring the enterprise and operational view. Frank brings the engineering view. We keep it simple and honest. Let’s start.” Disclaimer: The views shared on this podcast are our own and do not represent IBM's viewpoint.

에피소드

  1. Autonomous Databases, Where Autonomy Helps and Where It Hurts

    1일 전

    Autonomous Databases, Where Autonomy Helps and Where It Hurts

    Theme: Do autonomous databases fix bad data, or do they mainly improve operational reliability? Why are organizations moving toward autonomous operations? In episode 3, we talked about an IT service agent that created operational noise during an outage. The AI agent acted fast, but the ownership and escalation data were wrong, so the actions were wrong. If the data underneath these systems is fragile, should the data layer become autonomous too? In eposide 4 we are talking about autonomous databases, and what they can and cannot do in incidents like this. I am Monika Aggarwal, AI Technical Practitioner. I build agentic workflows grounded in clear rules, good data, and governance. I am joined by my colleague Frank Chavez. He is a Technical Architect and hands-on builder specializing in multi-agent orchestration and AI integration patterns. I bring the enterprise and operational view. Frank brings the engineering view.

    5분
  2. Why IT Service Agents Fail in Production, A Data Readiness Problem

    2월 9일

    Why IT Service Agents Fail in Production, A Data Readiness Problem

    Theme: Foundations & Data Readiness. Why do agents go rogue when the information source is weak? This is episode three: Why IT Service Agents Fail in Production, A Data Readiness Problem. Most enterprise agentic failures are not related to the model. They are data failures. We are using a real IT service ticketing example to show why data readiness matters for agents. I am Monika Aggarwal, AI Technical Practitioner. I build agentic workflows grounded in clear rules, good data, and governance. I am joined by my colleague Frank Chavez. He is a Technical Architect and hands-on builder specializing in multi-agent orchestration and AI integration patterns. I bring the enterprise and operational view. Frank brings the engineering view.

    3분
  3. Rules, Agents, Humans - A Practical Model for Agentic Workflows

    1월 10일

    Rules, Agents, Humans - A Practical Model for Agentic Workflows

    This episode explores the line between deterministic business logic and autonomous agents in real business operations, using a Commercial and Investment Banking onboarding scenario to show where rules work, where agents help, and where humans must stay in control. I am Monika Aggarwal, AI Technical Practitioner. I build agentic workflows grounded in clear rules, good data, and governance. I am joined by my colleague Frank Chavez. He is a Technical Architect and hands-on builder specializing in multi-agent orchestration and AI integration patterns. I bring the enterprise and operational view. Frank brings the engineering view.

    3분
  4. Brains and Guardrails: What Makes an AI Agent Enterprise-Ready?

    2025. 12. 16.

    Brains and Guardrails: What Makes an AI Agent Enterprise-Ready?

    Enterprises often stop at building a clever prototype. But when that agent touches real systems, the question changes from Can it run? to Can we trust it? That is the gap between experimentation and production.

    2분
  • 4개의 에피소드

평가 및 리뷰

5
최고 5점
2개의 평가

소개

You are listening to Agent Sense. Where we keep AI simple, practical, and grounded.” I am Monika Aggarwal, AI Technical Practitioner. I specialize in Operational Al and building agentic workflows grounded in clear rules, good data, and governance. I am joined by my colleague Frank Chavez. He is a Technical Architect and hands-on builder specializing in multi-agent orchestration and AI integration patterns. I bring the enterprise and operational view. Frank brings the engineering view. We keep it simple and honest. Let’s start.” Disclaimer: The views shared on this podcast are our own and do not represent IBM's viewpoint.

정보

  • 제작진
    Monika Aggarwal, Operational AI, IBM and Frank Chavez, Technical Architect, IBM
  • 방송 연도
    2025년 - 2026년
  • 에피소드
    4
  • 등급
    전체 연령 사용가
  • 저작권
    © Monika Aggarwal, Operational AI, IBM and Frank Chavez, Technical Architect, IBM
  • 웹사이트 보기
    Agent Sense | Agentic Workflows & Operational AI