『Agent Sense | Agentic Workflows & Operational AI』のカバーアート

Agent Sense | Agentic Workflows & Operational AI

Agent Sense | Agentic Workflows & Operational AI

著者： Monika Aggarwal Operational AI IBM and Frank Chavez Technical Architect IBM
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You are listening to Agent Sense. Where we keep AI simple, practical, and grounded. I am Monika Aggarwal. I specialize in Operational AI and in building agentic workflows grounded in decisions, 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.Monika Aggarwal, Operational AI, IBM and Frank Chavez, Technical Architect, IBM
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  • Agent Memory is More than RAG

    Agent Memory is More than RAG
    2026/08/23

    Season 2, Episode 1 - Agent Memory Is More Than RAG


    AI agents can access huge amounts of enterprise data, yet they often forget the context that matters.


    In this episode of Agent Sense, Monika Aggarwal and Frank Chavez talk with Ran Aroussi, founder and lead architect of MUXI, about what it takes to build useful agent memory.

    We discuss why storing data and using RAG does not create memory, what agents should remember, how memory can be distilled and updated over time, and why enterprise memory needs context, relationships, time, and source traceability.

    Ran also shares his perspective on building memory as an organizational capability, with access controls and governance built into the architecture.

    A practical conversation for architects, engineers, and AI leaders building agents for production.

    Guest: Ran AroussiFounder and Lead Architect, MUXICreator of yfinance

    Agent Sense is hosted by Monika Aggarwal and Frank Chavez.

    #AgentSense #AIAgents #AgentMemory #RAG #EnterpriseAI #MUXI
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    15 分
  • The Ambient Agent Pattern: AI That Works While You Sleep

    The Ambient Agent Pattern: AI That Works While You Sleep
    2026/08/12

    Most AI agents wait for a person to open a chat and give them a prompt. Ambient agents work differently. They listen for events across enterprise systems and start working when something changes.

    In this episode of Agent Sense, Monika Aggarwal and Frank Chavez discuss what makes an agent ambient and how the architecture changes when AI works continuously in the background.

    Using an SRE Ambient Agent as a mature example, they discuss how an agent can monitor operational signals, investigate incidents, invoke other agents and tools, involve a human when needed, and verify the outcome.

    The Ambient Agent design principle:

    Start with an event → Bound the action → Earn autonomy.
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    5 分
  • Episode 9: Beyond Meeting Summaries: From Conversation to Action

    Episode 9: Beyond Meeting Summaries: From Conversation to Action
    2026/08/02

    AI can summarize a meeting. Enterprise work starts after the summary.

    In this episode, Monika Aggarwal speaks with Artem Koren, co-founder and Chief Product Officer of Sembly AI, about how meeting context can move beyond notes and trigger real work.

    They discuss how AI can support follow-ups, workflow updates, CRM actions, and executive reporting across teams, countries, languages, and meeting platforms.

    Artem also explains why humans must steer agent execution and why enterprises should start with a controlled process, clear success measures, and a specific business outcome.

    Agent Sense keeps enterprise AI simple, practical, and grounded.

    Agent Sense reflects the personal perspectives and experiences of its hosts and guests. It is not an official IBM podcast.
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    11 分
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