Agent Sense | Agentic Workflows & Operational AI
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Agent Sense | Agentic Workflows & Operational AI

À PROPOS DE CE PODCAST 🔗

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.
Technologie
Animateurs :
Fréquence de mise à jour:
every 25 days
Durée audio moyenne:
7 minutes
Entretiens avec des invités
Anglais
États-Unis
13 épisodes
depuis 16 décembre 2025
episodic
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DERNIER ÉPISODE 🔗

The Missing Path From AI Agents to ROI

The Missing Path From AI Agents to ROI

Your AI agent works, but can you prove its business value? As enterprises invest in Agentic AI, AI automation, and autonomous AIagents, many struggle to demonstrate measurable ROI. The challenges oftenbegin before development, with unclear business requirements and poorlyunderstood workflows. In th…
00:12:17
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ÉPISODES PRÉCÉDENTS

𝐀𝐠𝐞𝐧𝐭 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞: 𝐁𝐞𝐲𝐨𝐧𝐝 𝐀𝐜𝐜𝐮𝐫𝐚𝐜𝐲

𝐀𝐠𝐞𝐧𝐭 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞: 𝐁𝐞𝐲𝐨𝐧𝐝 𝐀𝐜𝐜𝐮𝐫𝐚𝐜𝐲

𝐀𝐠𝐞𝐧𝐭 𝐒𝐞𝐧𝐬𝐞 𝐢𝐬 𝐚 𝐬𝐡𝐨𝐫𝐭 𝐩𝐨𝐝𝐜𝐚𝐬𝐭 𝐨𝐧 𝐦𝐚𝐤𝐢𝐧𝐠 𝐀𝐈 𝐬𝐢𝐦𝐩𝐥𝐞, 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐚𝐥, 𝐚𝐧𝐝 𝐠𝐫𝐨𝐮𝐧𝐝𝐞𝐝 An AI agent can be 95% accurate and still fail thebusiness. It can give the right answer and still take too long, use the wrong tool, cost too much, or fail to complete the task. Frank Chávez and I talk with Jay Migliaccio,…
00:06:34
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Agent Memory is More than RAG

Agent Memory is More than RAG

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 take…
00:15:28
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The Ambient Agent Pattern: AI That Works While You Sleep

The Ambient Agent Pattern: AI That Works While You Sleep

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 an…
00:04:34
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Episode 9: Beyond Meeting Summaries: From Conversation to Action

Episode 9: Beyond Meeting Summaries: From Conversation to Action

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, workf…
00:10:56
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𝑮𝒐𝒗𝒆𝒓𝒏𝒆𝒅 𝑪𝒂𝒕𝒂𝒍𝒐𝒈 𝒐𝒇 𝑨𝒈𝒆𝒏𝒕𝒊𝒄 𝑨𝑰 𝑨𝒔𝒔𝒆𝒕𝒔

𝑮𝒐𝒗𝒆𝒓𝒏𝒆𝒅 𝑪𝒂𝒕𝒂𝒍𝒐𝒈 𝒐𝒇 𝑨𝒈𝒆𝒏𝒕𝒊𝒄 𝑨𝑰 𝑨𝒔𝒔𝒆𝒕𝒔

Agent Sense — Episode 8: Governed Catalog of AI Assets Enterprise AI agents does not fail from lack of ideas. They fail from agent sprawl: duplicate builds, unclear ownership, no way to know what is safe to reuse. Jyotsna Narayanan, Principal Product Manager for watsonx Orchestrate at IBM, joins ho…
00:08:56
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𝑻𝒉𝒆 𝑬𝒗𝒐𝒍𝒖𝒕𝒊𝒐𝒏 𝒐𝒇 𝑨𝒈𝒆𝒏𝒕𝒔 𝑭𝒓𝒐𝒎 𝑪𝒉𝒂𝒕 𝒕𝒐 𝑪𝒐𝒎𝒑𝒖𝒕𝒆𝒓 𝑼𝒔𝒆

𝑻𝒉𝒆 𝑬𝒗𝒐𝒍𝒖𝒕𝒊𝒐𝒏 𝒐𝒇 𝑨𝒈𝒆𝒏𝒕𝒔 𝑭𝒓𝒐𝒎 𝑪𝒉𝒂𝒕 𝒕𝒐 𝑪𝒐𝒎𝒑𝒖𝒕𝒆𝒓 𝑼𝒔𝒆

The episode is about hashtag#9minutes long. In this episode, my co host Frank Chávez and I are joined by Vitalii Duk from Dynamiq to discuss how agents are moving from answering questions to doing work across tools, systems, and runtime environments. “𝑪𝒉𝒂𝒕 𝒎𝒆𝒂𝒏𝒔 𝒂𝒏 𝒂𝒈𝒆𝒏𝒕 𝒄𝒂𝒏 𝒂𝒏𝒔𝒘𝒆𝒓 𝒚𝒐𝒖𝒓 𝒒𝒖𝒆𝒔𝒕𝒊𝒐𝒏. 𝑪…
00:09:44
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MCP Gateway: The Control Layer for Enterprise Agents

MCP Gateway: The Control Layer for Enterprise Agents

Episode 6 of Agent Sense continues from Episode 5, where we talked about MCP, A2A, and enterprise integration. In this episode, Monika Aggarwal and Frank Chávez discuss why enterprise agents need governed access to core systems before they can scale in production. MCP helps agents connect to tools…
00:04:11
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Integration Will Decide Enterprise AI with MCP and Agent-to-Agent

Integration Will Decide Enterprise AI with MCP and Agent-to-Agent

Theme: As AI systems evolve from single models into networks of autonomous agents, integration is the primary bottleneck. Core Integration Challenges: Fragmented Tool Access Context Loss Across Agents Tight Coupling & Low Reusability Lack of Standardized Communication Integration needs sta…
00:04:34
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Autonomous Databases, Where Autonomy Helps and Where It Hurts

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 a…
00:04:42
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Avertissement: Le podcast et les illustrations intégrés sur cette page proviennent de Monika Aggarwal, Operational AI, IBM and Frank Chavez, Technical Architect, IBM, qui est la propriété de son propriétaire et n'est ni affilié ni approuvé par Listen Notes, Inc.
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