درباره این پادکست 🔗
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.
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.
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every 24 days
میانگین طول صدا:
6 minutes
مصاحبه های مهمان
انگلیسی
ایالات متحده آمریکا
12 قسمت
از سال 16 دسامبر 2025
episodic
آخرین اپیزود 🔗
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,…
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اپیزود قبلی 🔗
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…
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…
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…
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…
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…
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…
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…
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…
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 …
سلب مسئولیت: پادکست و آثار هنری تعبیه شده در این صفحه متعلق به Monika Aggarwal, Operational AI, IBM and Frank Chavez, Technical Architect, IBM است که متعلق به صاحب آن است و به Listen Notes، Inc وابسته یا تایید نشده است.
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