Agent Sense | Agentic Workflows & Operational AI
Agent Sense is a podcast about keeping AI practical and grounded, focused on operational AI and agentic workflows. It is hosted by Monika Aggarwal, who specializes in operational AI and building agentic workflows anchored in decisions, data, and governance. She is joined by her colleague Frank Chavez, a technical architect focused on multi-agent orchestration and AI integration patterns. Together they pair an enterprise and operational perspective with a hands-on engineering view, aiming to keep the discussion simple and honest. The hosts note that the views expressed are their own and do not represent IBM's viewpoint.
Episodes
๐๐ ๐๐ง๐ญ ๐๐๐ซ๐๐จ๐ซ๐ฆ๐๐ง๐๐: ๐๐๐ฒ๐จ๐ง๐ ๐๐๐๐ฎ๐ซ๐๐๐ฒ
๐๐ ๐๐ง๐ญ ๐๐๐ง๐ฌ๐ ๐ข๐ฌ ๐ ๐ฌ๐ก๐จ๐ซ๐ญ ๐ฉ๐จ๐๐๐๐ฌ๐ญ ๐จ๐ง ๐ฆ๐๐ค๐ข๐ง๐ ๐๐ ๐ฌ๐ข๐ฆ๐ฉ๐ฅ๐, ๐ฉ๐ซ๐๐๐ญ๐ข๐๐๐ฅ, ๐๐ง๐ ๐ ๐ซ๐จ๐ฎ๐ง๐๐๐An 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 Chรกvez and I talk with Jay Migliaccio, TechnicalProduct Manager for IBM watsonx Orchestrate, about how enterprises shouldmeasure and improve
Agent Memory is More than RAG
Season 2, Episode 1 - Agent Memory Is More Than RAGAI 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 agen
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 and how the architecture changes when AI works continuously in the background.Using an SRE Ambient Agent
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, workflow updates, CRM actions, and executive reporting across teams, countries, languages, and meeting platf
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Agent Sense โ Episode 8: Governed Catalog of AI AssetsEnterprise 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 host Monika Aggarwal to break down what a governed catalog of AI agents, tools, and MCP servers needs to
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The episode is about hashtag#9minutes long. In this episode, my co host Frank Chรกvez 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.โ๐ช๐๐๐ ๐๐๐๐๐ ๐๐ ๐๐๐๐๐ ๐๐๐ ๐๐๐๐๐๐ ๐๐๐๐ ๐๐๐๐๐๐๐๐. ๐ช๐๐๐๐๐๐๐ ๐๐๐ ๐๐๐๐๐ ๐๐๐ ๐๐๐๐๐ ๐๐๐ ๐๐๐๐ ๐๐๐๐๐๐ ๐๐๐๐๐๐ ๐๐๐๐๐๐๐๐๐๐๐๐, ๐๐๐๐๐, ๐๐๐
๐๐๐๐๐๐๐๐๐. ๐ป๐๐๐ ๐๐ ๐๐๐๐๐ ๐
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 Chรกvez discuss why enterprise agents need governed access to core systems before they can scale in production.MCP helps agents connect to tools and systems. But connection alone is not enough. As agents start working across ServiceNow, Workday, SA
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 AccessContext Loss Across AgentsTight Coupling & Low ReusabilityLack of Standardized CommunicationIntegration needs standards.MCP standardizes how agents connect to systems.Agent to agent communication standardizes how they pass wo
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 fragil
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 Te
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 join
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.
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