The Enterprise Arc of Agent Sense
Agent Sense started as a way to learn in public and share what we are seeing as enterprise AI moves beyond chat.
The major shift is from AI that answers questions to AI that can use tools, execute workflows, access enterprise systems, and support real business decisions.
The model is one part of the solution. Enterprises also need clear process design, trusted data, controlled access, integration patterns, observability, governance, and an operating model that keeps humans in the right parts of the loop.
Each episode follows that progression:
- Enterprise readiness: What breaks when agents leave demos
- Design boundaries: Where rules, agents, and human judgment belong
- Data readiness: Why bad data makes agents unsafe
- Data layer autonomy: Where autonomous action helps and where it creates risk
- Integration: How agents coordinate across enterprise systems
- Controlled access: Why agents need gateways before reaching core systems
- Agent execution: What changes when agents move from chat to computer use
- Ambient agents: How background agents monitor, decide, and escalate
- Governed reuse: Why enterprises need catalogs for agents, tools, and MCP servers
The goal is not to celebrate agents. The goal is to understand what it takes to make enterprise AI useful, controlled, and ready for real work.
Agent Sense Hosts
Co-Host & Creator
Monika is an enterprise AI technical practitioner with experience building and scaling large enterprise applications across healthcare, energy, and IBM software.
Her work sits at the intersection of architecture, data, workflow automation, governance, and adoption. She focuses on how enterprises move AI agents from demos into governed operating models where systems, people, data, and controls work together.
Agent Sense reflects that field perspective: practical lessons from enterprise AI conversations, client work, and hands-on agentic workflow design.
Co-Host & Practitioner
Frank is an AI technical architect with deep experience in automation, software testing, and enterprise AI implementation.
He has led generative AI and automation initiatives, designed testing frameworks, and built hands-on solutions across SaaS, RPA, and AI-driven applications.
He brings a builder and delivery lens to Agent Sense, with a focus on practical systems that can be tested, scaled, and adopted by the business.
Podcast Episodes
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.
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.
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.
Autonomous Databases, Where Autonomy Helps and Where It Hurts
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.
Integration Will Decide Enterprise AI with MCP and Agent-to-Agent
As AI systems evolve from single models into networks of autonomous agents, integration is the primary bottleneck. Integration needs standards. MCP standardizes how agents connect to systems. Agent to agent communication standardizes how they pass work. ๐ท MCP connects agents to enterprise systems. ๐ท A2A connects agents to each other so work can move across the enterprise.
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MCP Gateway: The Control Layer for Enterprise Agents
MCP helps agents connect to tools and systems. But connection alone is not enough. As agents start working across ServiceNow, Workday, SAP, HR, IT, finance, and customer operations, enterprises need a control layer. That is where the MCP Gateway comes in. We discuss how an MCP Gateway helps manage identity, policy, approvals, audit, and traceability. It gives agents access to approved tools without opening direct, unmanaged paths into core enterprise systems.
The Evolution of Agents From Chat to Computer Use
Guest: Vitalii Duk is the Founder and CEO of Dynamiq. He founded Dynamiq to make agentic AI practical and secure for organizations, simplifying the journey from prototype to production.
We discuss how agents are moving from answering questions to doing work across tools, systems, and runtime environments. ๐๐๐๐จ ๐๐จ ๐ฉ๐๐ ๐๐ฃ๐ฉ๐๐ง๐ฅ๐ง๐๐จ๐ ๐๐ง๐๐๐๐ฉ๐๐๐ฉ๐ช๐ง๐ ๐จ๐๐๐๐ฉ: ๐๐๐๐ฃ๐ฉ๐จ ๐๐ง๐ ๐ข๐ค๐ซ๐๐ฃ๐ ๐๐ง๐ค๐ข ๐ง๐๐จ๐ฅ๐ค๐ฃ๐จ๐ ๐ฉ๐ค ๐๐ญ๐๐๐ช๐ฉ๐๐ค๐ฃ. ๐๐๐ ๐ซ๐๐ก๐ช๐ ๐๐จ ๐ฃ๐ค๐ฉ ๐ค๐ฃ๐ก๐ฎ ๐๐ฃ ๐ฌ๐๐๐ฉ ๐ฉ๐๐ ๐๐๐๐ฃ๐ฉ ๐๐๐ฃ ๐๐ค. ๐๐ฉ ๐๐จ ๐๐ฃ ๐๐ค๐ฌ ๐จ๐๐๐๐ก๐ฎ, ๐ค๐๐จ๐๐ง๐ซ๐๐๐ก๐ฎ, ๐๐ฃ๐ ๐ง๐๐ฅ๐๐๐ฉ๐๐๐ก๐ฎ ๐๐ฉ ๐๐๐ฃ ๐ค๐ฅ๐๐ง๐๐ฉ๐ ๐๐ฃ ๐ง๐๐๐ก ๐๐ช๐จ๐๐ฃ๐๐จ๐จ ๐ฌ๐ค๐ง๐ .
Ambient Agents: Monitor, Decide, Escalate Coming Soon
Exploring ambient agents that continuously monitor business processes, make autonomous decisions within defined boundaries, and escalate to humans when needed. Understanding the balance between automation and human oversight in enterprise environments.
Interoperability and the Governed Catalog of AI Assets Coming Soon
Guest: Jyotsna K Narayanan, IBM Technical Product Management, Domain and Agent Catalog, IBM watsonx Orchestrate.
As companies move beyond AI pilots, many leaders run into a familiar problem: each team is building AI agents on their own. This leads to inconsistent customer experiences, more risk, and slower time to value. Departments often choose tools that solve their immediate needs but don't connect, creating a mix of agents that are hard to scale or manage.
This session will explain why interoperability matters and what it means to have a Governed catalog of AI Assets, that can improve consistency and reduce risk.
Guests
Practitioners and builders who have joined Agent Sense to share their field experience on enterprise AI.
Vitalii Duk ๐
Founder & CEO, Dynamiq
Vitalii founded Dynamiq to make agentic AI practical and secure for organizations, simplifying the journey from prototype to production. He brings a builder's perspective on what it takes to move agents from impressive demos into reliable, observable enterprise systems.
Episode 7 โ Chat to Computer UseJyotsna K Narayanan ๐
Technical Product Management, IBM watsonx Orchestrate
Jyotsna leads product management for Domain and Agent Catalog at IBM watsonx Orchestrate. She brings deep expertise in AI interoperability and governed reuse โ helping enterprises move beyond isolated AI pilots toward consistent, scalable agent operations.
Episode 9 โ Governed Catalog of AI Assets