Presentation
AI-Native DevOps for the Mainframe
Contributors
Event Type
Technical Session
DevOps
Enterprise Architecture
Languages, API's and Framework
Machine Learning/AI
All Audiences
TimeWednesday, August 199:15am - 10:15am EDT
LocationRoom 320
DescriptionThe enterprise DevOps conversation has moved past automation. The next frontier is AI-native: intelligence embedded into development, operations, and decision-making rather than layered on top as an assistant. For mainframe teams, this shift is both an opportunity and an architectural challenge.
This session addresses both. We examine the practical patterns for integrating AI agents into existing toolchains — the difference between Agentic Workflows (structured, auditable, human-in-the-loop) and fully autonomous Agentic Agents (goal-driven, adaptive, self-optimizing), and how Model Context Protocol (MCP) Servers connect AI to your existing toolchain. We show both models in action with real mainframe use cases.
We then look further ahead at what it means to advance mainframe DevOps for an AI-native enterprise — where AI participates in the delivery pipeline as a collaborator, not just a suggestion engine. Attendees will see how organizations are already making this shift, what the architecture looks like in practice, and how to start without introducing unnecessary risk. Implementation patterns are applicable immediately; the AI-native roadmap gives teams a longer horizon to plan against.
This session addresses both. We examine the practical patterns for integrating AI agents into existing toolchains — the difference between Agentic Workflows (structured, auditable, human-in-the-loop) and fully autonomous Agentic Agents (goal-driven, adaptive, self-optimizing), and how Model Context Protocol (MCP) Servers connect AI to your existing toolchain. We show both models in action with real mainframe use cases.
We then look further ahead at what it means to advance mainframe DevOps for an AI-native enterprise — where AI participates in the delivery pipeline as a collaborator, not just a suggestion engine. Attendees will see how organizations are already making this shift, what the architecture looks like in practice, and how to start without introducing unnecessary risk. Implementation patterns are applicable immediately; the AI-native roadmap gives teams a longer horizon to plan against.
Contributors
DevOps Architect & Evangelist
Lead Product Manager