AGNTCon + MCPCon Europe 2026

Enterprise mainframe systems often contain large amounts of unused and unreachable code, increasing complexity and risk. Safely removing this logic is difficult due to deeply interconnected execution paths.

In this session, I present a real-world case study where we delivered large-scale dead code remediation into production with zero incidents using an MCP-powered agentic AI approach.

We developed specialised AI agents, backed by Python tooling, to analyse code, detect unused logic, and support safe, auditable remediation with human validation. This reduced analysis time from days to under an hour per program.

The same approach was extended to business knowledge enablement using a reverse engineering agent, generating structured context integrated into Copilot Spaces, enabling finance teams to query system behaviour using natural language.

Learn how agentic AI can safely modernise legacy systems and bridge developer and business understanding.