Mission Refactored: Scaling Legacy Modernization with Agentic AI

Legacy software is a silent readiness risk. Across the Department of Defense (DOD) and the defense industrial base, mission-critical applications are often tethered to aging codebases that accumulate technical debt and resist modern security hardening. Traditional manual modernization is too slow to meet the pace of modern conflict and cloud-based AI tools are non-starters for sensitive or disconnected environments.

This webinar explores an alternative, an agentic software factory that enables engineers to supervise modernization at scale rather than performing every refactor by hand. We will detail the "Agent Mesh" architecture, a modular harness of specialized, small language models (SLMs) designed to operate entirely offline. Unlike standard frontier models, this approach uses agents to analyze legacy code, generate refactored equivalents for RHEL 10, and produce characterization tests to ensure functional equivalence.

You'll learn how to:

• Transition From Manual Code Migration to a Supervised Automation Model: Ensure that legacy systems are not just updated, but transformed into secure, supportable foundations for the next generation of mission delivery.
• Deploy Offline Agent Meshes: Build specialized AI harnesses for disconnected, mission-critical environments using local small language models.
• Automate Functional Validation: Use coding agents to generate characterization tests, ensuring refactored code maintains identical behavioral intent.
• Measure Modernization Success: Establish KPIs focused on functional equivalence and developer trust over simple completion speed.