Modernizing legacy applications is often a manual, high-risk endeavor. However, the emergence of AI-native development tools like GitHub Copilot and agentic IDE assistants has introduced a new playbook for architectural refactoring. This 45-minute session moves beyond “code completion” to explore ten high-impact, practical techniques for extending and securing aging codebases. This gives a bit of a roadmap for the software architect to finally ask the questions that took an unbounded time to investigate only a few years ago.

We will demonstrate how to treat your infrastructure and documentation as code-ready context, using AI to perform complex “archaeology” and reconstruction. You will learn how to automate the generation of system diagrams from messy Helm charts and how to synthesize OpenAPI specifications from undocumented endpoints to jumpstart new service integrations.

We will also tackle the “unseen” side of legacy debt: using AI to identify version mismatches in dependencies, verifying code against OWASP security standards, and building automated scalability tests. Finally, we’ll dive into the frontier of Agentic DevOps, showing how to test coordinating groups of agents and validate the accuracy of RAG (Retrieval-Augmented Generation) outputs to ensure your AI-assisted architecture remains grounded in truth.

Audience - software architects generally with legacy modernization concerns
Requirements - none other than understanding of your architecture & design process
Session about 1 hour with Q&A