The State of Large-Scale Code Modernization: AI, Languages, Security

Software keeps moving—and so must we. From end-of-life frameworks to sprawling polyglot stacks and never-ending CVEs, modernizing code at scale is one of the toughest, most necessary problems in engineering today. In this keynote, we’ll take a clear-eyed look at where we are—and what it really takes to move forward.

We’ll unpack the rise of agentic AI, and why the future isn’t just about bigger models but better data and tools. Generative AI may be great at writing new code, but modernizing existing code? That takes precision—and deterministic systems that know when not to guess.

We’ll also dig into the language engineering problem: how do you unify modernization with codebases written in Java, C#, Python, JavaScript, and more? Each language needs a custom model that captures types, formatting, and structure for meaningful, accurate change at scale.

Finally, we’ll confront the security tradeoffs facing modern teams: should you upgrade fast to stay on the latest most secure versions, or leverage back patches to stay secure on what you know? The answer isn't always forward motion—it’s smarter, safer modernization.