Jonathan is a Developer Advocate at AWS. Jonathan’s been doing all things automation and developer productivity at AWS since 2020. Prior to AWS, he practiced professional software development for over a decade. Jonathan enjoys music, birding and climbing rocks.
Java has powered enterprise systems for nearly three decades—but many teams still struggle with aging codebases, performance bottlenecks, and the complexity of modern cloud environments. In this session, we explore how generative AI is transforming not just how we write code, but how we modernize and optimize entire Java workloads through practical, end-to-end workflows.
You’ll learn how to use AI-assisted tools to refactor and upgrade legacy Java code, adopt modern frameworks and architectures, and continuously improve performance. We’ll go beyond code-level changes and show how AI can help analyze runtime behavior, uncover bottlenecks, and guide optimizations using tools like Java Flight Recorder and other observability techniques.
We’ll also cover how to combine different approaches—from existing tools to custom AI Embabel agents —that allows you to build a repeatable workflow that connects code changes with measurable performance improvements in production systems.