Every developer eventually faces the challenge of maintaining legacy code: systems written by others, often under time pressure, and difficult to understand or modify. While humans excel at creativity and problem-solving, cognitive overload makes it hard to trace complex dependencies or reason through tangled logic. AI offers a complementary advantage: it can process large codebases, identify potential issues, and generate structured insights without fatigue.

This session explores practical ways to apply AI in analyzing, reasoning about, and improving legacy systems. Attendees will learn how AI tools can surface hidden defects, suggest fixes, and assist in documenting difficult code sections. By combining human judgment with AI’s analytical strength, developers can make legacy codebases more maintainable, reliable, and easier to extend.

What You Will Learn

• How to use AI tools to detect and analyze issues in legacy codebases

• Techniques for reasoning about and documenting complex or poorly understood code

• Strategies for combining human expertise with AI assistance to improve maintainability

Who Should Attend

Developers, software engineers, and technical leads working with large or legacy systems who want to apply AI to streamline debugging, refactoring, and documentation.