Robert Brennan

This talk explores automating large-scale software refactoring and maintenance tasks using parallel AI agents. The core idea is that while individual agents are effective for smaller tasks, complex, multi-faceted operations like dependency updates, code modernization, or vulnerability remediation require orchestrating multiple agents working in parallel. This approach aims to tackle significant technical debt and improve developer productivity by automating laborious processes that are currently too large or complex for a single agent.

This talk explores the practical application and effectiveness of software development agents, emphasizing the shift from manual coding to higher-level problem-solving. It argues that while AI excels at the iterative process of writing and running code, human engineers remain crucial for critical thinking, user empathy, and architectural decisions. The presentation details the core components of these agents, their underlying mechanisms, and best practices for their integration into the development workflow.