Beyond code generation: rethinking engineering productivity in the age of AI agents

This post details the evolution of Dropbox's approach to AI in engineering, moving from AI coding assistants (copilots) to AI agent platforms like Nova. It explains how Nova enables engineers to delegate scoped tasks to AI agents, which can inspect code, edit files, run tests, and iterate on failures. The post highlights that the value of Nova comes from the surrounding systems (codebase context, engineering practices, safe execution, workflow integration, human review) rather than just the models. It also discusses the shift in measuring engineering productivity from code output (e.g., PR throughput) to broader system outcomes, including workflow adoption, production output, and customer impact, while emphasizing the importance of quality and trust. The post also touches on the need for engineers to adapt their workflows and the importance of enablement alongside tooling for successful agentic adoption.