AI-Driven Developer Productivity at Scale

AI is rapidly transforming the software development lifecycle, offering new ways for developers to build, test, and maintain applications more efficiently. From monorepo-aware coding assistants to agentic systems for large-scale code migrations, and from AI-generated tests to probabilistic agents reshaping quality strategies—this panel dives into the cutting edge of AI-powered developer tools. You’ll leave with actionable strategies for implementing AI in your own workflows, and practical ideas for driving meaningful productivity gains across your teams.
>What does “AI-driven productivity” look like in practice across the software development lifecycle?
>How can coding assistants be customized to work effectively in complex environments like monorepos or large codebases?
>What are agentic AI systems, and how are they being used for tasks like large-scale code migrations or refactoring?
>How is AI reshaping the traditional test pyramid—from the ground up with code generation, and from the top down with probabilistic testing?
>What are some low-lift, high-impact ways mobile teams can start integrating AI into their workflows today?