Mike Nakhimovich

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?