AI-assisted development is shifting from solo experimentation to team-wide engineering practices. As AI tooling and workflows evolve rapidly, Engineering Managers and Staff+ Engineers need to rethink what engineering culture means in the AI era. This roundtable will explore how we can build an AI-ready engineering culture that increases velocity without degrading architecture, maintainability, or code quality. How do we move faster with AI without introducing technical debt or AI slop? How do we choose the right AI tools and train engineers to use the appropriate model or workflow for each task? How do we share prompts, skills, agents, MCP servers, and workflows across multiple teams and repositories? How should code review, testing, and CI evolve in the age of AI-generated code? What signals show that AI adoption is improving engineering culture rather than eroding it? Which engineering metrics still matter in the AI era, and which ones need to change?