Most AI success stories are based on simple greenfield projects with few dependencies and fast feedback loops. That's not the world most enterprise developers live in. Brownfield applications are complex, built piecemeal over years. Developer experiences are full of bottlenecks - slow and inaccurate feedback loops, incomplete documentation, outdated frameworks. These are problems that human developers make up for. There is now another customer of that same experience: the AI Agent. Every gap developers learned to live with becomes a hurdle the agent must overcome. To make our platforms ready for AI we have to close those gaps.
This talk draws on two years working with enterprise teams moving from tactical AI tooling adoption to rethinking their team workflows to be AI Native. It covers practical techniques for assessing your platform's AI Readiness. I'll walk through the most common issues teams find, how shifting bottlenecks change your investment priorities, and what it actually takes to build a platform experience that works for both your developers' new role and your AI agents.
