From AI experiments to organizational shift: Lessons from Mercari’s transformation (Michael Galloway and Snehal Shinde)

Michael Galloway leads Platform Engineering at Mercari, while Snehal Shinde leads Cost and Performance Engineering. Together, they have been at the center of Mercari's effort to become an AI-native company.In this session from DX Annual, Michael and Snehal share what happened after Mercari's CEO mandated 100% AI adoption across the organization. While AI accelerated code generation and increased engineering output, the team quickly discovered that their existing dashboards could not answer a simple question: was AI actually improving productivity?They discuss how Mercari built new visibility into AI usage and software delivery, the bottlenecks they uncovered across the SDLC, why faster coding did not automatically translate into faster delivery, and the lessons they learned rolling out AI at scale. They also share how Mercari is rethinking software development around agents, feedback loops, and new ways of working.In this episode, we cover:(00:00) Intro(01:46) Mercari’s scale and engineering culture(02:51) DX awards at Mercari(03:44) Mercari’s push to become AI-native(06:34) The mandate to rethink everything(08:02) Mercari’s AI visibility problem and how they solved it(11:30) Mercari’s early findings on AI implementation(18:47) Closing the AI awareness gap at Mercari(21:11) Mapping AI opportunities across Mercari(31:32) Unpacking the results from the second rollout(34:14) Agent spec-driven development and what’s next(37:37) A multi-loop SDLC(40:50) Some hard lessons(42:55) Closing thoughtsReferenced:• Mercari• Cursor• Devin• Claude Code | Anthropic's agentic coding system• GitHub• Datadog• Tim Bozarth - Microsoft | LinkedIn• Airbnb• Jim Collins - Concepts - The Stockdale Paradox