BONUS How AI Is Reshaping Software Teams From the Inside With Dwarak Rajagopal

BONUS: How AI Is Reshaping Software Teams From the Inside — Lessons From Google, Meta, and Snowflake In this episode, Dwarak Rajagopal — VP of AI Engineering and Research at Snowflake — shares what he's seeing firsthand as AI agents become part of the software development process. From compressed sprint cycles to automated standups across time zones, Dwarak draws on two decades of building AI infrastructure at Google, Meta, Uber, and Apple to show what's actually changing inside engineering organizations today. From Compiler Engineer to AI Leader — The Thread That Connects Two Decades "In AI, the hardest part isn't just the models itself, it's making them work in real environments where data is messy, fragmented, and governed."   Dwarak started his career as an open-source GCC compiler engineer over two decades ago, optimizing hardware performance. He moved into graphics at Apple, then pivoted to AI when AlexNet started running on GPUs around 2011-2012. From there, he built autonomous driving software at Uber, led Meta's PyTorch core framework team bridging research and production, and at Google led AI Frameworks including getting Gemini training on TPUs. The common thread: always working at the intersection of research and production, making powerful technology work in the real world. That focus on real-world application is what drew him to Snowflake — where enterprise data meets AI at scale. AI Is Changing What Engineers Actually Do All Day "Engineers are spending more time on system design, validation, production reliability — and less time doing the implementation itself, because AI is helping that."   The shift Dwarak sees is concrete: AI is accelerating development, but the real value comes when it's grounded in enterprise data and context. At Snowflake, teams use tools like Cortex Code<span style= "f