Summary Generative AI has rapidly transformed everything in the technology sector. When Andrew Lee started work on Shortwave he was focused on making email more productive. When AI started gaining adoption he realized that he had even more potential for a transformative experience. In this episode he shares the technical challenges that he and his team have overcome in integrating AI into their product, as well as the benefits and features that it provides to their customers. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Dagster offers a new approach to building and running data platforms and data pipelines. It is an open-source, cloud-native orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. Your team can get up and running in minutes thanks to Dagster Cloud, an enterprise-class hosted solution that offers serverless and hybrid deployments, enhanced security, and on-demand ephemeral test deployments. Go to dataengineeringpodcast.com/dagster today to get started. Your first 30 days are free! Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics. Trusted by teams of all sizes, including Comcast and Doordash, Starburst is a data lake analytics platform that delivers the adaptability and flexibility a lakehouse ecosystem promises. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data. Want to see Starburst in action? Go to dataengineeringpodcast.com/starburst and get $500 in credits to try Starburst Galaxy today, the easiest and fastest way to get started using Trino. Your host is Tobias Macey and today I'm interviewing Andrew Lee about his work on Shortwave, an AI powered email client Interview Introduction How did you get involved in the area of data management? Can you describe what Shortwave is and the story behind it? What is the core problem that you are addressing with Shortwave? Email has been a central part of communication and business productivity for decades now. What are the overall themes that continue to be problematic? What are the strengths that email maintains as a protocol and ecosystem? From a product perspective, what are the data challenges that are posed by email? Can you describe how you have architected the Shortwave platform? How have the design and goals of the product changed since you started it? What are the ways that the advent and evolution of language models have influenced your product roadmap? How do you manage the personalization of the AI functionality in your system for each user/team? For users and teams who are using Shortwave, how does it change their workflow and communication patterns? Can you describe how I would use Shortwave for managing the workflow of evaluating, planning, and promoting my podcast episodes? What are the most interesting, innovative, or unexpected ways that you have seen Shortwave used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on Shortwave? When is Shortwave the wrong choice? What do you have planned for the future of Shortwave? Contact Info LinkedIn Blog Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with m