Your team is under pressure to ship apps and AI agents faster, but the data architecture underneath keeps getting in the way. You're managing a separate operational database and analytics warehouse, maintaining pipelines to move data between them, and still waiting on stale data and untangling governance gaps. This session looks at how teams are simplifying that picture with Lakebase and LTAP. We'll start with the everyday problems: environments that are slow to spin up, databases that are hard to scale, and analytics that can't keep up with what your app just wrote. Then we'll show how a serverless Postgres built on open lake storage changes the day-to-day, from branching a full database in seconds to running analytics on live operational data without building a single pipeline. You'll leave with a clear picture of where Lakebase and LTAP can remove friction from your own stack and how other teams are already putting it to work. Built for data engineers, application developers, and platform teams.