1. Leveraging Agentic AI in Games
Agentic AI turn your game into a living, breathing world.
Agentic AI brings a new layer of intelligence to games, NPCs that remember your actions, QA bots that adapt as the game evolves, and support systems that respond with real understanding. It’s not about replacing creative teams, but giving them tools to build deeper, more personal, and more responsive experiences.
https://www.databricks.com/blog/leveraging-agentic-ai-games
2. Model Once, Represent Everywhere: UDA (Unified Data Architecture) at Netflix
Netflix unify petabytes of data across teams, tools, and use cases, without breaking everything
Netflix is solving one of the hardest problems in modern data systems: fragmented, duplicated, inconsistent models across platforms. Instead of forcing uniformity, they’ve built a semantic knowledge graph that lets teams define core concepts once, then reuse, map, and project them everywhere. UDA is quietly transforming how data connects, scales, and stays human-readable in a world of microservices and massive content growth.
https://netflixtechblog.com/uda-unified-data-architecture-6a6aee261d8d
3. Making Every Search Rewarding: How Ibotta Transformed Offer Discovery With Databricks.
Ibotta rebuilt its offer discovery engine using Databricks to personalize, scale, and delight millions of users.
The authors in this post show how Ibotta went from prototype to production, transforming search with fine-tuned models and Databricks Vector Search. It's a story of precision, iteration, and making every query count, reducing zero-result searches by 70% and unlocking meaningful engagement at scale.
4.The Apache Iceberg v3 Table Spec: Celebrating the Open Source Community’s Shared Success
Apache Iceberg v3 strengthen the open data ecosystem, and what role has the open source community played in shaping its new table spec
Apache Iceberg’s new v3 table spec is more than just a technical update, it’s a story of community, collaboration, and open standards shaping the future of data. If you care about how vendor-neutral innovation happens in real time, powered by hundreds of contributors across companies. From default values to deletion vectors and geospatial types, it offers a deep dive into how open source is building scalable, flexible data infrastructure.
https://www.snowflake.com/en/blog/apache-iceberg-v3-table-spec-oss-shared-success/
5. Load Testing with Impulse at Airbnb
Airbnb usesImpulse to simulate millions of requests and ensure their systems scale reliably under peak load conditions.
Airbnb’s Impulse isn’t just a load testing tool, it’s a powerful framework that helps engineers simulate real-world traffic, mock complex dependencies, and test asynchronous flows, all within CI/CD. This post is a must-read if you care about building resilient systems at scale , it shows how decentralized, self-service load testing can catch the hard problems.
https://medium.com/airbnb-engineering/load-testing-with-impulse-at-airbnb-f466874d03d2
I have provided links for informational purposes and do not suggest endorsement to you. All views expressed in this newsletter are my own and do not represent current, former, or future employer” opinions.