Browse past weeks of engineering reads.
Spotify's podcast video ingestion pipeline experienced reliability issues that degraded the experience for podcast creators over a two-month period.
Spotify needed to reduce friction in data discovery and analytics by enabling non-technical users to ask natural language questions about data without requiring dashboard navigation or SQL expertise.
Scaling developer productivity and experience when coding is no longer the primary bottleneck, requiring infrastructure and tooling that enable both human teams and AI agents to work effectively.
Efficiently evaluating and validating LLM-generated outputs at scale during experimentation without manual review bottlenecks.
Spotify needed to migrate thousands of downstream datasets when source datasets changed structure, without manually updating each consumer application.
Making the Spotify Ads API accessible to non-technical users and reducing friction in ad campaign management by enabling natural language interaction instead of requiring direct API integration.
How to identify and surface the most interesting and meaningful listening moments from a year's worth of user streaming data to create personalized narrative highlights for Wrapped.
How can software engineers leverage AI agents to improve development workflows and productivity at scale?
Spotify needed to optimize ad targeting and delivery at scale by coordinating multiple specialized systems to make smarter advertising decisions rather than relying on monolithic ad selection logic.