# Spotify Engineering Blog

Spotify's official technology blog

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## AI Changed How Spotify Builds. What We Learned (and Fixed) About Quality at Higher Velocity

DevFeed: [AI Changed How Spotify Builds. What We Learned (and Fixed) About Quality at Higher Velocity](<https://devfeed.tech/articles/ai-changed-how-spotify-builds-what-we-learned-and-fixed-about-quality-at-higher-velocity-41282.md>)

Original publisher: [Read original article](<https://engineering.atspotify.com/2026/9/ai-changed-how-spotify-builds-what-we-learned-and-fixed-about-quality-at-higher-velocity/>)

Author: Spotify Engineering

Published: 2026-09-16T19:13:53Z

Content type: article

Language: en

Sources: [Spotify Engineering](<https://devfeed.tech/sources/spotify-engineering.md>), [Spotify Engineering Blog](<https://devfeed.tech/sources/spotify-engineering-blog.md>)

Topics: [Monitoring](<https://devfeed.tech/topics/monitoring.md>), [reliability](<https://devfeed.tech/topics/reliability.md>), [Microservices](<https://devfeed.tech/topics/microservices.md>), [Data pipelines](<https://devfeed.tech/topics/data-pipelines.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Job](<https://devfeed.tech/topics/job.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [bug](<https://devfeed.tech/tags/bug.md>), [data-pipelines](<https://devfeed.tech/tags/data-pipelines.md>), [jobs](<https://devfeed.tech/tags/jobs.md>), [microservices](<https://devfeed.tech/tags/microservices.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [reliability](<https://devfeed.tech/tags/reliability.md>)

### AI overview

Spotify describes how rapid change, content-processing weaknesses, capacity limits, and a scheduling bug contributed to delays in publishing episodes. It reports adding end-to-end monitoring, fixing the scheduler, lowering batch-job priority, and increasing capacity.

### Source excerpt

Quality and reliability have always been a point of pride for Spotify. We run an extraordinarily complex... The post AI Changed How Spotify Builds. What We Learned (and Fixed) About Quality at Higher Velocity appeared first on Spotify Engineering.

## Why Spotify Is Not Using Bayesian A/B Testing

DevFeed: [Why Spotify Is Not Using Bayesian A/B Testing](<https://devfeed.tech/articles/why-spotify-is-not-using-bayesian-a-b-testing-156.md>)

Original publisher: [Read original article](<https://engineering.atspotify.com/2026/9/why-spotify-is-not-using-bayesian-a-b-testing/>)

Author: Spotify Engineering

Published: 2026-09-08T13:18:44Z

Content type: article

Language: en

Sources: [Spotify Engineering](<https://devfeed.tech/sources/spotify-engineering.md>), [Spotify Engineering Blog](<https://devfeed.tech/sources/spotify-engineering-blog.md>)

Topics: [Data Science](<https://devfeed.tech/topics/data-science.md>), [Tooling](<https://devfeed.tech/topics/tooling.md>)

Tags: [a-b-testing](<https://devfeed.tech/tags/a-b-testing.md>), [data](<https://devfeed.tech/tags/data.md>), [data-science](<https://devfeed.tech/tags/data-science.md>), [experimentation](<https://devfeed.tech/tags/experimentation.md>), [inference](<https://devfeed.tech/tags/inference.md>), [statistics](<https://devfeed.tech/tags/statistics.md>), [testing](<https://devfeed.tech/tags/testing.md>), [tooling](<https://devfeed.tech/tags/tooling.md>)

### AI overview

Spotify argues that Bayesian A/B testing can be oversimplified and that its claimed advantages require careful configuration. The article compares Bayesian and frequentist approaches and explains why Spotify does not currently need Bayesian inference alongside its frequentist tooling.

### Source excerpt

Clearing the confusion about what Bayesian A/B testing is. The post Why Spotify Is Not Using Bayesian A/B Testing appeared first on Spotify Engineering.

## Portal by Spotify cut my Claude Code token usage by 90%

DevFeed: [Portal by Spotify cut my Claude Code token usage by 90%](<https://devfeed.tech/articles/portal-by-spotify-cut-my-claude-code-token-usage-by-90-155.md>)

Original publisher: [Read original article](<https://engineering.atspotify.com/2026/9/portal-by-spotify-cut-my-claude-code-token-usage-by-90/>)

Author: Spotify Engineering

Published: 2026-09-03T16:06:40Z

Content type: article

Language: en

Sources: [Spotify Engineering](<https://devfeed.tech/sources/spotify-engineering.md>), [Spotify Engineering Blog](<https://devfeed.tech/sources/spotify-engineering-blog.md>)

Topics: [AI Bots](<https://devfeed.tech/topics/ai-bots.md>)

Tags: [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-coding](<https://devfeed.tech/tags/ai-coding.md>), [claude](<https://devfeed.tech/tags/claude.md>), [claude-code](<https://devfeed.tech/tags/claude-code.md>), [cli](<https://devfeed.tech/tags/cli.md>), [gemini](<https://devfeed.tech/tags/gemini.md>), [mcp](<https://devfeed.tech/tags/mcp.md>)

### AI overview

The article describes using Portal modes to route repetitive AI coding work, such as reading large files and generating predictable code, to a cheaper model while reserving Claude for harder problems.

### Source excerpt

Most of what an AI coding agent does for me isn't thinking. It's I/O. The post Portal by Spotify cut my Claude Code token usage by 90% appeared first on Spotify Engineering.

## When Can LLMs Replace Humans in A/B Tests?

DevFeed: [When Can LLMs Replace Humans in A/B Tests?](<https://devfeed.tech/articles/when-can-llms-replace-humans-in-a-b-tests-154.md>)

Original publisher: [Read original article](<https://engineering.atspotify.com/2026/8/when-can-llms-replace-humans-in-a-b-tests/>)

Author: Spotify Engineering

Published: 2026-08-13T18:57:22Z

Content type: article

Language: en

Sources: [Spotify Engineering](<https://devfeed.tech/sources/spotify-engineering.md>), [Spotify Engineering Blog](<https://devfeed.tech/sources/spotify-engineering-blog.md>)

Topics: [Large Language Model](<https://devfeed.tech/topics/llm.md>), [A/B Testing](<https://devfeed.tech/topics/a-b-testing.md>), [datasets](<https://devfeed.tech/topics/datasets.md>), [data](<https://devfeed.tech/topics/data.md>), [experiments](<https://devfeed.tech/topics/experiments.md>)

Tags: [a-b-testing](<https://devfeed.tech/tags/a-b-testing.md>), [analysis](<https://devfeed.tech/tags/analysis.md>), [data](<https://devfeed.tech/tags/data.md>), [data-science](<https://devfeed.tech/tags/data-science.md>), [experiment](<https://devfeed.tech/tags/experiment.md>), [gpt](<https://devfeed.tech/tags/gpt.md>), [llm](<https://devfeed.tech/tags/llm.md>), [llms](<https://devfeed.tech/tags/llms.md>), [model](<https://devfeed.tech/tags/model.md>), [testing](<https://devfeed.tech/tags/testing.md>)

### AI overview

The article examines whether large language model predictions can replace human outcomes in A/B tests. Using the Upworthy dataset, it finds that calibrated predictions can recover treatment effects under specific assumptions, while raw predictions recovered only 39% of the observed human effect.

### Source excerpt

TL;DR: LLM predictions can stand in for human outcomes in A/B tests, but only by assumption, not by design.... The post When Can LLMs Replace Humans in A/B Tests? appeared first on Spotify Engineering.

## Indexing the Data Lake for Online Point Queries

DevFeed: [Indexing the Data Lake for Online Point Queries](<https://devfeed.tech/articles/indexing-the-data-lake-for-online-point-queries-152.md>)

Original publisher: [Read original article](<https://engineering.atspotify.com/2026/7/indexing-the-data-lake-for-online-point-queries/>)

Author: Spotify Engineering

Published: 2026-07-27T20:34:28Z

Content type: article

Language: en

Sources: [Spotify Engineering](<https://devfeed.tech/sources/spotify-engineering.md>), [Spotify Engineering Blog](<https://devfeed.tech/sources/spotify-engineering-blog.md>)

Topics: [AI, ML & Data Engineering](<https://devfeed.tech/topics/ai-ml-data-engineering.md>), [Amazon S3](<https://devfeed.tech/topics/amazon-s3.md>)

Tags: [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [analytics](<https://devfeed.tech/tags/analytics.md>), [bigquery](<https://devfeed.tech/tags/bigquery.md>), [data](<https://devfeed.tech/tags/data.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [low-latency](<https://devfeed.tech/tags/low-latency.md>), [parquet](<https://devfeed.tech/tags/parquet.md>), [sql](<https://devfeed.tech/tags/sql.md>), [storage](<https://devfeed.tech/tags/storage.md>)

### AI overview

Spotify describes Random Access Parquet (RAP), which uses an external index and ranged reads to support low-latency key-based lookups in data-lake Parquet files without maintaining separate serving copies.

### Source excerpt

Companies like Spotify need vast quantities of data accessible at low latency for online services and,... The post Indexing the Data Lake for Online Point Queries appeared first on Spotify Engineering.

## Content Ingestion & Podcast Video Incident Report

DevFeed: [Content Ingestion & Podcast Video Incident Report](<https://devfeed.tech/articles/content-ingestion-podcast-video-incident-report-149.md>)

Original publisher: [Read original article](<https://engineering.atspotify.com/2026/7/content-ingestion-and-podcast-video-incident-report/>)

Author: Spotify Engineering

Published: 2026-07-20T16:24:48Z

Content type: article

Language: en

Sources: [Spotify Engineering](<https://devfeed.tech/sources/spotify-engineering.md>), [Spotify Engineering Blog](<https://devfeed.tech/sources/spotify-engineering-blog.md>)

Topics: [incident](<https://devfeed.tech/topics/incident.md>), [Transcodings](<https://devfeed.tech/topics/transcodings.md>), [systems](<https://devfeed.tech/topics/systems.md>), [Playback](<https://devfeed.tech/topics/playback.md>)

Tags: [analysis](<https://devfeed.tech/tags/analysis.md>), [batch](<https://devfeed.tech/tags/batch.md>), [cost](<https://devfeed.tech/tags/cost.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [incident](<https://devfeed.tech/tags/incident.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [media](<https://devfeed.tech/tags/media.md>), [playback](<https://devfeed.tech/tags/playback.md>), [publication](<https://devfeed.tech/tags/publication.md>), [scale](<https://devfeed.tech/tags/scale.md>)

### AI overview

Spotify Engineering reports on a June 24 incident in which video transcoding infrastructure reached capacity, creating a queue backlog and delaying podcast video publication for several hours. The report identifies limited capacity headroom, a concurrent batch-processing job, and increased per-item processing costs as contributing factors, and describes a broader reliability program for the publishing pipeline.

### Source excerpt

Over the past two months, podcast creators have experienced a series of reliability issues on Spotify. This... The post Content Ingestion & Podcast Video Incident Report appeared first on Spotify Engineering.