Spotify Launches Xirp for Managing AI Coding Agent Sessions

Aug 12, 2026
Spotify launched Xirp, a vendor neutral environment for managing parallel AI coding agent sessions across tools such as Claude Code, Gemini CLI, and Codex.
Spotify Launches Xirp for Managing AI Coding Agent Sessions

On August 10, 2026, Spotify launched Xirp, a vendor neutral agentic development environment for managing AI coding agent sessions. The tool is designed to coordinate sessions across coding agent harnesses including Claude Code, Gemini CLI, and Codex.

Xirp runs each agent session in its own Git worktree, allowing multiple agents to work on the same codebase without interfering with each other. Spotify said the system can make more than 50 parallel sessions manageable and lets developers switch tools or models during a task while carrying over the working state.

The company also described an integration between Xirp and Portal, its developer platform connected to Backstage. With Portal, agent sessions can start with context from a software catalog, including component architecture, dependency graphs, ownership data, and architectural decisions. Session transcripts and metadata can then flow back into Portal for later use by engineers or agents.

Spotify said thousands of its engineers have used Xirp across more than 36,000 sessions. The tool is available to try at xirp.spotify.com.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like AI Programming Weekly or Daily AI Brief.

Also, consider following us on social media:

AI Brief AI Brief (X)
Free newsletter

AI Programming Weekly

Weekly news about AI tools for software engineers, AI enabled IDE's and much more.

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.