@spotify-engineering
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Spotify's goal for AI is bold, but simple: make it as intuitive and indispensable to daily work as email or Google Docs. And not just for engineers, but for every Spotifier across every function.
At Spotify, data problems used to follow a specific pattern. You'd look for the relevant dashboard, there weren't any. You'd message the corresponding data expert on Slack, wait until they had time to help. But with thousands of teams moving fast, the demand for data insights had quietly outpaced...
What happens when coding stops being the bottleneck? At Spotify, we’re starting to find out.
TL;DR LLM evals, automated judges that assess relevance, coherence, and quality at scale, are a powerful new tool. Paired with online experiments, they raise the hit rate of what we test and create a feedback loop that makes both evals and experiments smarter over time.
We built a suite of skills, agents and tools bundled as a plugin to make the Spotify Ads Platform easily accessible to AI agentic tools. The spotify-ads-api plugin is available on and through Anthropic's marketplace. Download it now and create your own advertising campaigns just by asking Claud...
This is part 4 in our series about Spotify's journey with background coding agents (internal codename: “Honk”) and the future of large-scale software maintenance. See also , , and .
