Code grew 7x faster than headcount; hundreds of teams ran identical migrations for months. Agents now author and auto-merge the bulk of PRs.
A global streaming platform with 2,900 engineers managing a backend exceeding 20 million lines of code across thousands of repositories, shipping 4,500 production deployments daily.
The codebase was growing seven times faster than the engineering headcount, with hundreds of teams manually executing the same migrations across...
“And then two months later I found myself not using an IDE anymore. And the way that I was working had completely changed. A change that I had not seen in, again, the 30 years that I’ve been doing this.”
Audio streaming platform for music, podcasts, and digital content.
Anthropic is a technology company specializing in artificial intelligence and machine learning solutions.
Spotify's Codebase automation is part of this use case:
Related implementations across industries and use cases
Rigid scripts left complex migrations manual. Now, a background agent turns natural language prompts into verified, merged pull requests.
Simple data requests faced months-long delays. Now, an AI agent writes production-ready pipelines, cutting review time by 41%.
Designers relied on static mocks and engineering queues. Now they build live apps directly, shrinking 6-month cycles to 8 weeks.
Rigid scripts left complex migrations manual. Now, a background agent turns natural language prompts into verified, merged pull requests.
Simple data requests faced months-long delays. Now, an AI agent writes production-ready pipelines, cutting review time by 41%.
Translating updates one language at a time bottlenecked distribution. Now, AI drafts multilingual commentary in minutes for editor review.
Rugby match data existed but never reached fans live. AI now turns it into 65+ on-screen insights per game, built and approved by analysts.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
Code grew 7x faster than headcount; hundreds of teams ran identical migrations for months. Agents now author and auto-merge the bulk of PRs.
A global streaming platform with 2,900 engineers managing a backend exceeding 20 million lines of code across thousands of repositories, shipping 4,500 production deployments daily.
The codebase was growing seven times faster than the engineering headcount, with hundreds of teams manually executing the same migrations across...
“And then two months later I found myself not using an IDE anymore. And the way that I was working had completely changed. A change that I had not seen in, again, the 30 years that I’ve been doing this.”
Audio streaming platform for music, podcasts, and digital content.
Anthropic is a technology company specializing in artificial intelligence and machine learning solutions.
Spotify's Codebase automation is part of this use case:
Related implementations across industries and use cases
Rigid scripts left complex migrations manual. Now, a background agent turns natural language prompts into verified, merged pull requests.
Simple data requests faced months-long delays. Now, an AI agent writes production-ready pipelines, cutting review time by 41%.
Designers relied on static mocks and engineering queues. Now they build live apps directly, shrinking 6-month cycles to 8 weeks.
Rigid scripts left complex migrations manual. Now, a background agent turns natural language prompts into verified, merged pull requests.
Simple data requests faced months-long delays. Now, an AI agent writes production-ready pipelines, cutting review time by 41%.
Translating updates one language at a time bottlenecked distribution. Now, AI drafts multilingual commentary in minutes for editor review.
Rugby match data existed but never reached fans live. AI now turns it into 65+ on-screen insights per game, built and approved by analysts.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.