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 part 1, part 2, and part 3.In Part 2, we explored how we enabled our Fleet Management tools to use agents to rewrite our software automatically. We also explored how to write good prompts that allow the agent to best work without needing human input. In this blog post, we give a case study of how one team at Spotify used Honk with our Backstage and Fleet Management platforms to ease the pain of migrating thousands of dataset consumers onto new dataset versions — saving an estimated 10 engineering weeks in the process. We also share what we learned about how to make our data landscape more autonomous-coding-agent–friendly in the process.Dataset migrations can be painfulAs any data team knows, getting users to migrate to new endpoints can be a slow and painful process, both for the data owners and the downstream teams that use the datasets day-to-day.At the end of last year we needed to deprecate two of the most heavily-used user datasets in order to release new versions with additional dimensions that would unlock new features. These deprecated datasets had ~1,800 direct downstream data pipelines between them and indirectly impacted several thousand more across the entire company. We faced the prospect of migrating ~1,800 direct downstream data pipelines in only six months, across three very different pipeline frameworks that we use at Spotify: the SQL-based BigQuery Runner and dbt frameworks, and the Scala-based Scio.We estimated that it would have taken around 10 engineering weeks of effort to complete these migrations manually. Facing that much work, we explored how Backstage, Fleet Management, and Honk might be able to automate some of the complexity. Simplifying fleet migrations with BackstageBefore we could begin making any code changes, we had to first understand the lineage of our deprecated datasets so we would know which repositories to make those changes in. This is where Backstage’s endpoint lineage and Codesearch plugins came in. Each endpoint’s Backstage page gave a clear list of downstream consumers, giving us an immediate sense of the scale of our migration. With Codesearch, we wrote queries that would find target repositories across the Spotify GitHub Enterprise landscape, and mark them as in-scope for our migrations, which we orchestrated using our Fleetshift plugin.