Let’s be honest: content migrations are one of the most fascinating challenges in Drupal. You’re reverse-engineering years of content architecture, understanding how a site evolved, and designing a pipeline to reshape everything into a new structure.

Our challenge: a Drupal 10 site with 163 paragraph types — many acting as rich HTML containers mixing headings, images, documents, and embeds — to be transformed into 42 clean, typed bundles in Drupal 11. A 4:1 compression that raised a key question: what if, instead of mapping content one-to-one, we decompose it into atomic fragments and reassemble it into something new?

First, we needed visibility. Analysing 163 paragraph types, tracing references, and measuring field usage across thousands of items is complex. So we built an AI agent with 12 atomic skills to query the source database, analyse bundles on demand, detect orphans, verify usage, and generate structured issues — turning weeks of exploration into repeatable analysis.

Then came the engineering: a system to split HTML into typed fragments via DOM traversal, a deriver pipeline to fan out migrations, and a content assembler to rebuild paragraph fields by probing multiple migration maps with fallback logic.

This is a different approach to complex migrations — combining AI-assisted analysis with creative engineering from day one.