Automating Drupal Code Refactoring and Reviews with LLMs

Scott Weston of Bounteous explores how Large Language Models can automate Drupal code refactoring and reviews. He argues that LLMs complement static analysis tools by tracing complex logic flows, spotting edge-case bugs, suggesting dependency-injection refactors, and enforcing team style conventions. By offloading routine checks to AI, senior engineers can focus on architecture and business logic without slowing development velocity.

The article outlines practical integration patterns: local pre-commit Git hooks querying a self-hosted model, pull-request bots using cloud APIs to post inline feedback, and scheduled repository-wide scans for deprecations or security gaps. Weston emphasizes precise prompt engineering, privacy considerations for cloud versus self-hosted LLMs, and CI cost controls such as file size limits and caching unchanged files.

Bounteous’s guide is detailed and actionable, with sample scripts and prompt templates. It could be strengthened with empirical data on review time savings, cost comparisons between cloud and local models, and case studies demonstrating improved code quality in real-world Drupal projects.