AI-Generated Code Is Forcing a Rethink of Code Review in Drupal

A blog post by Ronald te Brake examines how the rise of AI-generated code is exposing limits in traditional code review practices, particularly those centred on reviewing diffs alone.

The article argues that while tools like Git effectively show what changed, they provide little visibility into why changes were made, what constraints shaped them, or how AI systems contributed to the outcome. As AI accelerates code generation, maintainers are left reviewing larger volumes of changes with reduced context, leading to what the author describes as “intent” and “comprehension” debt.

To address this gap, the post highlights emerging approaches that capture additional context alongside code changes, including prompts, intermediate steps, and attribution between human and AI contributions. Experiments with tools such as the Entire CLI show how this information can be surfaced within existing workflows, allowing reviewers to inspect not just the result, but the process behind it.

The article frames this as a shift toward “intent review,” where understanding the problem, constraints, and decision path becomes a precursor to examining implementation details. Rather than replacing traditional review, this approach adds a layer of transparency that supports maintainability, auditability, and trust in increasingly AI-assisted development environments.