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Turn one giant AI-generated pull request to a reviewable stack
GitHub's stacked pull requests enable developers to break massive AI-generated PRs into chains of small, independently reviewable layers.
What: GitHub has introduced a native workflow to manage 'stacked' pull requests, allowing for code review on incremental, single-concern commits rather than massive, opaque diffs produced by AI tools.
Why it matters: AI code generators often output massive chunks of code that are impossible to review manually; decomposition is the only path to maintainable code quality.
Takeaway: Adopt stacked PR workflows for AI-assisted features to prevent review bottlenecking and improve tracking of specific commits.
Original article
GitHub stacked pull requests give developers and their agents a native way to decompose work that otherwise lands in a giant pull request. It turns pull requests into a chain of small, focused, and independently reviewable layers, each scoped to a single concern. This post explains how to use stacked pull requests to simplify reviews.
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