Enforce Small PRs for AI-Generated Code
AI tools make it easy to generate thousands of lines of code in seconds. This often leads to "AI-slop" PRs that are so large they are impossible to review, hiding bugs and security flaws. This practice destroys team velocity and code quality by creating massive review bottlenecks.
You should maintain and enforce strict pull request (PR) size limits (e.g., ≤250-400 lines) for all code, especially AI-generated code.1 The ease of generation must not be allowed to bypass the human requirement for thorough, manageable review.
The adoption of AI coding tools is directly correlated with a massive increase in PR size. One 2025 report found that a 90% increase in AI adoption was associated with a 154% increase in pull request size. Another analysis found AI-assisted PRs are, on average, 18% larger. This directly causes pain-point-10-oversized-prs. Large PRs are the enemy of quality. They are cognitively overwhelming, difficult to review, and create "review fatigue".3 This fatigue is dangerous, as it's the primary reason that subtle pain-point-01-almost-correct-code bugs and security flaws are missed by human reviewers.2 Small, focused PRs are reviewed more quickly, are less error-prone, and are merged faster.1 Enforcing this policy is a non-negotiable guardrail to maintain human accountability and ensure the quality of your codebase.
This rule must be enforced for all developers on all teams as a core part of the team's standard development workflow. It is a critical counterpart to the adoption of any AI code-generation tool.
Set a Clear Standard: Agree on a reasonable line limit for PRs (e.g., 250-400 lines of meaningful change) and document it in your PR template.1 Automate Enforcement: Use automated tooling in your CI pipeline or code host (like GitHub/GitLab) to flag or block PRs that exceed this limit. Train Developers: Coach your team to break down large, AI-generated features. Instead of one giant PR for a new feature, they should submit a series of small, focused PRs (e.g., "1. Add data models," "2. Create service layer," "3. Build API endpoint"). Use AI for Summaries: For the small PRs you do have, use AI in the CI pipeline to automatically summarize the changes, reducing the reviewer's cognitive load even further (see Rec 19).4
Workflows that implement or support this recommendation.
- Creating a comprehensive code review checklist for your team - Graphite.com - https://graphite.com/guides/code-review-checklist-guide
Code review best practices including PR size limits. - Empirically supported code review best practices : r/programming - Reddit - https://www.reddit.com/r/programming/comments/18mghkp/empirically_supported_code_review_best_practices/
Research on code review practices and PR size. - A smarter code review checklist: What to track, fix, and improve - Appfire - https://appfire.com/resources/blog/code-review-checklist
Code review checklist and PR size management. - Boost your Continuous Delivery pipeline with Generative AI | Google ... - https://cloud.google.com/blog/topics/developers-practitioners/boost-your-continuous-delivery-pipeline-with-generative-ai
Using AI for PR summaries and automated documentation.
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Engineering Leader & AI Guardrails Leader. Creator of Engify.ai, helping teams operationalize AI through structured workflows and guardrails based on real production incidents.