Story
The exponential curve behind open source backlogs
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Overview
Open source contributions can experience significant delays, with some pull requests (PRs) waiting over a year for merges despite receiving approvals. Factors contributing to these backlogs include queuing theory dynamics and the allocation of time within the review process.
Summary from armanckeser.com.
Reports
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Community reactions
Each reaction summarizes sampled comments from the linked discussion.
Hacker News · armanckeser.com
Hacker News discussion ↗
Historical count: 5 · 5 saved in sample · Historical sample
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Based on 5 sampled comments from this thread. Analyzed 2026-04-14.
- Praise: Automated code review using AI can significantly reduce the time spent on trivial mistakes, allowing maintainers to focus on more complex architectural issues, which is crucial for project efficiency.
- Praise: Leveraging AI for code reviews could enhance the quality of feedback if better prompting techniques are employed, potentially improving developer experience and project outcomes.
- Concern: AI code reviews are often unreliable, with a correctness rate of only about 80%, leading to increased workload as maintainers must verify both the original code and AI-generated feedback.
- Concern: The current implementation of AI in code reviews does not save time for maintainers, as they end up reviewing both the pull request and the AI's comments, which can be counterproductive.