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Jev-based code review on Hacker News
The thread on classifying each change in an agent pull request as P0, P1, or P2 so a reviewer only sees the highest tier by default.
- Format
- Post
- Published by
- Community
- Author
- namanbhulawat
- Last verified
- Sep 2026
Used inJev for Software & DevTools
Highlights
- 47 points and 56 comments on 25 September 2026.
- The author says agent pull requests can land with 230 file changes that people merge unread.
- The tool ranks each change P0, P1, or P2, and shows only P0 by default.
Watch out
The 230-file figure is the author's example of the problem, not a measured review of that diff.
Questions about this entry
Short answers drawn from the linked project or page.
A ranking demo, as far as anything published goes. The entry copy documents no detection rates or false-negative counts, and the 230-file pull request is the author's example of the problem rather than a measured review of that diff.
Ordering is what is documented: each change is ranked P0, P1 or P2 and only P0 shows by default. The thread publishes no accuracy data for spotting defects, so treat the triage as presentation rather than verification.
That is where most of the thread goes, and it is about process rather than this tool. Commenters argue that bolting more AI review onto huge diffs solves the wrong problem, and describe shipping fewer features as quality declines.
They are hidden by default, which is the whole design and also its risk. The thread's substantive complaint is about dropped quality gates, so an unreviewed middle tier is exactly the failure mode people are already arguing about.
Commenters argued that bolting more AI onto a broken process misses the point: if you regularly generate PRs with 230 changed files, the process is the problem, and an LLM that produced the change is also capable of splitting it up.
One said code quality at work is regressing and they ship fewer product features than before with AI. Another described agents committing broken code and stacking micro-fixes on top, still broken.
A commenter asked what is revolutionary about Jev, calling it a generic classifier like the random forests and logistic regressions of 15 years ago and questioning how its accuracy could beat a custom model.
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Hacker News: Jev classifies agent PR hunks as P0, P1, or P2 so reviewers see P0 first.
namanbhulawat47 pointsJev Based Code ReviewRead the thread on Hacker NewsHacker News: Thread on Selmar's Jev code-review calibration notes and ordering.py comparisons.
Lectem2 pointsCalibrating Jev as a Code ReviewerRead the thread on Hacker NewsX: Magic Jev Ball for code review
X: jev-review: a local-first score loop for coding agents
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