{
  "id": 11234133,
  "title": "One Correction Wave: A Stop Rule for AI-Assisted Review",
  "url": "https://urgent.news/2026/10/01/one-correction-wave-a-stop-rule-for-ai-assisted-review",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-01T16:45:00.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/qnbs/one-correction-wave-a-stop-rule-for-ai-assisted-review-56lf"
  },
  "original_language": "en",
  "account": "A coding agent reviews a pull request and makes changes, but the reviewer finds new issues each time, leading to a loop of corrections. This loop is not proof that AI review is ineffective; rather, it indicates that the team has not established a stopping rule for the review process. The team needs to define a clear process to determine when to stop making corrections and accept or reject the changes. A practical approach is to implement a \"one correction wave\" method, where reviewers collect all the findings, let the intended reviewers and required checks complete for the current revision, group duplicate comments, and distinguish actionable defects from questions or style preferences. The reviewer should then assign an owner, determine the consequence level, and validate the failure path before making any changes. The reviewer should also correct the issues coherently and make related sets of accepted fixes together instead of committing each bot suggestion separately. After making the corrections, the reviewer should re-run the evidence, run deterministic checks on the new head, and inspect the resulting diff. The final step is to decide whether to merge the changes, request a bounded correction, or stop with the remaining unknown issues. This process pattern helps make the loop observable and provides a natural point to end the review.",
  "summary": "A reviewer finds a bug. A coding agent fixes it. The fix triggers another review. The reviewer finds a style issue. The agent changes it. A new run notices a nearby concern. Soon the pull request has ten commits, three of them correcting earlier corrections, and nobody is sure which result is the one to review. That loop is not proof that AI review is useless. It is a sign that the team has not…",
  "key_points": [
    "Implement a \"one correction wave\" method to stop endless review loops",
    "Reviewer collects findings, groups duplicate comments, distinguishes defects",
    "After corrections, re-run evidence, deterministic checks, and inspect diff"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}