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      "id": "anthropic-run-code-review-nearly-every-pr-16-54-2026",
      "text": "We run Code Review on nearly every PR at Anthropic. Before, 16% of PRs got substantive review comments. Now 54% do. It won't approve PRs — that's still a human call — but it closes the gap so reviewers can actually cover what's shipping.",
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      "id": "anthropic-separate-agents-vote-on-each-review-finding-2026",
      "text": "Findings get verified by other agents before humans review them. Several agents look for bugs at the same time. Then a separate group votes on each finding, and it only gets posted if enough of them agree it's real. Findings that are only about style, diagnostics, or cleanup get dropped. We A/B tested those filters on our own PRs before keeping them.",
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      "work": {
        "title": "How the Claude Code team does code review",
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        "date": "2026-10-15",
        "publisher": "claude.dev Blog (Anthropic)",
        "locator": "Layer by layer: 2. AI review on every pull request",
        "url": "https://claude.dev/blog/solving-code-review-at-anthropic/"
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      "grade": "B",
      "gradeMeaning": "The organization's own post, paper or talk.",
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        "status": "verified",
        "meaning": "An independent second reader re-fetched the source and confirmed the wording.",
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    {
      "id": "anthropic-code-review-billed-token-usage-15-25-per-review-2026",
      "text": "Reviews are billed on token usage and generally average $15–25, scaling with PR size and complexity.",
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        "title": "Bringing Code Review to Claude Code",
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        "date": "2026-03-09",
        "publisher": "claude.com (Anthropic)",
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        "status": "verified",
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        {
          "metric": "cost-per-review",
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          "period": "March 2026",
          "definition": "typical price of one Code Review run to a customer, midpoint of the stated $15 to $25 range; a vendor price, not Anthropic's internal cost",
          "level": "unclear"
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      ],
      "url": "https://the-ai-record.com/passages/anthropic-code-review-billed-token-usage-15-25-per-review-2026",
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    {
      "id": "uber-ureview-today-analyzes-over-90-weekly-65-2025-2",
      "text": "uReview today analyzes over 90% of the weekly ~65,000 diffs (equivalent of pull requests) landed at Uber. Engineers who interact with the tool mark 75% of its comments as useful",
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      "speaker": "Sonal Mahajan",
      "speakerId": "sonal-mahajan",
      "speakerUrl": "https://the-ai-record.com/people/sonal-mahajan",
      "speakerLevel": "practitioner",
      "role": "Staff Engineer, Programming Systems team",
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      "organization": "Uber",
      "organizationId": "uber",
      "organizationUrl": "https://the-ai-record.com/organizations/uber",
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      "work": {
        "title": "uReview: Scalable, Trustworthy GenAI for Code Review at Uber",
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        "date": "2025-08-12",
        "publisher": "Uber engineering blog",
        "url": "https://www.uber.com/us/en/blog/ureview/"
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      "grade": "B",
      "gradeMeaning": "The organization's own post, paper or talk.",
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        "status": "verified",
        "meaning": "An independent second reader re-fetched the source and confirmed the wording.",
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        "ai-review-quality"
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    {
      "id": "ona-already-code-review-automation-running-every-pr-2026",
      "text": "We already had Ona's code review automation running on every PR. The agent reviewed diffs, ran the code in a full environment, cross-referenced tickets, and left inline comments with an 88% acceptance rate and a 50% reduction in time spent on pull requests.",
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      "speaker": null,
      "speakerId": null,
      "speakerUrl": null,
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      "voice": "organization",
      "organization": "Ona",
      "organizationId": "ona",
      "organizationUrl": "https://the-ai-record.com/organizations/ona",
      "aiVendor": true,
      "work": {
        "title": "How auto-approving low-risk PRs with AI cut our lead time by 74%",
        "type": "post",
        "date": "2026-04-09",
        "publisher": "Ona blog",
        "locator": "The experiment",
        "url": "https://ona.com/stories/auto-approving-low-risk-prs"
      },
      "grade": "B",
      "gradeMeaning": "The organization's own post, paper or talk.",
      "verification": {
        "status": "verified",
        "meaning": "An independent second reader re-fetched the source and confirmed the wording.",
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      },
      "topics": [
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        "measuring-impact",
        "ai-review-quality"
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      "figures": [
        {
          "metric": "review-comment-acceptance-rate",
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          "period": "before auto-approval, 2026",
          "definition": "Share of the agent's inline review comments that human reviewers accepted",
          "level": "assisted"
        },
        {
          "metric": "time-spent-on-pull-requests-reduction",
          "value": 0.5,
          "unit": "share",
          "period": "before auto-approval, 2026",
          "definition": "Reduction in time spent on pull requests, as the post states it",
          "level": "assisted"
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      ],
      "url": "https://the-ai-record.com/passages/ona-already-code-review-automation-running-every-pr-2026",
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    },
    {
      "id": "openai-agentic-code-reviews-look-code-changes-series-2026",
      "text": "We're now seeing agentic code reviews that look at code changes through a series of different lenses. In the past, it would have been impractical for a cloud infrastructure engineer and a security engineer to review every single code change. With agents, that becomes possible.",
      "context": null,
      "speaker": "Venkat Venkataramani",
      "speakerId": "venkat-venkataramani",
      "speakerUrl": "https://the-ai-record.com/people/venkat-venkataramani",
      "speakerLevel": "leader",
      "role": "VP of Engineering, Applied Infra",
      "voice": "person",
      "organization": "OpenAI",
      "organizationId": "openai",
      "organizationUrl": "https://the-ai-record.com/organizations/openai",
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      "work": {
        "title": "Inside OpenAI's agentic software factory",
        "type": "press",
        "date": "2026-09-15",
        "publisher": "The Pragmatic Engineer",
        "locator": "2. Death of the IDE & pull requests",
        "url": "https://newsletter.pragmaticengineer.com/p/openai-software-factory"
      },
      "grade": "C",
      "gradeMeaning": "An interview or press quote.",
      "verification": {
        "status": "verified",
        "meaning": "An independent second reader re-fetched the source and confirmed the wording.",
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      },
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        "code-review",
        "autonomy-and-oversight"
      ],
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        "engineering",
        "security"
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      "url": "https://the-ai-record.com/passages/openai-agentic-code-reviews-look-code-changes-series-2026",
      "json": "https://the-ai-record.com/api/v1/passages/openai-agentic-code-reviews-look-code-changes-series-2026.json"
    },
    {
      "id": "cognition-bottleneck-shifted-writing-code-reviewing-devin-review-2026",
      "text": "As we ship more code with agents, the bottleneck shifted from writing code to reviewing it. Devin Review turns large, complex GitHub PRs into intuitively organized diffs and precise explanations. We use it for every PR now.",
      "context": null,
      "speaker": null,
      "speakerId": null,
      "speakerUrl": null,
      "speakerLevel": null,
      "role": null,
      "voice": "organization",
      "organization": "Cognition",
      "organizationId": "cognition",
      "organizationUrl": "https://the-ai-record.com/organizations/cognition",
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      "work": {
        "title": "How Cognition Uses Devin to Build Devin",
        "type": "post",
        "date": "2026-02-27",
        "publisher": "Cognition",
        "locator": "Automated Code Review",
        "url": "https://cognition.com/blog/how-cognition-uses-devin-to-build-devin"
      },
      "grade": "B",
      "gradeMeaning": "The organization's own post, paper or talk.",
      "verification": {
        "status": "verified",
        "meaning": "An independent second reader re-fetched the source and confirmed the wording.",
        "reviewedOn": "2026-11-04"
      },
      "topics": [
        "code-review",
        "coding-agents",
        "bottleneck-after-agents"
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      "functions": [
        "engineering"
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      "figures": [],
      "url": "https://the-ai-record.com/passages/cognition-bottleneck-shifted-writing-code-reviewing-devin-review-2026",
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    },
    {
      "id": "microsoft-ai-assistant-started-internal-experiment-scaled-2025",
      "text": "This AI Assistant started as an internal experiment and now has scaled to support over 90% of PRs across the company impacting more than 600K pull requests per month.",
      "context": null,
      "speaker": "Sneha Tuli",
      "speakerId": "sneha-tuli",
      "speakerUrl": "https://the-ai-record.com/people/sneha-tuli",
      "speakerLevel": "leader",
      "role": "Principal Product Manager",
      "voice": "person",
      "organization": "Microsoft",
      "organizationId": "microsoft",
      "organizationUrl": "https://the-ai-record.com/organizations/microsoft",
      "aiVendor": true,
      "work": {
        "title": "Enhancing Code Quality at Scale with AI-Powered Code Reviews",
        "type": "post",
        "date": "2025-07-14",
        "publisher": "Engineering@Microsoft blog",
        "url": "https://devblogs.microsoft.com/engineering-at-microsoft/enhancing-code-quality-at-scale-with-ai-powered-code-reviews/"
      },
      "grade": "B",
      "gradeMeaning": "The organization's own post, paper or talk.",
      "verification": {
        "status": "verified",
        "meaning": "An independent second reader re-fetched the source and confirmed the wording.",
        "reviewedOn": "2026-11-04"
      },
      "topics": [
        "code-review",
        "adoption-and-usage"
      ],
      "functions": [
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      ],
      "figures": [
        {
          "metric": "prs-covered-share",
          "value": 0.9,
          "unit": "share",
          "period": "as of July 2025 (post date)",
          "definition": "Share of pull requests across the company the AI code review assistant supports; stated as 'over 90%'",
          "level": "assisted"
        },
        {
          "metric": "prs-per-month",
          "value": 600000,
          "unit": "pull requests per month",
          "period": "as of July 2025 (post date)",
          "definition": "Pull requests per month affected by the AI code review assistant; stated as 'more than 600K'",
          "level": "assisted"
        }
      ],
      "url": "https://the-ai-record.com/passages/microsoft-ai-assistant-started-internal-experiment-scaled-2025",
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    },
    {
      "id": "juspay-70-reduction-trivial-review-comments-40-faster-turnaround-2026",
      "text": "After 6 months in production: 70% reduction in trivial review comments (style, formatting) 40% faster PR turnaround time Zero security issues missed in production (caught during review) $0.12 average cost per PR review (using cost-optimized model routing)",
      "context": "List markers dropped; the four bullets under \"After 6 months in production:\" are joined with spaces.",
      "speaker": null,
      "speakerId": null,
      "speakerUrl": null,
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      "voice": "organization",
      "organization": "Juspay",
      "organizationId": "juspay",
      "organizationUrl": "https://the-ai-record.com/organizations/juspay",
      "aiVendor": true,
      "work": {
        "title": "How We Built an AI Code Reviewer with NeuroLink and Bitbucket",
        "type": "post",
        "date": "2026-04-06",
        "publisher": "dev.to (NeuroLink AI organization account, Juspay)",
        "locator": "Results & Lessons Learned",
        "url": "https://dev.to/neurolink/how-we-built-an-ai-code-reviewer-with-neurolink-and-bitbucket-3io9"
      },
      "grade": "B",
      "gradeMeaning": "The organization's own post, paper or talk.",
      "verification": {
        "status": "verified",
        "meaning": "An independent second reader re-fetched the source and confirmed the wording.",
        "reviewedOn": "2026-11-04"
      },
      "topics": [
        "code-review",
        "measuring-impact",
        "ai-cost-and-spend",
        "ai-review-cost"
      ],
      "functions": [
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      ],
      "figures": [
        {
          "metric": "reduction-trivial-review-comments",
          "value": 0.7,
          "unit": "share",
          "period": "6 months in production",
          "definition": "Reduction in trivial review comments (style, formatting) from the Yama AI reviewer",
          "level": "assisted"
        },
        {
          "metric": "faster-pr-turnaround",
          "value": 0.4,
          "unit": "share",
          "period": "6 months in production",
          "definition": "Faster PR turnaround time",
          "level": "assisted"
        },
        {
          "metric": "avg-cost-per-pr-review",
          "value": 0.12,
          "unit": "usd",
          "period": "6 months in production",
          "definition": "Average cost per PR review with cost-optimized model routing",
          "level": "assisted"
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      "id": "microsoft-5000-repositories-onboarded-ai-code-reviewer-2025",
      "text": "Per early experiments and data science studies, 5000 repositories onboarded to AI code reviewer observed 10 – 20% median PR completion time improvements.",
      "context": null,
      "speaker": "Sneha Tuli",
      "speakerId": "sneha-tuli",
      "speakerUrl": "https://the-ai-record.com/people/sneha-tuli",
      "speakerLevel": "leader",
      "role": "Principal Product Manager",
      "voice": "person",
      "organization": "Microsoft",
      "organizationId": "microsoft",
      "organizationUrl": "https://the-ai-record.com/organizations/microsoft",
      "aiVendor": true,
      "work": {
        "title": "Enhancing Code Quality at Scale with AI-Powered Code Reviews",
        "type": "post",
        "date": "2025-07-14",
        "publisher": "Engineering@Microsoft blog",
        "locator": "Impact on quality and velocity",
        "url": "https://devblogs.microsoft.com/engineering-at-microsoft/enhancing-code-quality-at-scale-with-ai-powered-code-reviews/"
      },
      "grade": "B",
      "gradeMeaning": "The organization's own post, paper or talk.",
      "verification": {
        "status": "verified",
        "meaning": "An independent second reader re-fetched the source and confirmed the wording.",
        "reviewedOn": "2026-11-04"
      },
      "topics": [
        "code-review",
        "developer-productivity",
        "measuring-impact"
      ],
      "functions": [
        "engineering"
      ],
      "figures": [
        {
          "metric": "median-pr-completion-time-improvement-low",
          "value": 0.1,
          "unit": "share",
          "period": "early experiments, 5000 onboarded repositories",
          "definition": "Low end of the stated range of median PR completion time improvement",
          "level": "assisted"
        },
        {
          "metric": "median-pr-completion-time-improvement-high",
          "value": 0.2,
          "unit": "share",
          "period": "early experiments, 5000 onboarded repositories",
          "definition": "High end of the stated range of median PR completion time improvement",
          "level": "assisted"
        }
      ],
      "url": "https://the-ai-record.com/passages/microsoft-5000-repositories-onboarded-ai-code-reviewer-2025",
      "json": "https://the-ai-record.com/api/v1/passages/microsoft-5000-repositories-onboarded-ai-code-reviewer-2025.json"
    }
  ],
  "topic": {
    "id": "code-review",
    "title": "How is AI used in code review?",
    "group": "Reviewing agent code",
    "summary": "AI that reviews code changes, finds problems before merge, or picks the human reviewer.",
    "passages": 110,
    "url": "https://the-ai-record.com/topics/code-review",
    "json": "https://the-ai-record.com/api/v1/topics/code-review.json"
  },
  "notice": [
    "Every passage is reproduced word for word from the cited source.",
    "Check the verification status: \"reported\" means not yet confirmed by an independent second reader.",
    "Organizations flagged aiVendor sell AI tools or services and have a reason to publish flattering numbers.",
    "An empty result means the archive holds nothing on it, not that nobody has said anything."
  ]
}