{
  "apiVersion": "v1",
  "topic": {
    "id": "ai-review-cost",
    "title": "What does an AI code review cost?",
    "group": "Reviewing agent code",
    "summary": "The price of one AI review of a pull request, what drives it up, and what organizations did to bring it down.",
    "passages": 16,
    "url": "https://the-ai-record.com/topics/ai-review-cost",
    "json": "https://the-ai-record.com/api/v1/topics/ai-review-cost.json"
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  "passages": [
    {
      "id": "cloudflare-code-quality-high-effort-average-review-2026",
      "text": "With code quality at high effort, the average review now costs just $0.77, down 68% from the $2.43 it averaged over our two most expensive weeks before we started.",
      "context": null,
      "speaker": "Ryan Skidmore",
      "speakerId": "ryan-skidmore",
      "speakerUrl": "https://the-ai-record.com/people/ryan-skidmore",
      "speakerLevel": "practitioner",
      "role": "Author of Cloudflare's \"Orchestrating AI Code Review at scale\" blog post",
      "voice": "person",
      "organization": "Cloudflare",
      "organizationId": "cloudflare",
      "organizationUrl": "https://the-ai-record.com/organizations/cloudflare",
      "aiVendor": true,
      "work": {
        "title": "Cutting our inference bill by 68% by being obsessive about optimization",
        "type": "post",
        "date": "2026-10-19",
        "publisher": "Cloudflare blog",
        "url": "https://blog.cloudflare.com/obsessive-inference-optimization/"
      },
      "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": "2026-11-07"
      },
      "topics": [
        "ai-review-cost",
        "controlling-ai-spend"
      ],
      "functions": [
        "engineering"
      ],
      "figures": [
        {
          "metric": "cost-per-review",
          "value": 0.77,
          "unit": "usd",
          "period": "after mid-September to early October 2026 changes",
          "definition": "Average cost of one AI code review, code quality reviewer at high effort",
          "level": "n/a"
        },
        {
          "metric": "cost-per-review-reduction",
          "value": 0.68,
          "unit": "share",
          "period": "versus the two most expensive weeks before the work",
          "definition": "Fall in average cost per AI code review (from $2.43)",
          "level": "n/a"
        }
      ],
      "url": "https://the-ai-record.com/passages/cloudflare-code-quality-high-effort-average-review-2026",
      "json": "https://the-ai-record.com/api/v1/passages/cloudflare-code-quality-high-effort-average-review-2026.json"
    },
    {
      "id": "coval-roster-brought-median-cost-per-review-2026",
      "text": "In its first week in production the roster brought the median cost per review from about thirty cents to eleven while publishing at roughly the same rate.",
      "context": null,
      "speaker": "Dana Dzik",
      "speakerId": "dana-dzik",
      "speakerUrl": "https://the-ai-record.com/people/dana-dzik",
      "speakerLevel": "practitioner",
      "role": "Engineer, Coval (author of the Coval blog post on its code reviewer)",
      "voice": "person",
      "organization": "Coval",
      "organizationId": "coval",
      "organizationUrl": "https://the-ai-record.com/organizations/coval",
      "aiVendor": true,
      "work": {
        "title": "Notes on Building a Code Reviewer",
        "type": "post",
        "date": "2026-09-10",
        "publisher": "Coval blog",
        "locator": "The roster",
        "url": "https://www.coval.ai/blog/how-we-built-our-code-reviewer/"
      },
      "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": "2026-11-07"
      },
      "topics": [
        "ai-review-cost",
        "code-review"
      ],
      "functions": [
        "engineering"
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      "figures": [
        {
          "metric": "median-review-cost",
          "value": 0.11,
          "unit": "usd",
          "period": "first week of the roster in production",
          "definition": "Median model cost per automated code review, down from about $0.30",
          "level": "human-approves"
        }
      ],
      "url": "https://the-ai-record.com/passages/coval-roster-brought-median-cost-per-review-2026",
      "json": "https://the-ai-record.com/api/v1/passages/coval-roster-brought-median-cost-per-review-2026.json"
    },
    {
      "id": "sentry-security-scanning-five-dollars-a-pr-explicit-decision-worth-it-2026",
      "text": "So the concrete example here is we do security scanning after on our PRs in local and after our PRs even land because they will always find some things that are real that we have overlooked. And they sort of beat humans on the … code review. And it's expensive. It … us, I think like five bucks a PR or something like that to run all the checks that we want. But that's where we made an explicit decision that it's worth it.",
      "context": "Pstrucha is answering the moderator's question: 'when does a loop pay for itself, and how often is this actually the case?'",
      "speaker": "Greg Pstrucha",
      "speakerId": "greg-pstrucha",
      "speakerUrl": "https://the-ai-record.com/people/greg-pstrucha",
      "speakerLevel": "practitioner",
      "role": "Developer, Sentry",
      "voice": "person",
      "organization": "Sentry",
      "organizationId": "sentry",
      "organizationUrl": "https://the-ai-record.com/organizations/sentry",
      "aiVendor": true,
      "work": {
        "title": "The Great Loops Debate",
        "type": "talk",
        "date": "2026-07-17",
        "publisher": "AI Engineer (YouTube)",
        "locator": "36:59",
        "url": "https://www.youtube.com/watch?v=c35YoMdnI78"
      },
      "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",
        "security",
        "ai-cost-and-spend",
        "ai-review-quality",
        "ai-review-cost"
      ],
      "functions": [
        "engineering",
        "security"
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      "figures": [
        {
          "metric": "cost-per-pr-checks",
          "value": 5,
          "unit": "usd",
          "period": "per pull request, as the speaker states it",
          "definition": "cost of running all the security scans he wants on one pull request, 'I think like five bucks a PR or something like that'",
          "level": "unclear"
        }
      ],
      "url": "https://the-ai-record.com/passages/sentry-security-scanning-five-dollars-a-pr-explicit-decision-worth-it-2026",
      "json": "https://the-ai-record.com/api/v1/passages/sentry-security-scanning-five-dollars-a-pr-explicit-decision-worth-it-2026.json"
    },
    {
      "id": "rewind-reviews-average-73-cents-per-pr-twelve-dollars-2026",
      "text": "For the curious: reviews average around $0.73 per PR, with significant variance. Small dependency bumps cost cents; large multi-file PRs with many substantive findings can push past twelve dollars.",
      "context": null,
      "speaker": "Dave North",
      "speakerId": "dave-north",
      "speakerUrl": "https://the-ai-record.com/people/dave-north",
      "speakerLevel": "leader",
      "role": "Leads the technical operations group",
      "voice": "person",
      "organization": "Rewind",
      "organizationId": "rewind",
      "organizationUrl": "https://the-ai-record.com/organizations/rewind",
      "aiVendor": false,
      "work": {
        "title": "Review is the bottleneck now: How we let AI approve pull requests (safely)",
        "type": "post",
        "date": "2026-06-01",
        "publisher": "Rewind blog",
        "locator": "The Death Star",
        "url": "https://rewind.com/blog/ai-approve-pull-requests-safely/"
      },
      "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": [
        "ai-cost-and-spend",
        "code-review",
        "ai-review-cost"
      ],
      "functions": [
        "engineering"
      ],
      "figures": [
        {
          "metric": "avg-cost-per-pr-review",
          "value": 0.73,
          "unit": "usd",
          "definition": "Average token spend per AI review of a pull request (\"around\")",
          "level": "n/a"
        }
      ],
      "url": "https://the-ai-record.com/passages/rewind-reviews-average-73-cents-per-pr-twelve-dollars-2026",
      "json": "https://the-ai-record.com/api/v1/passages/rewind-reviews-average-73-cents-per-pr-twelve-dollars-2026.json"
    },
    {
      "id": "cloudflare-cost-side-average-review-costs-1-19-2026",
      "text": "On the cost side, the average review costs $1.19 and the median is $0.98. The distribution has a long tail of expensive reviews – massive refactors that trigger full-tier orchestration. The P99 review costs $4.45, which means 99% of reviews come in under five dollars.",
      "context": null,
      "speaker": "Ryan Skidmore",
      "speakerId": "ryan-skidmore",
      "speakerUrl": "https://the-ai-record.com/people/ryan-skidmore",
      "speakerLevel": "practitioner",
      "role": "Author of Cloudflare's \"Orchestrating AI Code Review at scale\" blog post",
      "voice": "person",
      "organization": "Cloudflare",
      "organizationId": "cloudflare",
      "organizationUrl": "https://the-ai-record.com/organizations/cloudflare",
      "aiVendor": true,
      "work": {
        "title": "Orchestrating AI Code Review at scale",
        "type": "post",
        "date": "2026-04-20",
        "publisher": "Cloudflare blog",
        "locator": "Show me the numbers! / The overview",
        "url": "https://blog.cloudflare.com/ai-code-review"
      },
      "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": [
        "ai-cost-and-spend",
        "code-review",
        "ai-review-cost"
      ],
      "functions": [
        "engineering"
      ],
      "figures": [
        {
          "metric": "cost-per-review",
          "value": 1.19,
          "unit": "usd",
          "period": "average, March 10 to April 9, 2026",
          "definition": "Average cost of one AI review run; median $0.98, P99 $4.45",
          "level": "n/a"
        }
      ],
      "url": "https://the-ai-record.com/passages/cloudflare-cost-side-average-review-costs-1-19-2026",
      "json": "https://the-ai-record.com/api/v1/passages/cloudflare-cost-side-average-review-costs-1-19-2026.json"
    },
    {
      "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,
      "speakerLevel": 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"
        }
      ],
      "url": "https://the-ai-record.com/passages/juspay-70-reduction-trivial-review-comments-40-faster-turnaround-2026",
      "json": "https://the-ai-record.com/api/v1/passages/juspay-70-reduction-trivial-review-comments-40-faster-turnaround-2026.json"
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    {
      "id": "juspay-multi-model-strategy-cheaper-models-simple-checks-cut-costs-2026",
      "text": "Multi-model strategy works: Using cheaper models for simple checks and expensive ones for complex reasoning cut costs by 80%",
      "context": null,
      "speaker": null,
      "speakerId": null,
      "speakerUrl": null,
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      "voice": "organization",
      "organization": "Juspay",
      "organizationId": "juspay",
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      "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 > Key Lessons",
        "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"
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        "code-review",
        "ai-review-cost",
        "controlling-ai-spend"
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          "metric": "cost-reduction-multi-model",
          "value": 0.8,
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          "definition": "Cost cut by routing simple checks to cheaper models and complex reasoning to expensive ones",
          "level": "n/a"
        }
      ],
      "url": "https://the-ai-record.com/passages/juspay-multi-model-strategy-cheaper-models-simple-checks-cut-costs-2026",
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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.",
      "context": null,
      "speaker": null,
      "speakerId": null,
      "speakerUrl": null,
      "speakerLevel": null,
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      "voice": "organization",
      "organization": "Anthropic",
      "organizationId": "anthropic",
      "organizationUrl": "https://the-ai-record.com/organizations/anthropic",
      "aiVendor": true,
      "work": {
        "title": "Bringing Code Review to Claude Code",
        "type": "post",
        "date": "2026-03-09",
        "publisher": "claude.com (Anthropic)",
        "locator": "Cost and control",
        "url": "https://claude.com/resources/articles/code-review"
      },
      "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": "2026-11-07"
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      "figures": [
        {
          "metric": "cost-per-review",
          "value": 20,
          "unit": "usd",
          "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"
        }
      ],
      "url": "https://the-ai-record.com/passages/anthropic-code-review-billed-token-usage-15-25-per-review-2026",
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    },
    {
      "id": "coval-configuration-catches-most-what-our-2026",
      "text": "The configuration that catches the most of what our human reviewers catch is also the cheapest one we have run, and most of its budget goes to models that would be dismissed on sight as too weak for code review—which, individually, they are.",
      "context": null,
      "speaker": "Dana Dzik",
      "speakerId": "dana-dzik",
      "speakerUrl": "https://the-ai-record.com/people/dana-dzik",
      "speakerLevel": "practitioner",
      "role": "Engineer, Coval (author of the Coval blog post on its code reviewer)",
      "voice": "person",
      "organization": "Coval",
      "organizationId": "coval",
      "organizationUrl": "https://the-ai-record.com/organizations/coval",
      "aiVendor": true,
      "work": {
        "title": "Notes on Building a Code Reviewer",
        "type": "post",
        "date": "2026-09-10",
        "publisher": "Coval blog",
        "locator": "Where it goes",
        "url": "https://www.coval.ai/blog/how-we-built-our-code-reviewer/"
      },
      "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": "2026-11-07"
      },
      "topics": [
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        "ai-review-quality"
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      "functions": [
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      "url": "https://the-ai-record.com/passages/coval-configuration-catches-most-what-our-2026",
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    {
      "id": "uber-we-saw-against-like-very-naive-2026",
      "text": "we saw that against like a very naive implementation, our costs were down by 60%, and our quality and our accuracy was up by around 70%.",
      "context": "Ameya Ketkar is summarizing the effect of the observability and evaluation work on uReview, Uber's code-review system.",
      "speaker": "Ameya Ketkar",
      "speakerId": "ameya-ketkar",
      "speakerUrl": "https://the-ai-record.com/people/ameya-ketkar",
      "speakerLevel": "practitioner",
      "role": "Speaker, AI Engineer World's Fair 2026 (job title not stated)",
      "voice": "person",
      "organization": "Uber",
      "organizationId": "uber",
      "organizationUrl": "https://the-ai-record.com/organizations/uber",
      "aiVendor": false,
      "work": {
        "title": "Building uReview, Uber's Multi-Agent Code Review Engine (talk, AI Engineer World's Fair 2026)",
        "type": "talk",
        "date": "2026-08-28",
        "publisher": "AI Engineer (YouTube)",
        "locator": "10:50",
        "url": "https://www.youtube.com/watch?v=EL123UNokkI"
      },
      "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": "2026-11-03"
      },
      "topics": [
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        "ai-cost-and-spend",
        "measuring-impact",
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        "ai-evals"
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      "functions": [
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      "figures": [
        {
          "metric": "ai-review-cost-change",
          "value": -60,
          "unit": "percent",
          "period": "against a naive first implementation",
          "definition": "cost of running uReview, compared with a very naive implementation, as Ketkar describes it",
          "level": "n/a"
        },
        {
          "metric": "ai-review-quality-change",
          "value": 70,
          "unit": "percent",
          "period": "against a naive first implementation",
          "definition": "quality and accuracy of uReview, compared with a very naive implementation, as Ketkar describes it; the talk does not say how this is measured",
          "level": "n/a"
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      ],
      "url": "https://the-ai-record.com/passages/uber-we-saw-against-like-very-naive-2026",
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    {
      "id": "ionix-dropped-rovo-paying-more-than-results-2026",
      "text": "The first was cost. We were paying more for it than the results justified, and the obvious replacements wanted the same kind of money.",
      "context": "The post's author explains why Ionix dropped Rovo, an AI review tool, before building its own reviewer; “it” in the passage is Rovo.",
      "speaker": "Arthur Vinberg",
      "speakerId": "arthur-vinberg",
      "speakerUrl": "https://the-ai-record.com/people/arthur-vinberg",
      "speakerLevel": "leader",
      "role": "Head of DevOps & IT",
      "voice": "person",
      "organization": "Ionix",
      "organizationId": "ionix",
      "organizationUrl": "https://the-ai-record.com/organizations/ionix",
      "aiVendor": false,
      "work": {
        "title": "We built an AI PR reviewer. The hard part was teaching it to say nothing.",
        "type": "post",
        "date": "2026-08-13",
        "publisher": "Ionix blog",
        "locator": "Why we built it instead of buying it",
        "url": "https://www.ionix.io/blog/we-built-an-ai-pr-reviewer/"
      },
      "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": "2026-11-08"
      },
      "topics": [
        "ai-review-cost",
        "code-review"
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      "url": "https://the-ai-record.com/passages/ionix-dropped-rovo-paying-more-than-results-2026",
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    },
    {
      "id": "madewithlove-40-month-more-expensive-end-tooling-spectrum-2025",
      "text": "At $40/month, it is on the more expensive end of the tooling spectrum, especially when compared to something like GitHub Copilot, which costs $19/month per user.",
      "context": null,
      "speaker": "Peter Eysermans",
      "speakerId": "peter-eysermans",
      "speakerUrl": "https://the-ai-record.com/people/peter-eysermans",
      "speakerLevel": "practitioner",
      "role": "Author, madewithlove blog (role not stated on the page)",
      "voice": "person",
      "organization": "madewithlove",
      "organizationId": "madewithlove",
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      "work": {
        "title": "Automatic pull request reviewing with Cursor's Bugbot",
        "type": "post",
        "date": "2025-09-02",
        "publisher": "madewithlove blog",
        "locator": "What does it cost?",
        "url": "https://madewithlove.com/blog/automatic-pull-request-reviewing-with-cursors-bugbot"
      },
      "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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      "topics": [
        "ai-review-cost"
      ],
      "functions": [
        "engineering"
      ],
      "figures": [
        {
          "metric": "ai-reviewer-price",
          "value": 40,
          "unit": "usd",
          "period": "as of July 24, 2025",
          "definition": "Bugbot subscription price per month as the author states it; compared with $19 per user per month for GitHub Copilot",
          "level": "n/a"
        }
      ],
      "url": "https://the-ai-record.com/passages/madewithlove-40-month-more-expensive-end-tooling-spectrum-2025",
      "json": "https://the-ai-record.com/api/v1/passages/madewithlove-40-month-more-expensive-end-tooling-spectrum-2025.json"
    },
    {
      "id": "cloudflare-medium-effort-did-lose-real-findings-2026",
      "text": "Medium effort did lose real findings. In the randomized split, code quality at medium led to roughly a quarter as many acted-on findings as at high, which is why we're moving it to high.",
      "context": null,
      "speaker": "Ryan Skidmore",
      "speakerId": "ryan-skidmore",
      "speakerUrl": "https://the-ai-record.com/people/ryan-skidmore",
      "speakerLevel": "practitioner",
      "role": "Author of Cloudflare's \"Orchestrating AI Code Review at scale\" blog post",
      "voice": "person",
      "organization": "Cloudflare",
      "organizationId": "cloudflare",
      "organizationUrl": "https://the-ai-record.com/organizations/cloudflare",
      "aiVendor": true,
      "work": {
        "title": "Cutting our inference bill by 68% by being obsessive about optimization",
        "type": "post",
        "date": "2026-10-19",
        "publisher": "Cloudflare blog",
        "locator": "Review quality",
        "url": "https://blog.cloudflare.com/obsessive-inference-optimization/"
      },
      "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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    {
      "id": "anthropic-one-pr-fifty-review-rounds-overnight-2026",
      "text": "Review has to converge. An agent author and an agent reviewer can keep each other busy indefinitely. One CLI PR went through more than fifty rounds of review and fixes overnight before its author stopped it. When we ran git blame on what the reviewer kept flagging, about 59% of it was code that had been there since the reviewer's first pass.",
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      "speaker": null,
      "speakerId": null,
      "speakerUrl": null,
      "speakerLevel": null,
      "role": null,
      "voice": "organization",
      "organization": "Anthropic",
      "organizationId": "anthropic",
      "organizationUrl": "https://the-ai-record.com/organizations/anthropic",
      "aiVendor": true,
      "work": {
        "title": "How the Claude Code team does code review",
        "type": "post",
        "date": "2026-10-15",
        "publisher": "claude.dev Blog (Anthropic)",
        "locator": "How we make the reviewer better",
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      },
      "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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        "ai-review-cost"
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      "functions": [
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      ],
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        {
          "metric": "review-rounds-single-pr",
          "value": 50,
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          "period": "one night, one Claude Code CLI pull request",
          "definition": "Rounds of AI review and agent fixes on a single pull request before its author stopped it (\"more than fifty\"; lower bound)",
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        },
        {
          "metric": "repeat-findings-share",
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          "definition": "Share of what the AI reviewer kept flagging that was code present since its first pass, found with git blame (\"about 59%\")",
          "level": "n/a"
        }
      ],
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    },
    {
      "id": "anthropic-prs-passing-after-one-review-round-65-to-78-2026",
      "text": "Before and after the convergence work: pull requests passing after one review and fix round rose from 65% to 78%; pull requests needing five or more rounds fell from 8.9% to 1.5%; mean reviews to pass fell from 2.08 to 1.32.",
      "context": "The text description of a chart in the post comparing internal pull requests before and after changes to re-review, which the post lists as a cap of three rounds, re-reviewing only the new diff after the first few passes, flagging the class of bug, and not repeating findings already posted.",
      "speaker": null,
      "speakerId": null,
      "speakerUrl": null,
      "speakerLevel": null,
      "role": null,
      "voice": "organization",
      "organization": "Anthropic",
      "organizationId": "anthropic",
      "organizationUrl": "https://the-ai-record.com/organizations/anthropic",
      "aiVendor": true,
      "work": {
        "title": "How the Claude Code team does code review",
        "type": "post",
        "date": "2026-10-15",
        "publisher": "claude.dev Blog (Anthropic)",
        "locator": "How we make the reviewer better: Figure D, Review that converges (the chart's text description)",
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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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      },
      "topics": [
        "ai-review-cost",
        "ai-review-quality"
      ],
      "functions": [
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      ],
      "figures": [
        {
          "metric": "prs-pass-after-one-review-round",
          "value": 0.78,
          "unit": "share",
          "period": "internal pull requests, after the convergence changes (0.65 before)",
          "definition": "Share of pull requests passing after one AI review and fix round",
          "level": "unclear"
        },
        {
          "metric": "prs-needing-five-plus-review-rounds",
          "value": 0.015,
          "unit": "share",
          "period": "internal pull requests, after the convergence changes (0.089 before)",
          "definition": "Share of pull requests needing five or more review rounds",
          "level": "unclear"
        },
        {
          "metric": "avg-review-iterations",
          "value": 1.32,
          "unit": "iterations per PR",
          "period": "internal pull requests, after the convergence changes (2.08 before)",
          "definition": "Mean reviews to pass",
          "level": "unclear"
        }
      ],
      "url": "https://the-ai-record.com/passages/anthropic-prs-passing-after-one-review-round-65-to-78-2026",
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    },
    {
      "id": "anthropic-review-noise-costs-more-when-author-agent-2026",
      "text": "Noise costs more when the author is an agent. A person can wave off a nit in seconds. An agent fixes it, which means another commit and another round of review.",
      "context": null,
      "speaker": null,
      "speakerId": null,
      "speakerUrl": null,
      "speakerLevel": null,
      "role": null,
      "voice": "organization",
      "organization": "Anthropic",
      "organizationId": "anthropic",
      "organizationUrl": "https://the-ai-record.com/organizations/anthropic",
      "aiVendor": true,
      "work": {
        "title": "How the Claude Code team does code review",
        "type": "post",
        "date": "2026-10-15",
        "publisher": "claude.dev Blog (Anthropic)",
        "locator": "How we make the reviewer better",
        "url": "https://claude.dev/blog/solving-code-review-at-anthropic/"
      },
      "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": "2026-11-07"
      },
      "topics": [
        "ai-review-quality",
        "ai-review-cost"
      ],
      "functions": [
        "engineering"
      ],
      "figures": [],
      "url": "https://the-ai-record.com/passages/anthropic-review-noise-costs-more-when-author-agent-2026",
      "json": "https://the-ai-record.com/api/v1/passages/anthropic-review-noise-costs-more-when-author-agent-2026.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."
  ]
}