--- title: What are code reviews even for? | daily.dev description: AI coding tools are generating code faster than humans can review it — at Meta, lines of code per diff grew 106% and diffs per developer rose 51%, mostly from... canonical: https://daily.dev/posts/what-are-code-reviews-even-for--kzh6kkthn twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: What are code reviews even for? | daily.dev og:description: AI coding tools are generating code faster than humans can review it — at Meta, lines of code per diff grew 106% and diffs per developer rose 51%, mostly from... og:url: https://daily.dev/posts/what-are-code-reviews-even-for--kzh6kkthn og:image: https://api.daily.dev/og/posts/KZH6KKThN.png og:image:alt: What are code reviews even for? og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # What are code reviews even for? **[Software Engineering Research](https://daily.dev/sources/abinoda)** · 9 min read · 11 upvotes · 3 comments ## Summary AI coding tools are generating code faster than humans can review it — at Meta, lines of code per diff grew 106% and diffs per developer rose 51%, mostly from agentic AI. But the real problem predates AI: teams were already struggling with large PRs, poor change descriptions, and reviewer overload. Research shows code review was never just about defect detection; only 14% of review comments are defect-related. The rest serves knowledge transfer, shared ownership, and architectural understanding. Meta's RADAR system offers a model — automating low-risk diffs while routing higher-risk ones to humans, achieving a revert rate one-third of normal and a production incident rate one-fiftieth as high. The recommended approach: fix review fundamentals first (small PRs, meaningful descriptions, automated routine checks), then design AI assistance around human judgment rather than replacing it, and actively protect the knowledge-building function that human review provides. Automating away review risks accumulating 'cognitive and intent debt' — a growing gap between what a system does and what the team understands about why. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### How much did AI coding tools increase code review volume at Meta? Lines of code per human-landed diff increased by 106% over a year, and diffs per developer per month rose 51%, with more than 80% of that growth attributed to agentic AI. Meanwhile the share of diffs reviewed within 24 hours declined, leaving some large groups with thousands of pending reviews. _Teams scaling AI-generated code can compare notes on review bottlenecks and fixes through daily.dev._ ### What is Meta's RADAR system for code review? RADAR (Risk Aware Diff Auto Review) is Meta's system that automates review for a carefully selected subset of low-to-medium risk changes while routing higher-risk diffs to human reviewers, combining static analysis, machine learning, LLM-based review, and deterministic validation. It reviewed over 535,000 diffs, landed more than 331,000, cut revert rates to roughly a third of non-RADAR diffs, reduced production incident rates fiftyfold, and cut median time to close by more than 330%. _Engineers weighing automated code review tools track real-world results like RADAR's on daily.dev._ ### What percentage of code review comments are actually about finding defects? Only about 14% of review comments focus on defects, according to a landmark Microsoft study, even though most developers cite defect detection as their primary motivation for reviewing code. More than half of developers reported using review to explore alternative solutions, transfer knowledge, and stay aware of what teammates are building. _Anyone rethinking what code review should measure can follow this debate on daily.dev._ ## Community discussion Top comments from developers on daily.dev. **@agustinbarrientos** · 1 upvotes > I'd happily automate the routine checks, but I wouldn't give up human review for architectural context and knowledge transfer. **@ricktonoli** · 0 upvotes > So reviews become more about making sure AI doen't break stuff and do dumb things as opposed to "could this be better" or future proofing? Or do we just trust me bro the AI and let it handle those concerns? Or do we even care about that anymore when we can just turn over new apps in a day? > > Perhaps it's just a reality we have to accept, that the age of Software Craftsmanship is over and we've entered the Industrial Age, all of us becoming factory workers managing a conveyor belt. ## Similar posts on daily.dev - [Agentic Code Review](https://daily.dev/posts/agentic-code-review-0ue8fcsa1) · Addy Osmani · 146 upvotes · 14 comments - [Why AI Code Reviews Are Slowing Down PRs](https://daily.dev/posts/why-ai-code-reviews-are-slowing-down-prs-yubjqxjqr) · Aviator Blog · 0 upvotes · 1 comments - [Code review is burning out your best engineers](https://daily.dev/posts/code-review-is-burning-out-your-best-engineers-5anqvkfac) · The New Stack · 0 upvotes · 0 comments - [Code Reviews in the Age of AI](https://daily.dev/posts/code-reviews-in-the-age-of-ai-acvy63drb) · Earthly · 1 upvotes · 0 comments --- Tags: [#productivity](https://daily.dev/tags/productivity), [#ai-coding](https://daily.dev/tags/ai-coding), [#code-review](https://daily.dev/tags/code-review), [#company-culture](https://daily.dev/tags/company-culture) [View this post on daily.dev](https://daily.dev/posts/what-are-code-reviews-even-for--kzh6kkthn) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"What are code reviews even for?","url":"https://daily.dev/posts/what-are-code-reviews-even-for--kzh6kkthn","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/what-are-code-reviews-even-for--kzh6kkthn"},"datePublished":"2026-08-05T10:42:42.707Z","dateModified":"2026-09-13T19:30:52.256Z","description":"AI coding tools are generating code faster than humans can review it — at Meta, lines of code per diff grew 106% and diffs per developer rose 51%, mostly from...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/ee5304d5d0ebfeb18c1ea565b3d1c51d?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/ee5304d5d0ebfeb18c1ea565b3d1c51d?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Software Engineering Research","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Software Engineering Research","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/70072ba716944ea6b33b3e3dc413140c","url":"https://daily.dev/sources/abinoda"},"commentCount":3,"discussionUrl":"https://daily.dev/posts/what-are-code-reviews-even-for--kzh6kkthn","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":11},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":3}],"keywords":"productivity,ai-coding,code-review,company-culture","timeRequired":"PT9M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Software Engineering Research","item":"https://daily.dev/sources/abinoda"},{"@type":"ListItem","position":3,"name":"What are code reviews even for?"}]} {"@context":"https://schema.org","@type":"WebPage","@id":"https://daily.dev/posts/what-are-code-reviews-even-for--kzh6kkthn","comment":[{"@type":"Comment","text":"I’d happily automate the routine checks, but I wouldn’t give up human review for architectural context and knowledge transfer.","datePublished":"2026-08-05T22:45:26.814Z","url":"https://daily.dev/posts/KZH6KKThN#c-AgSHp46sB","author":{"@type":"Person","name":"Agustin Barrientos","url":"https://daily.dev/agustinbarrientos","image":"https://media.daily.dev/image/upload/s--5ayxQnqn--/f_auto/v1788281802/avatars/avatar_wQYYVe5Tbj0NJ7C7qPoa8?_a=BAMAMicg0"},"interactionStatistic":{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1}},{"@type":"Comment","text":"So reviews become more about making sure AI doen’t break stuff and do dumb things as opposed to “could this be better” or future proofing? Or do we just trust me bro the AI and let it handle those concerns? Or do we even care about that anymore when we can just turn over new apps in a day?\nPerhaps it’s just a reality we have to accept, that the age of Software Craftsmanship is over and we’ve entered the Industrial Age, all of us becoming factory workers managing a conveyor belt.","datePublished":"2026-08-06T06:00:07.321Z","dateModified":"2026-08-06T06:01:56.112Z","url":"https://daily.dev/posts/KZH6KKThN#c-YgIdJWplg","author":{"@type":"Person","name":"Rick Tonoli","url":"https://daily.dev/ricktonoli","image":"https://media.daily.dev/image/upload/s--1mKwVOZD--/f_auto/v1745813607/avatars/avatar_54gVqSdbL9DajhGSKNFpY"}}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/what-are-code-reviews-even-for--kzh6kkthn#faq","mainEntity":[{"@type":"Question","name":"How much did AI coding tools increase code review volume at Meta?","acceptedAnswer":{"@type":"Answer","text":"Lines of code per human-landed diff increased by 106% over a year, and diffs per developer per month rose 51%, with more than 80% of that growth attributed to agentic AI. Meanwhile the share of diffs reviewed within 24 hours declined, leaving some large groups with thousands of pending reviews. Teams scaling AI-generated code can compare notes on review bottlenecks and fixes through daily.dev."}},{"@type":"Question","name":"What is Meta's RADAR system for code review?","acceptedAnswer":{"@type":"Answer","text":"RADAR (Risk Aware Diff Auto Review) is Meta's system that automates review for a carefully selected subset of low-to-medium risk changes while routing higher-risk diffs to human reviewers, combining static analysis, machine learning, LLM-based review, and deterministic validation. It reviewed over 535,000 diffs, landed more than 331,000, cut revert rates to roughly a third of non-RADAR diffs, reduced production incident rates fiftyfold, and cut median time to close by more than 330%. Engineers weighing automated code review tools track real-world results like RADAR's on daily.dev."}},{"@type":"Question","name":"What percentage of code review comments are actually about finding defects?","acceptedAnswer":{"@type":"Answer","text":"Only about 14% of review comments focus on defects, according to a landmark Microsoft study, even though most developers cite defect detection as their primary motivation for reviewing code. More than half of developers reported using review to explore alternative solutions, transfer knowledge, and stay aware of what teammates are building. Anyone rethinking what code review should measure can follow this debate on daily.dev."}}]} ```