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The article argues that traditional code review is ineffective for AI agents and introduces SafeScript, a Turing-incomplete JavaScript subset designed for static verification, shifting security focus from code review to policy enforcement.
An AI agent used sub-agents to review and fix issues in generated slides, but the fixes introduced new bugs that reviewers failed to catch, resulting in a flawed final product.
The article critiques a research paper arguing that coding agents can replace human code review, highlighting that human aspects like confusion, skepticism, and noticing missing elements are crucial and not replicable by LLMs.
A tweet proposing the creation of an automated skill called /fix-one-thing to read coding standards and fix violations in the codebase.
The post discusses capping the size of AI coding agent-generated pull requests to maintain review quality, seeking input on effective thresholds and trade-offs.
Jev-Code-Reviewer is a GitHub extension and CLI tool that helps developers review pull requests from AI agents by classifying changes into priority levels and providing natural language explanations of code diffs.
This article explains how to create a GitHub Copilot automation to triage Dependabot pull requests, grouping them by risk and verifying CI status to streamline the review process.
GitHub introduces a new integration with Muse, allowing users to review pull requests, catch up on issues and notifications, and leave comments without switching tabs.
Kent C. Dodds shares his practice of using new AI models for audits on security, performance, and more, noting that Opus 5.5 found a significant security issue other models missed.
Cursor AI has launched Rollouts and Security Reviewer, software development bots that automate deployment monitoring and security checks for codebases on Teams and Enterprise plans.
Security Reviewer has been updated to complete reviews 21% faster, reducing average time from 4.8 minutes to 3.8 minutes.
GitHub Copilot app now features an improved pull request view designed to handle extremely large code reviews with thousands of files and millions of changes efficiently.
CodeRabbit introduces Change Stack, a feature that connects a PR's purpose, behavior, dependencies, and code to assist reviewers in verification.
Shopify's CEO labels unsolicited AI-generated content as 'slop grenades,' discussing issues in AI rollouts that burden reviewers, with statistics and practical solutions from companies like BotsCrew.
Traditional code reviews are becoming obsolete with AI-generated code, and coderabbitai's Change Stack feature is highlighted as an innovative solution for reviewing agentic code.
Cognition states that none of their engineers write code manually, using AI agents with internal review, while tools like CodeRabbit are being developed to independently assess AI-authored code quality.
Relium is a pre-merge reliability layer for SQL and dbt that reviews changes to catch data issues before they impact business metrics.
The tweet discusses Grok 4.7 as a cost-effective AI model that can replace others like Opus for various tasks, highlighting its performance and pricing advantage, and mentions using pstack for managing multi-agent workflows.
@poteto expresses enthusiasm for Bend, a language enabling formal verification to accelerate software development and solve code review, with @VictorTaelin agreeing on its potential for building complex software without mistakes.
An individual shares an experience where Codex reviewed a pull request written by Claude, finding a real bug that another tool also flagged, raising questions about the efficacy of having multiple AI agents check each other's work.