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A developer created a code-review tool running on a consumer RTX 5090 GPU using open-weight models, achieving F1 22.7 on the Martian code-review benchmark, and is considering turning it into a product or open-sourcing it.
Codex now supports custom review rules defined in AGENTS.md, enabling automatic application of expert review context to every pull request.
Diffsmith is a tool that lets you comment on your AI agent's code and collaborate on changes.
This essay examines how AI-generated code has broken the traditional link between the worker's credentials and their output, sparking debates over gatekeeping and quality. It proposes that new verification tools can rebundle contribution with a verifiable receipt, addressing both quality and access concerns.
The developer dzhng shares a GitHub repository of composable AI agent skills for building software factories, enabling autonomous goal-driven code generation with human review at decision points.
The article argues that requiring thorough code review negates the supposed productivity gains of LLM coding assistants, as empirical research shows they do not help write code better or faster, and proponents fail to address the inherent error rates.
OpenAI's GPT-5.6 Sol achieves state-of-the-art on a cybersecurity benchmark, and the new Codex Security plugin helps teams find, validate, and fix vulnerabilities in real code. This article provides a step-by-step guide to installing and using the plugin in Codex.
Observing that many PRs in the Bun repo feature AI reviewers (CodeRabbit and Claude) interacting with AI bots (Robobun), highlighting the increasing role of AI in code review.
This post describes how to build a self-improving code review agent as part of a cloud software factory, using a code review skill, GitHub actions, and an outer-loop agent for continuous improvement.
Grepathy is a tool that reads AI coding agent session transcripts to extract decisions and commits a markdown file explaining why code was written a certain way, making agent-written code reviewable and preserving reasoning.
Armin Ronacher reflects on how the shared language of a software project — the common understanding of concepts, boundaries, and invariants — lives in documentation, code, and conversations, and how the friction of coordination synchronizes people, a process that AI agents might disrupt.
git-absorb automatically creates fixup commits for staged changes, mirroring hg absorb's functionality. It integrates with git's autosquash to streamline applying code review feedback without manual commit SHA hunting.
This paper studies 1.02 million pull requests to analyze the transition from human-centric to AI agentic code review, finding that agent-involved patterns improve efficiency but not quality.
Mantis Skills is a portable toolkit from Google for building security review harnesses using coding agents, enabling automated vulnerability detection, reproduction, and patching across various codebases.
Shawn Wang (@swyx) shares his current focus on several AI and developer projects, including Sol Ultra, Fable 5, Sonnet 5, Terra Ultra, SWE 1.7, and Devin review, while using tools like Kakuna and interview techniques from @mattpocockuk and @trq212.
Kody Koala is a developer tool that helps users create their own integrations rather than relying on hosted integrations, giving them complete control.
In this blog post, antirez argues that in the age of AI, programmers should focus on controlling the ideas behind their software rather than reading every line of code, as AI can generate locally optimal code but humans excel at big-picture design and direction.
A developer built a tool using MiniMax AI's M3 model to analyze entire GitHub repositories in a single prompt, producing code health reports and bug detection. It successfully processed react's 780k-token codebase for $0.23.
Researchers demonstrate a new prompt injection attack where malicious instructions hidden in images bypass AI code reviewers and cause coding agents to leak repository secrets.
Matt Pocock shares an idea for a workflow using LLMs to generate podcast summaries of code diffs, aiming to prevent comprehension debt in fast-moving repos; he has implemented it for his personal wiki with good results.