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22 GoKawiil briefs on this topic

Study of 700+ firms finds AI coding agents boost code volume, not shipped software

A study covering more than 700 software companies found that AI coding agents raised lines of code by 30 percent, commits by 20 percent, and pull requests by 23 percent, but did not meaningfully increase the rate at which firms resolved tracked features or issues in tools like Jira. Researchers attribute the gap to code review, which took 49 percent longer on average after AI tools were adopted, with more revisions required and more reviewer comments per pull request.

Study: AI coding agents boost code volume but not software output

Harvard researchers Fiona Chen and James Stratton analyzed Jellyfish analytics covering 300 million work events across more than 700 software firms and 700,000 employees from 2021 to March 2026. They found that while AI coding assistants and agents increase the volume of code generated, firms show little evidence of increased software output or reduced employment, because human code review becomes a bottleneck, with longer reviews, more revision requests, and more reviewer comments.

Agent.reviews Launches AI Tool for Automated Reviews of Software Resources

Agent.reviews introduces an AI-powered platform that reads and writes reviews on various software tools, including source control and code review repositories. The platform aims to streamline the review process by automating assessments of code and repository configurations.

New open-source tool Jev prioritizes AI-generated PR changes for review

Jev is a local code review tool that classifies changes in agent-generated pull requests into priority tiers (P0, P1, P2), showing only the highest-priority changes by default. It runs on the reviewer's own machine, translates diffs into natural language explanations, and does not post anything back to GitHub. The tool integrates with a Chrome extension and GitHub CLI to analyze real pull requests, alongside a offline demo mode.

Critic tool lets reviewers query the AI coding agent that wrote the code

A new tool called Critic routes review questions from a code-change page directly to the coding agent's original session rather than a generic assistant. It uses a short lease system so exactly one connected author device answers a question at a time, and if that device disconnects, the task returns to the queue after 45 seconds without losing context. Questions can be queued even if all author devices are offline, and session transcripts remain stored locally on the originating machine.

Delta launches public beta, aiming to replace pull requests with agent-based review

A new tool called Delta has entered public beta, offering a multiplayer workspace where teams write code alongside AI agents and review the results without relying on traditional pull requests. The company behind it says it has already disabled pull requests on its own repository, running all internal collaboration through Delta instead. The tool is available on macOS, Linux, Windows, and via browser, including mobile access to ongoing conversation threads.

Benchmark test finds GPT-5.6 Luna catches fewer bugs than GPT-6 Astra but at 28x lower cost

A new benchmark comparing OpenAI's GPT-5.6 Luna and GPT-6 Astra on code review found Luna verified 69 bugs across 50 pull requests versus Astra's 92, while costing roughly 28 times less per review. Luna also produced more false positives, with 24 of 93 flagged issues failing verification compared to Astra's 4 of 96, and it caught fewer security-related bugs.

Developer observes lasting bias against 'reduce' in code reviews

A software developer shares an anecdotal pattern from years of code reviews: peers rarely object to map or filter functions, but frequently flag reduce as hard to read. The developer notes reduce appears far less often in codebases than similar array methods, despite personally preferring it.

OpenAI's GPT-6 Astra outperforms rivals in cross-file code review tests

Early benchmark testing shows OpenAI's GPT-6 Astra model identifies about 4% more actionable bugs than GPT-5.6 Sol and 22% more than Opus 5 in code review evaluations. The advantage widens significantly on harder cross-file reviews, where Astra beats Sol by 20% and Opus 5 by 33%, suggesting stronger ability to trace how a change in one file affects code elsewhere.

uv Python tool adds deduplication for wheel cache files

A pull request submitted to the uv project introduces a mechanism to deduplicate files stored in its wheel cache, reducing redundant copies of package files. The change was merged into the open-source Python packaging tool's codebase after review.