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When AI Argues Back: The Promise and Peril of Evidence-Based Multi-Agent Debate

Fact-checking has always had a small public-relations problem: being right is not the same as being believed. A platform can label a claim false. A newsroom can publish a careful correction. A compliance team can flag a misleading ad, remove it, document the action, and still watch the same claim reappear in a shinier costume three hours later. The hard part is not only detection. It is persuasion. People need to understand why a claim fails, not merely be informed that someone with a badge disapproves of it. ...

November 11, 2025 · 15 min · Zelina
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Reason, Reveal, Resist: The Persuasion Duality in Multi‑Agent AI

Meetings are already persuasive systems. Someone speaks first, someone sounds confident, someone produces a spreadsheet with just enough decimal places to look holy, and suddenly the room has moved. Multi-agent AI systems are not so different. They are becoming small artificial committees: one agent retrieves, another proposes, another critiques, another decides. The optimistic version says this gives us productive disagreement. The less adorable version says we have built a machine for circulating influence, and we are only now asking what makes one agent cave to another. ...

October 2, 2025 · 14 min · Zelina