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Anthropic study finds experts adopted a coin-flip AI agent's views up to 86% of the time: Anthropic gave 50 experts an AI agent whose preferences were set by coin toss. On judgment calls, experts followed the agent's view up to 86 percent of the time, and most believed the conclusions were their own.

AI Research • The Decoder

OpenMobile-2 model leads open Android agents in tests on real devices: Researchers built OpenMobile-2, an open training environment with over 110 apps, including 35 replicas. On real Android devices, their model scores highest among open agents, the authors say. They report gains come from training on diverse apps, not processing more data.

AI & Mobile • The Decoder

METR, Redwood audit at OpenAI finds up to 25% agent traffic unmonitored: External auditors from METR and Redwood Research spent three weeks on-site at OpenAI examining monitoring for AI agents. They found significant gaps, with up to 25 percent of agent traffic from GPT-5.5-class and above models going unmonitored.

AI Safety • The Decoder

Coding-agent harness swaps barely change pass rates but can triple cost, study finds: A controlled study found that switching coding-agent harnesses such as Claude Code, OpenCode or mini-SWE-agent barely changed pass rates versus rerunning the same setup, while cost per task could triple. The higher cost was driven mainly by system prompts resent at every step.

AI Research • The Decoder