
What happened
Jacob Coxon, who trained AI systems at Anthropic and OpenAI, resigned, accusing both of racing to self-improving superintelligence and gambling with lives.
Why it matters
Evan Hubinger, who leads an Anthropic safety team, agreed, saying AI could kill all humans with >10% chance within a decade, and that Anthropic has no plan yet.
What to watch
The test is whether Anthropic and rivals develop safety plans before racing ahead; Coxon says they are locked in a race despite the risk.
WHO IT HITSEnterprise decision-makers relying on AI systems from Anthropic and OpenAI face fundamental uncertainty about long-term safety and control. Also, employees and researchers at these firms must weigh personal risk against career advancement and impending IPOs.
Summaries like this, every morning.
Anthropic's own safety community is fracturing over the pace of AI development. Jacob Coxon's departure, after previously working at OpenAI, underscores a pattern of high-profile exits from both companies over safety concerns. His accusation that these labs are "racing straight to self-improving superintelligence" comes as they are reportedly preparing for IPOs, potentially adding financial pressure to already aggressive timelines.
Evan Hubinger's public agreement and candid admission that the company lacks a safety plan highlight an internal contradiction: leadership voices acknowledge existential risks but admit no concrete strategy to mitigate them. The exchange occurs against backdrop of rogue agent incidents and warnings about frontie model monitorability, suggesting these are not isolated fears but endemic issues recognized even within the industry.
The stakes hinge on whether Anthropic and its rivals can translate safety rhetoric into actionable plans before deploying more powerful systems. Coxon's "locked in a race" characterization suggests competitive pressure may override caution. For companies integrating these AI systems, this debate signals that the technology's future is not merely a matter of capability but of governance and trust, with potentially fatal consequences if worst-case predictions materialize.
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