Latent Space: The AI Engineer Podcast · September 16, 2026 · 1h 26m

Underwriting Superintelligence: Backing Agents you can Sue — Rune Kvist, AIUC

Show notes

AIUC first got our attention with the NFDG backing, and have just announced a $40M series A today, with the most impressive industry advisor list we may have ever seen for an early startup behind AIUC-1 , their agent standard backed by real insurance: From being Anthropic’s first product hire to building the standards, testing, and insurance infrastructure meant to make frontier AI deployable, Rune Kvist is betting that the biggest constraint on AI adoption won’t be capability it will be trust. In this episode, the AIUC cofounder joins swyx and Vibhu to announce a new $40M round and explain why companies like Cursor, Harvey, Lovable, and ElevenLabs are increasingly confronting a problem that gets harder as AI gets better: who is responsible when autonomous systems fail? We go deep on AIUC-1 , the emerging standard for agent security, safety, and reliability; how AI agents are stress-tested for jailbreaks, hallucinations, and data leaks; and why Rune thinks standards and insurance could become critical infrastructure for AI. We also discuss the growing trust gap between governments and frontier labs, AI-enabled cyber and biological risks, why every model can ultimately be jailbroken, what happens when a $20 coding agent causes $200M of damage , whether AI engineers should be certified, and why even after AGI there may be one job the labs can never do themselves: be their own watchdog. We discuss: * Why risk, liability, and trust may become the binding constraint on AI adoption * Rune’s path from reading the Scaling Laws paper to joining Anthropic in its earliest days * What Anthropic understood about scaling, compute, and the future years before it became obvious * Why Waymo illustrates the gap between AI capability and real-world deployment * AIUC’s $40M round and work with Cursor, Harvey, Lovable, ElevenLabs, and other frontier AI companies * AIUC-1: a standard for AI agent security, safety, and reliability * How agents are tested for jailbreaks, hallucinations, an

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