Jeff Crume examines Jev, a new AI approach that makes structured decisions rather than generating text, through a cybersecurity lens. He argues that confidence scores are not evidence, that AI decisions expand the attack surface, and that observability, decomposed reasoning, independent controls, and human oversight are needed before trusting them.
This episode asks whether a model described as dangerously capable is a real security problem or a marketing narrative. It uses the Astra sandbox incident as a starting point, then covers how agents are moving from chat into the browser to book, file, draw, and shop, and what that shift means for payments, advertising, and merchant data.
Karan Singhal, who leads health AI research at OpenAI, joins a16z's Jay Rughani to discuss how OpenAI is building trustworthy health intelligence into general-purpose frontier models. The conversation covers expert-driven evaluation and disagreement handling, the role of AI as a complement to doctors, integrations with Epic and clinician copilots, personal agents navigating fragmented healthcare, the distinction between medical information and medical care, and how falling costs of medical intelligence could compress the lag in clinical consensus and accelerate treatment discovery.
Richard Socher, CEO of Recursive and author of The Eureka Machine, makes the case for automating the scientific method with recursively self-improving AI. He covers how AI keeps replacing hand-crafted expertise with scale, the four pillars of his approach, why hallucinations can aid discovery, why RSI still rules out an overnight takeoff, and how science may become an engineering discipline across physics, biology, and economics.
Al Chen explains what it takes to get AI observability software through the security and compliance reviews of major banks. He covers build pipelines, agent-driven CVE remediation with verifiable exploit tests, ClickHouse backup and restore verification, PII and MNPI leakage through LLM judges, and the tradeoffs of zero leakage and data sovereignty, with an emphasis on showing evidence to shorten time to production.
Lincoln Murr, head of AI product at Coinbase, explains agentic finance, covering agents that pay and agents that grow money. He traces the path from AgentKit, an early experiment giving an AI a wallet, to x402, an open payment standard built on the long-unused HTTP 402 code. He also discusses microtransactions as a replacement for the ad economy, agents executing trades from simple instructions, the trust-building lessons from two years of development, and the vision of agents that can pay for their own upkeep.