How to build an AI-Native Health Company — Dan Feng, Maven Clinic
Dan Feng outlines Maven Clinic's transformation into an AI-native company, driven by the realization that "building is cheap and arguing is expensive" in the AI era. This shift has reshaped planning to short, iterative sprints, revolutionized software development with AI coding tools, forced adaptive changes in code review processes, and necessitated a nuanced, multi-layered approach to ensuring reliability in generative AI systems.
Healthcare’s Agent Bytecode: X12 as the Harness for AI Agents — Vasant Kearney, Onlay
Vasant Kearney presents a nuanced perspective on implementing AI in healthcare, particularly in insurance. He highlights that while AI is evolving rapidly, real-world application requires understanding that solving isolated problems doesn't equate to complex solutions. His core argument is the utility of X12 as a 'harness' for agentic AI, providing a structured, confining framework for LLMs in healthcare. This approach acknowledges that X12 defines the contract between providers and payers, and even phone calls can be seen as X12 transactions. However, he cautions that X12, or any payer data, isn't ground truth due to disparate system origins, necessitating an internal 'semi-correct' representation. Kearney advocates for a balanced "AI pilled and AI skeptical" stance, embracing AI's potential while remaining cautious about its inherent limitations, cost, and the necessity for robust system design and evaluation.
Stateless, Yet Durable: MCP Tasks v2
Cornelia Davis explores the evolution of MCP Tasks, detailing the transition from v1 to v2. She highlights how v2's stateless protocol design supports durable, long-running agentic workflows by shifting durability responsibilities to the client and simplifying elicitation. The presentation includes a demo of a purchase order process and discusses future scalability enhancements through a notification-based approach.
MCPs for Observability Stacks
Diana Todea, Head of Developer Relations at VictoriaMetrics, demonstrates how Model-Controller-Pair (MCP) servers enhance observability stacks for faster, smarter troubleshooting. She highlights the use of AI-driven anomaly detection, natural language querying, and customizable "skills" to investigate production issues, manage metrics, and generate alerts, showcasing practical applications with two interconnected MCP servers.
What should security leaders do with AI? They don’t know.
This podcast explores the challenges cybersecurity leaders face in adopting AI, the emergence of new threats like ghostjacking, and AI's current capabilities in patching vulnerabilities. It highlights the prevalent "AI decision paralysis" and offers strategic advice for integrating AI into security operations, advocating for a human-in-the-loop approach and a realistic assessment of AI's current
Michael Kratsios: Inside the White House's AI Strategy
Michael Kratsios, from Scale AI and the White House, discusses US AI policy, advocating for open-source AI, flexible regulation, and supporting startups against incumbent moats. He outlines the White House's vision for AI-driven scientific discovery and the future focus on Quantum Information Science, while urging Congress to legislate on preemption and IP. He concludes with a call for technologists to engage in public service.
