Dr. Sarah Gebauer presents a clinical framework for deploying AI agents in healthcare, drawing a powerful analogy between AI agents and medical residents. She outlines the critical risks, validation strategies, and post-deployment monitoring required to make agents useful, safe, and credible in high-stakes clinical environments.
Andrew Rabinovich, CTO and Head of AI at Upwork, details their strategy for building AI agents for digital work. He introduces a custom reinforcement learning approach called RLEF (Reinforcement Learning from Experience), explains why digital work marketplaces are ideal training grounds, and shares his vision for a future where AI delivers finished projects, orchestrated by a meta-agent named Uma.
Jesse Zhang, co-founder and CEO of Decagon, discusses how their AI agents are revolutionizing customer service for large enterprises by replacing mundane human labor. He covers their go-to-market strategy, the importance of a hardworking in-office culture, his journey as a second-time founder, and the future of an agentic world where AIs interact on behalf of companies and consumers.
Edwin Chen, founder and CEO of Surge AI, shares the company's origin story, its rapid, bootstrapped growth, and its research-driven philosophy on data. He critiques traditional data labeling, explains why metrics like inter-annotator agreement fail for complex tasks, and offers a sharp analysis of benchmark hacking. Chen also details the future of data, from multimodal and agentic reasoning in rich RL environments to the need for hyper-specialized expertise for scientific discovery.
Box CEO Aaron Levie discusses the paradigm shift from cloud to AI, arguing that AI will augment jobs by automating non-strategic work and create massive opportunities for startups to tackle previously unsolvable problems with unstructured data. He covers the evolution of SaaS business models, the 'build vs. buy' debate, and offers key advice for founders in the AI era.
OpenAI's Greg Brockman and Thibault Sottiaux explore the evolution of AI-powered software development, from the first coding sparks in GPT-3 to today's GPT-5 Codex. They detail the concept of the "harness," the rise of agentic coding, breakthroughs in automated code review, and how AI agents capable of running for hours on complex refactoring will reshape the future of engineering.