Harness is proving that innovation at scale doesn’t have to come at the cost of speed or focus. By adopting a “startup within a startup” model, independent teams operate with the agility of a startup while leveraging shared infrastructure to move faster and smarter. This approach is blurring the lines between engineering, product, and business, requiring leaders to build cross-disciplinary skills, create tighter alignment on outcomes, and embed accountability at every level. In an era where AI is accelerating both opportunity and competition, this model offers a blueprint for scaling innovation that directly drives business impact. In this session, you'll get insights into: How Harness structures independent startup teams to innovate quickly while maintaining accountability Essential product and business skills engineering leaders need to become true strategic partners Strategies for aligning roadmaps, investment decisions, and metrics across engineering and product How to connect engineering work directly to business outcomes to maximize impact Leadership principles for fostering rapid innovation cycles that scale without losing focus

In less than a decade, OpenAI evolved from a pure research lab into the fastest-growing product in history, scaling from 100 million to 700 million weekly users. This transformation required building an engineering function and culture from scratch, blurring the boundaries between research, product, and infrastructure. Sulman Choudhry, Head of ChatGPT Engineering, shares the organizational design choices, hiring shifts, and cultural bets that enabled unprecedented shipping velocity. He’ll cover what happens when domains collide, how to balance senior talent with AI-native interns, and the real-time architecture changes behind major launches like ChatGPT Images. This is a candid look at the patterns, anti-patterns, and opportunity zones that emerge when you scale AI products at breakneck speed.