TechCrunch Disrupt 2026: Stage Lineup and Key Speakers from Nvidia and Anthropic

Disrupt 2026 is scheduled to return to San Francisco from October 13 to October 15, taking over Moscone West for three days of programming focused on the evolving venture capital and technology landscape. This year’s iteration moves away from a singular main-stage approach, instead distributing content across six specialized stages designed to provide deeper technical and strategic engagement for attendees.

The programming is divided into thematic tracks: Disrupt, Builders, AI, Real World AI, Smart Money, and Smart Systems. This structure allows for more focused discussions, particularly on the Builders and AI stages, where the emphasis shifts from high-level industry overviews to the practicalities of scaling infrastructure and deploying machine learning models in commercial environments.

Conceptual digital art showing a network of circuits and gears.
The 2026 event tracks focus on the practicalities of scaling AI infrastructure and hardware.

The speaker lineup for the 2026 event includes several prominent figures in artificial intelligence and hardware. Confirmed participants include Les Karpas, the Inception Global Head of Physical AI at Nvidia, and Cat de Jong, the Head of Applied AI at Anthropic. Their involvement points toward a heavy focus on the intersection of physical robotics and large-scale AI applications.

Beyond the stage presentations, the event continues to host the Startup Battlefield 200, a curated cohort of early-stage companies. These startups will compete for a $100,000 equity-free grand prize. The competition serves as a central pillar of the event, offering founders a platform to pitch directly to panels of venture capitalists and industry experts.

For those planning to attend, the venue at Moscone West will serve as the hub for both the technical sessions and the broader exhibition floor. While the “Smart Money” stage focuses on the current state of fintech and investment, the “Smart Systems” and “Real World AI” tracks are expected to highlight the transition of automated technologies from laboratory settings to industrial and consumer use cases.

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