Discussion Groups
Our discussion groups are intimate, curated conversations led by some of the biggest names in AI. Attendees are assigned to a group based on the topics they're interested in for a collaborative conversation with other AI leaders.
Each group dives deep into a specific topic, giving attendees the chance to engage directly with the discussion leader and fellow participants in a small-group setting.
Examples From Past Summits
Parag Agrawal
Founder & CEO, Parallel Web Systems
Taking the Web From Human-First to Machine-First
The fabric of the internet is changing as we progress towards agents becoming the primary users of the web. It might not be too far from now that more traffic is agentic than user-driven. How will those agents interact with products, sites, and services?
Julie Bornstein & Kirsten Green
Founder & CEO, Daydream + Founder & Managing Partner, Forerunner Ventures
LLMs Open the Door — Expertise Builds the House
As the first wave of consumer AI applications emerged, many assumed that building a “wrapper” on top of large language models would be simple. The reality is far more complex — and far more interesting. True differentiation comes from being excellent at the edge, where deep domain expertise and nuance meet AI advancements to honor a vertical’s cultural, regulatory, and highly subjective intricacies. This discussion will explore what it takes to translate LLM potential into real consumer value at the application layer.
Emil Eifrem
Founder & CEO, Neo4j
The Persistent Memory Layer: Do Agents Need a Brain, Beyond Just a Model?
The next generation of agents won’t just complete tasks - they’ll remember, adapt, and improve over time. Persistent memory is key to making it happen, and it’s fast becoming a new battleground for product defensibility and differentiation. But what does durable memory look like in practice? How do we architect memory that scales with users, respects privacy, and compounds value? The session explores the question of agentic memory: when it’s needed, what founders needed to build lasting agent intelligence, and what VCs should look for when investing in it.