AI · Oct 7, 2026
OpenAI’s Alexander Embiricos is coming to TechCrunch Disrupt 2026 — days after the launch of DotsGet hands-on: The full lineup of interactive roundtables at TechCrunch Disrupt 2026
Oct 7, 2026, 7:15 AM · TechCrunch

Read TechCrunch's Disrupt roundtable list as a map, and one theme keeps surfacing: AI that looks great in a pilot and then stalls before it reaches real work.
Why it matters
This is TechCrunch promoting its own conference, so we read it as a program listing, not news. Disrupt 2026 runs October 13 to 15 at Moscone West in San Francisco, and TechCrunch expects more than 10,000 founders, investors and operators. The roundtables are small, discussion-style sessions spread across two dedicated spaces.
What makes the list worth a few minutes is what organizers and speakers chose to talk about. Agendas like this are a decent snapshot of where startup money and attention sit right now, and of the problems people are willing to admit in a room full of peers.
From the desk
The word that keeps showing up is not breakthrough. It is pilot. Kodamai's Maha Achour and 2468 Ventures' Pankaj Kedia are asking why so many enterprise AI projects stay stuck there. Databricks' Ankita Mehta is covering why pilots stall and why not every workflow needs an agent. Balerion's Naren Krishna and Pruven Capital's Travis Skelly argue that AI-native approaches will not work for big companies that cannot rip out their core systems. Smartsheet's Rajeev Singh frames AI as exposing what enterprise software got wrong rather than replacing it. We find that refreshing. A conference circuit that admits the gap between demo and deployment is healthier than one that pretends it is closed.
Physical AI is the other drumbeat. iMerit's Radha Basu on the data problems behind robots and autonomy, MetaProp's Jackson Feder on construction, property and energy, Rugged Robotics' Logan Farrell and Brick & Mortar Ventures' Austin Yount on what a robot must deliver beyond a good demo, and SandboxAQ's Jack Hidary with Nvidia's Stacie Calad-Thomson on AI grounded in physics, chemistry and biology. The repeated emphasis on reliability and trust in these descriptions is the right instinct. Software that fails gets a bug ticket. A robot that fails on a job site can hurt someone.
Two sessions speak to market structure. PitchBook's Harrison Rolfes asks whether anyone can still compete in AI given what it calls a $100 billion entry fee, and Premise's Mercedes Bent and Vanessa Larco are covering open-weight models as an alternative stack for startups. We think those belong together. Open models are one of the few forces pushing against concentration at the top.
What I'm watching for is what is thin on this list. There is a CISO career session and plenty on reliability, but little here centers the workers whose jobs these agents are meant to absorb, or the customers on the receiving end of agentic shopping. Walmart's Srishti Chaudhary is asking who owns the customer relationship in that world, which is the right question. We would like to hear more voices answering it from outside the vendor side of the table.
Context
A few sessions are sponsored, including ones from the New York Stock Exchange on El Segundo's hard-tech scene, Twin Peaks Wealth Advisors on founder liquidity, and UC Berkeley's Sutardja Center. One quantum computing session for investors had no speaker announced at publication. Earlier Disrupt coverage on our desk looked at the conference's safety sessions and its real-world AI stage; this list adds the small-room conversations around them.
Who feels it
- Enterprise buyers
- Several sessions openly treat stalled pilots as the norm. That is useful cover for asking vendors hard questions about production results before committing.
- Robotics and physical AI founders
- Investors are signaling that reliability, workflow fit and ROI matter more than demos. Expect diligence to follow that line.
- Startups weighing open-weight models
- Open models are being framed as a cost, control and security trade, not a charity. That is a mature conversation worth joining.
- Healthcare organizations
- Questa Capital's Brian Butler contrasts decades-long EHR adoption with generative AI uptake in about three years. Fast adoption raises the stakes on getting oversight right.
What to watch
- Whether Disrupt sessions surface concrete pilot-to-production numbers rather than anecdotes
- How investors talk about capital concentration in frontier AI and the room left for open-weight builders
- Any physical AI startups showing real deployment and safety records, not just demos
- Anthropic's forward-deployed engineering session as a signal of how labs plan to sell into enterprises