Get all your questions answered at TechCrunch Disrupt 2026: The full breakout session agenda revealed
- ID
- 32310
- Status
- summarized
- Published
- 06 Oct 2026, 10:00 PM
- Fetched
- 06 Oct 2026, 10:37 PM
- Provider
- TechCrunch
- Category
- technology
- Original URL
- https://techcrunch.com/2026/10/06/get-all-your-questions-answered-at-techcrunch-disrupt-2026-the-full-breakout-session-agenda-revealed/
- Source URL
- https://techcrunch.com/feed/
Summary
- Score
- 2.0
- Created
- 06 Oct 2026, 10:38 PM
- Tags
- Audience
- saas_foundersai_ml_learnersai_agent_users
What happened
TechCrunch published the full breakout session agenda for Disrupt 2026, running October 13-15 at Moscone West in San Francisco with 10,000+ founders, investors, and operators expected. Breakout sessions are 50 minutes each, combine expert insight with audience Q&A, and are first come, first served with limited room capacity. Listed topics include building with AI agents, where value accrues as AI shifts from training to inference, what 'physical AI' means, running a better fundraiser, and how AI changes company and team growth; one session is sponsored by SOSV and features SOSV HAX's Susan Schofer and Duncan Turner. Pricing promos include up to $100 off a pass, 50% off a second pass, and a $75 Expo+ Pass for people recently laid off.
Why it matters
There is no product, pricing change, or technical disclosure here — it is a conference agenda and ticket promotion, so nobody's build changes because of it. The only usable signal is the topic list: 'training to inference' value accrual and 'build with AI agents' being headliner breakout themes is a weak directional hint about where founder attention is in late 2026, and the $75 Expo+ Pass is a concrete, low-cost option if anyone is already planning a US trip. For a Malaysian audience, budget the airfare and visa time on top of the ticket before treating this as an opportunity.
Discussion angle
The agenda lists 'where value accrues as AI shifts from training to inference' as a breakout topic — ask the room where they think that value actually lands for small teams: model providers, inference infra, or the app layer, and whether anyone locally is building against that bet.