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Each year, we get a huge influx of applicants to speak at TechCrunch\u2019s events, and this year\u2019s Founder Summit in Boston on November 4<\/a> will be no different! We want to thank everyone who applied to take part in our programming and to help share their expertise with the startup community.<\/p>\n After careful review, we have 11 finalists who are vying for four slots within this year\u2019s event agenda, and each one showcases the kind of practical, essential insights that can only be delivered by those who have built, iterated, and succeeded.<\/p>\n You can vote via this link<\/a> to weigh in on which sessions ultimately make the cut. Submissions will close on September 4. If you\u2019re voting and haven\u2019t already gotten your Founder Summit tickets this year, what are you waiting for?<\/p>\n On November 4 in Boston, you\u2019ll get the chance to learn directly from the experts in intimate, exclusive sessions that can put you ahead of the competition or set you up to play a pivotal role in developing the next era of innovators. We still have discounts running on tickets that can save you up to $100 right here<\/a>!<\/p>\n With that said, let\u2019s dive into our Disrupt Audience Choice nominees, and remember: The voting takes place via this form,<\/a> so take a look and then submit your vote!<\/p>\n Alexandra Ames: Founder and Chief Event Strategist,\u00a0Blueprint Lab<\/a>\u00a0<\/strong><\/p>\n Early-stage founders approach events one of two ways: say yes to every opportunity, or avoid them entirely because the ROI feels impossible to justify. Neither is smart. Events can build your audience and credibility before product-market fit but only if you\u2019re strategic about which ones deserve your time and budget. We\u2019ll discuss how to think strategically when resources are tight, including how to maximize ROI from founder events like this one. You\u2019ll leave with frameworks for prioritizing stage-appropriate event investments, tactics for proving value without complex tools, and clarity on when events make sense and when they don\u2019t.<\/p>\n Hannan Happi: CEO and Co-Founder,\u00a0Exowatt<\/a>\u00a0<\/strong><\/p>\n Domestic manufacturing is back in the spotlight, but building hardware in the U.S. is still widely seen as too expensive to scale. This session explores how founders can design hardware companies that make \u201cMade in the USA\u201d economically viable from day one. We\u2019ll break down supply chain strategy, cost structure, factory partnerships, and how policy tailwinds like the IRA and CHIPS Act change the equation. Attendees will leave with a practical framework for evaluating when domestic manufacturing can become a competitive advantage \u2014 not just a branding decision.<\/p>\n Andy Tang: Partner,\u00a0Draper Associates<\/a>\u00a0<\/strong><\/p>\n Pitches that change industries rarely fit existing categories \u2014 and most investors will pass on them for exactly that reason. This talk explores why the most fundable startups are often the hardest ones to describe, and what that means for how you build and position yours. Founders will leave with a clearer sense of the difference between a market insight and a market-creating idea, and what it actually takes to get a pattern-matching investor to bet on something genuinely new \u2014 before the rest of the world has a name for it.<\/p>\n Shishir Tewari: Head of Enterprise Data Engineering,\u00a0Procore Technologies<\/a>\u00a0<\/strong><\/p>\n Are messy data sources causing your LLMs to hallucinate? Relational databases struggle to bridge the semantic gap for AI. Learn to build a production-ready GraphRAG pipeline that turns chaotic data into actionable insights. Actionable takeaways: Build an offline pipeline to resolve disjointed datasets into \u201cgolden records.\u201d Translate flat records into an interconnected Neo4j knowledge graph. Deploy a secure, local LLM (Ollama) to translate natural language into validated Cypher queries. Give your AI the foundational data structure it needs!<\/p>\n Merve\u00a0Kitapci: Managing Partner and CGO,\u00a0ADIN.AI<\/a>\u00a0<\/strong><\/p>\n Most founders chase product-market fit before landing enterprise clients. We did the opposite. This roundtable covers the exact motion for closing global enterprise accounts at pre-Series A: how to structure the first conversation with a Fortune 500 CMO; why agency partnerships accelerate enterprise sales; how to price with no brand recognition; and what zero organic churn means for your fundraising story. Attendees leave with a repeatable enterprise sales framework, an early-stage AI pricing model, and the three things that make a CMO say yes before legal sees the contract.<\/p>\n Peter Farkas: CEO,\u00a0Percona<\/a>\u00a0<\/strong><\/p>\n Building a successful open source company without venture capital is rare \u2014 scaling it past $50 million in revenue is even rarer. This talk shares two decades of lessons from growing a commercial open source business from zero to global scale. We\u2019ll cover product-market fit, monetizing open source while keeping the core free, building distributed teams before remote work was mainstream, and creating a repeatable go-to-market engine without outside funding. We\u2019ll also discuss failures, hard lessons, and how to compete against well-funded alternatives while staying bootstrapped. Attendees will leave with practical strategies for scaling sustainably.<\/p>\n Linden Tibbets: CEO and Co-Founder,\u00a0IFTTT<\/a>\u00a0<\/strong><\/p>\n The playbook has flipped, and we have lived it firsthand. A five-person team can now outbuild, outship, and outmaneuver companies with 500 engineers. This roundtable gets into the tactical reality of running a lean, AI-powered team: which tools are actually worth your time, how to build workflows that compound instead of bloat, and where most teams are burning cycles on AI that goes nowhere. Walk away knowing how to audit your current stack for speed gaps, which AI-driven growth motions are converting right now, and how to use your small size as an advantage, not an excuse.<\/p>\n Jeff Mahler: Co-Founder and CTO,\u00a0Ambi Robotics<\/a>\u00a0<\/strong><\/p>\n In today\u2019s AI boom, impressive demos can generate headlines, funding, and early excitement, but they rarely prove a real business by themselves. This session explores the gap between prototype performance and real-world deployment, and why many promising AI startups stall before reaching scale. Founders and investors will learn how to evaluate whether AI systems are truly ready for production, the operational and reliability metrics that matter most, and how to build companies that can move beyond hype to durable, real-world impact.<\/p>\n Gregory Kurtzer: CEO and Founder,\u00a0CIQ<\/a>\u00a0<\/strong><\/p>\n Greg Kurtzer helped create CentOS, one of the world\u2019s most widely used operating systems, then founded CIQ and launched Rocky Linux when Red Hat discontinued CentOS. In this session, he shares hard-won lessons from building open source movements and a startup from scratch: why founders must leave ego at the door, then navigate the transition from hiring versatile generalists early, then moving to a team of specialists as you scale. He explains the mistake he almost made by dismissing the value of culture and core values, and what it really takes to build something durable.<\/p>\n Vikram Chaudhery, PhD: CEO and Founder,\u00a0Genoa Ventures<\/a>\u00a0<\/strong><\/p>\n Most AI healthcare demos look incredible and ship nothing. The companies that will matter in 2026 aren\u2019t the ones with the best models. They\u2019re the ones that get decisions to clinicians in an actionable window and change what doctors actually do for the patient in real clinical workflows. This roundtable digs into what separates investable healthcare AI from expensive science fairs, where agentic systems are creating real value beyond copilots, what founders consistently get wrong before their Series A, and the bar that anyone funding, founding, or joining a healthcare AI company should apply.<\/p>\n George Bandarian: Founder and General Partner,\u00a0Untapped Ventures<\/a>\u00a0<\/strong><\/p>\n The best technical founders building in AI and robotics aren\u2019t failing because of their product \u2014 they\u2019re failing because they don\u2019t understand what top investors are actually looking for. In this roundtable, early-stage technical founders will work through what YC, a16z speedrun, and top-tier VCs evaluate beyond the deck: founder-market fit signals, why most technical founders need a business counterpart earlier than they think, how to position an autonomous economy company for a lead investor, and what the fundraising process actually looks like before you have traction.<\/p>\n<\/div>\n When you purchase through links in our articles, we may earn a small commission<\/a>. This doesn\u2019t affect our editorial independence.<\/em><\/p>\nHow to Build Events Strategy Before You Can Afford a Full-Time Events Team\u00a0<\/h3>\n
How to Build a \u201cMade in the USA\u201d Hardware Company and Actually Scale It\u00a0<\/h3>\n
Build Something We Don\u2019t Have a Word for Yet<\/h3>\n
GraphRAG in Action: Stop Hallucinations with Knowledge Graphs<\/h3>\n
The Enterprise AI Playbook: How to Close L\u2019Oreal and Vodafone Before You Raise a Series A\u00a0<\/h3>\n
Lessons from 20 Years of Bootstrapping an Open Source Business to $50M+<\/h3>\n
Small but Mighty: How AI Lets Lean Teams Outship the Giants<\/h3>\n
The Demo Trap: Why Impressive AI Doesn\u2019t Always Build Real Companies<\/h3>\n
From CentOS to Rocky Linux: Building Movements That Outlast You\u00a0<\/h3>\n
The Healthcare AI Companies That Will Actually Matter\u00a0<\/h3>\n
How Technical AI Founders Get Into YC, a16z Speedrun, and Raise from Top-Tier VCs<\/h3>\n