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AI-native founders are not just building different products. They are changing how companies test ideas, organise teams, gather feedback and scale. In this EUVC conversation, Laura Modiano, who leads Founder Experience at OpenAI, shares what she is learning from founders building with AI across every stage of the company journey, from inception and pre-seed through to later-stage scale-ups. Laura explains how founders are using AI to pressure-test ideas from the perspective of investors, customers and different functions before entering real conversations. She argues that as building becomes easier, taste, speed and a strong point of view become increasingly important competitive advantages. The conversation also explores why AI-native teams are moving beyond rigid job titles, how centralised company knowledge can improve collaboration and why every function, from engineering to finance and marketing, should increasingly be able to build with AI. In addition, Laura discusses how established companies can become AI-first, the role OpenAI wants to play alongside startups building on its models and why European founders may benefit from being closer to industries such as manufacturing, logistics and healthcare. Highlights How founders can pressure-test ideas with AI Why taste is becoming a startup moat How AI-native teams organise and collaborate Why shared company knowledge matters more than ever How small teams can increase their output with AI How scale-ups can become AI-first Where OpenAI sees its role alongside application-layer startups Why European founders may have an edge in the real economy Timestamps (00:00) Intro(02:45) OpenAI’s support for startups(05:45) How Laura works with founders(08:40) What AI changes at the inception stage(10:00) Pressure-testing ideas with AI(12:20) Using AI before the first investor meeting(16:00) How founders should use AI at pre-seed(18:10) Why taste is becoming a moat(22:00) How AI-native teams should operate(25:20) Building a centralised knowledge system(28:40) How startups can scale with AI(31:00) Will OpenAI move further into the application layer?(34:00) How non-AI-native companies can become AI-first(38:40) Why everyone in a company should be a builder(40:40) Why European founders have an advantage(42:00) What AI is already changing inside enterprises

Getting pension funds into venture is not simply a question of appetite. The harder part is giving institutions a structure they understand, a risk profile they can assess and a clear path to returns. In this conversation from EUVC Summit 2026, Dario My, Head Venture Hub Switzerland at Deep Tech Nation Switzerland, joins Joe Schorge, Founder and Managing Partner at Isomer Capital, to discuss how Switzerland is trying to make venture more accessible to pension funds. Dario explains what Deep Tech Nation Switzerland has learned from working directly with pension funds, where interest in venture exists but experience with the asset class is still limited. He shares how its roundtables grew from three participating pension funds to around 20 and why performance remains the starting point for any allocation decision. The conversation also explores why early-stage venture is still perceived as highly risky, how education can gradually change that view and why pension fund mobilisation needs to be solved at country level. Dario also discusses the pension fund investment foundation created with pension funds themselves to address practical barriers and provide a more workable route into venture. Highlights Why pension fund appetite alone is not enough What Swiss pension funds need before allocating to venture Why performance remains the primary requirement How education can change perceptions of early-stage investing What Deep Tech Nation Switzerland learned from pension fund roundtables Why pension fund mobilisation needs country-specific solutions How a dedicated investment structure can reduce practical barriers What Switzerland’s approach could mean for European venture

Owning and operating a business can give family investors access to insights that are difficult to reproduce from the outside. The question is how to turn that knowledge into a genuine advantage for funds and founders. In this conversation from EUVC Summit 2026, ⁠Owen Reynolds⁠, Investment Director VC at ⁠Innotek⁠, shares how an active family business can bring deeper market knowledge, faster diligence and practical operating context into venture investing. Innotek is a single family office investing across venture capital, private equity and direct investments, with roots in industrial, manufacturing and technology. Owen explains how its in-house automation, robotics and engineering expertise can support investment decisions and portfolio companies in ways that go beyond capital. He also discusses why operating companies can sometimes “skip the first five slides” of a pitch deck, how continuous exposure to customers and supply chains creates an information advantage and why specialist investors risk losing some of that edge as they become professional investors. The conversation also covers how family offices can support VCs and portfolio companies more effectively, why that support needs to be specific rather than assumed and where LP expectations and established fund structures may be holding venture back. Highlights How operating businesses create an investment edge Why active operators can accelerate due diligence How in-house technical expertise can support venture investing Why specialist VCs can gradually lose their specialisation How family offices can work more effectively with VCs Why operating support needs to be specific and credible Where LP structures may be restricting venture funds How family offices can become stronger long-term partners

What does a genuinely useful VC relationship look like, and how much should operating experience matter when investors are advising founders? In this episode of This Week in European Tech, Dan Bowyer and Mads Jensen of SuperSeed discuss what separates strong VC partnerships from weaker ones, why venture outcomes naturally follow power laws and what founders should realistically expect from the investors around their table. They also look at the UK Budget and whether it goes far enough for founders, the wider economic pressures facing younger people and what could encourage more people to build companies. The conversation then turns to AI, including Anthropic’s planned IPO, where inference may happen in the future and the growing question of whether companies can trust the models and agents operating inside their businesses. Dan and Mads also discuss technological sovereignty, the case for stronger European AI infrastructure and what Europe should prioritise rather than trying to recreate every layer of the technology stack. Highlights What founders should expect from a strong VC partnership How much operating experience matters for investors Why venture capital produces power-law outcomes What the UK Budget means for founders Why entrepreneurship may have an energy problem as well as a policy problem What Anthropic’s planned IPO could tell us about the AI market Why more AI inference could move onto personal devices The security risks created by AI agents at scale Whether European companies can trust foreign AI models Where Europe should focus its technology sovereignty efforts

In vertical AI, choosing a narrower market can look like giving up scale, but for Corti it created the focus needed to go much deeper into healthcare and build around the accuracy, compliance and real-world complexity that clinical environments demand. Andreas Cleve, Co-Founder and CEO of Corti, joins us to explain the thinking behind that choice and what it has meant in practice. Andreas describes healthcare not as one market but as many highly specialised ones, each with its own workflows, terminology and requirements. That depth means bigger general-purpose models alone are not enough. Corti has instead had to build further down the stack and take greater control over the technology and infrastructure required to get AI into production. The trade-off becomes especially clear around accuracy. AI can perform well in a demo and still fall short in a clinical environment, where one incorrect word or detail can change the meaning entirely. Andreas explains why clinical-grade performance depends on much more than training better models, from working closely with users to adapting to individual specialties and solving the last-mile problems that appear when technology meets real workflows. The conversation also explores why Corti brought compliance in-house rather than treating regulation as something to outsource. For founders building in healthcare, legal, financial services or other high-stakes domains, the broader question is how to decide which constraints to accept, which capabilities to own and where going deeper can create an advantage that broader competitors struggle to replicate. Highlights Why Corti chose vertical AI over a broader horizontal approachWhat founders give up when they deliberately narrow their marketWhy bigger models do not automatically solve regulated-domain problemsWhy 90% accuracy can still fall far short in clinical environmentsHow specialisation pushes vertical AI companies deeper into the stackWhy getting AI into production requires more than model performanceWhy Corti built its compliance capability in-houseHow founders can think differently about regulation and other high-stakes constraints Timestamps (00:00) Intro(01:45) What Corti is building(03:45) Why healthcare needs specialised AI(05:45) Why bigger models do not solve healthcare(07:40) Healthcare is not one market(09:50) The trade-offs of going vertical(11:50) Funding a capital-intensive AI company from Europe(13:15) Why Corti is doubling down on Copenhagen(16:45) Copenhagen’s talent problem(19:30) Why 90% accuracy is not enough in healthcare(23:00) Solving the last mile of healthcare AI(25:45) Where AI adoption is happening fastest in healthcare(31:20) Why regulation is not the enemy(34:40) How founders should approach compliance(37:40) What founders should understand about venture funding(42:30) Why European VCs need a GPU strategy(46:40) Europe’s growth funding gap(48:00) When should European founders move to the US?

Seed investors are often told to ride their winners. But when the best companies remain private well beyond the original fund horizon, that creates a difficult question: when should a fund start turning paper gains into cash? In this conversation from EUVC Summit 2026, Romain Lavault, General Partner at Partech, joins Joe Schorge, Founder and Managing Partner at Isomer Capital, to discuss how seed funds can manage liquidity without giving up too much of their strongest positions. Romain explains how longer company lifecycles have changed the economics of seed investing, why secondaries have become a major route to liquidity and how Partech uses a framework to decide when to sell portions of high-performing companies. They also explore LP expectations around DPI, why liquidity decisions should be planned rather than emotional and how early conversations with founders can make future secondary transactions easier. Highlights Why seed funds face a growing liquidity challengeHow longer company lifecycles affect fund returnsWhy secondaries have become more importantWhen to sell part of a winnerHow to balance DPI with long-term upsideWhy founders need advance notice of liquidity plansWhy funds need a liquidity model as well as a fund model

Want help sharpening your fundraising story? Request a discovery call with Denes Ban, Founder of RAISE. --- Fundraising is not just about having a strong company or a compelling idea. It is also about understanding where the process breaks, how investors respond and what actually moves them to act. In this talk from EUVC Summit 2026, Denes Ban, Founder of RAISE, explains why fundraising should be treated as a measurable system rather than a matter of charisma or instinct. Drawing on his work with hundreds of founders and GPs, Denes breaks down the conversion funnel behind fundraising, why most people misdiagnose their bottleneck and how numbers, story and urgency work together. He also introduces the idea of a minimum viable story, built around five elements: how the world is changing, the problem, the solution, why you win and why now. Along the way, he explains why founders often rush too quickly to the solution and why “European resilience” on its own is not enough to raise capital. Highlights Why quality alone does not win How to identify the real fundraising bottleneck Why fundraising is a system that can be improved The role of numbers, story and urgency How to build a minimum viable story Why the problem should come before the solution What creates urgency in an investor process Why “European resilience” alone is not a fundraising strategy

Europe has deep pools of capital, but much of that money still fails to reach the companies and assets that could drive future growth. In this episode, Dan Bowyer and Mads Jensen of SuperSeed are joined by Karim Palant, Director of External Affairs at UK Private Capital, to discuss why domestic capital remains underrepresented in venture and private markets, and why that matters for Europe’s competitiveness. They look at pension reform, the UK’s reliance on international LPs, the incentives that keep domestic capital flowing elsewhere, and what the upcoming UK budget could mean for founders, investors, and wealth creation. The conversation also turns to AI infrastructure and cybersecurity, including whether trillion-dollar CapEx plans will actually materialise, how AI is making old cyber vulnerabilities easier to exploit, and what personal AI agents could mean for future security risks. Highlights Why Europe’s own capital is not backing enough of its growth Why pension money still struggles to reach venture and private markets The risks of relying too heavily on international capital What the UK budget could mean for founders and investors Whether the AI infrastructure boom is starting to slow How AI is changing cybersecurity What personal AI agents could mean for security

AI has transformed what is possible in language, but biology remains a much harder frontier. Oliver Vince, Co-Founder at Basecamp Research, believes one of the biggest constraints is that we still understand only a fraction of life on Earth, leaving AI models with a fundamentally incomplete picture of biology. Speaking at EUVC Summit 2026, Oliver joins Lorenzo Cerchi, Venture Capital Investor at Singular, a backer of Basecamp Research, to discuss how new biological datasets and frontier AI models could change therapeutic design, and why Europe may have an edge where AI meets deep scientific expertise. Oliver explains how Basecamp Research approaches the data problem in biology, how scaling laws could translate into better models and how those models might eventually help move from disease biology towards new medicines. The conversation also looks at the gap between European and US attitudes to risk, what it takes to finance highly ambitious deep-tech companies and why scientific talent needs room to pursue outcomes that may be uncertain but potentially enormous. They close on the longer-term possibility that AI could help tackle diseases that remain difficult or impossible to treat today, and why Oliver believes that potential is too significant to remain confined to the lab. Highlights Why biology is still a major data problemHow AI scaling laws could apply to therapeutic designWhere Europe has an advantage in AI and deep techWhy ambitious deep tech needs a different attitude to riskTurning scientific talent into breakthrough companiesThe path from disease biology to new medicinesWhy “prompt to cure” could become possible Timestamps (00:00) Intro(01:10) Why biology has an AI data problem(03:20) Where Europe can win in AI(05:05) The challenge of scaling deep tech in Europe(07:10) Why ambitious venture needs a different risk mindset(09:15) Europe’s scientific talent advantage(11:05) From disease biology to generating medicines(12:35) Playing for diseases we cannot treat today(13:05) Why “prompt to cure” may be possible

Quantum computing is not simply about making today’s computers faster. For Jan Goetz, CEO & Co-Founder at IQM Quantum Computers, the opportunity lies in solving problems that conventional computing architectures may never handle efficiently enough. Speaking at EUVC Summit 2026, Jan explains how IQM grew from university research into a full-stack quantum company building its own chips, systems, manufacturing capacity and cloud infrastructure. He reflects on the practical realities of building deep tech, including operating an early quantum computer from an office with improvised cooling, raising significant capital for hardware and scaling a company before much of the surrounding infrastructure exists. The session also explores Europe’s position in quantum, why hardware is becoming a critical bottleneck and how IQM is trying to scale globally while remaining headquartered in Finland. Highlights Why conventional computing is approaching physical limitsWhy quantum requires a different computing modelTurning university research into a deep-tech companyBuilding hardware before the infrastructure existsWhy hardware matters as much in quantum as it does in AIEurope’s current position in quantum computingScaling a capital-intensive company from EuropeAccessing global capital without leaving Europe Timestamps (00:00) Intro(01:05) Why some problems need a different kind of computer(03:05) Why bigger data centres are reaching their limits(04:05) How quantum computing scales differently(05:00) The energy problem behind AI compute(06:05) Building a full-stack quantum computer(07:20) From university research to building IQM(09:15) Building a quantum computer in an office(12:15) Europe’s position in quantum computing(13:25) Why hardware is becoming the bottleneck(14:05) Raising capital and planning a dual listing

Convelio’s most difficult period forced some of its most consequential decisions. After the art market contracted sharply, the company reduced its team, changed its business model and shifted its focus from top-line growth towards profitability. Host Andreas Munk Holm speaks with Edouard Gouin, CEO and Co-Founder of Convelio, about navigating that period and the decisions that ultimately helped the company reach its first fully profitable quarter. Edouard discusses the cost of delaying layoffs, bringing investors behind a new strategy, rebuilding trust and moving from a largely asset-light model towards physical operations, storage and software. He also shares the thinking behind the 65-page leadership manual he wrote during this period, the principles it codified around hiring, management and honest feedback and how Convelio is using AI to automate operational work. Highlights Moving from growth towards profitabilityMaking difficult decisions before circumstances force themAligning investors around a new strategyRebuilding trust after layoffsMoving beyond a purely asset-light modelWriting a 65-page leadership manualHiring for strengths and giving honest feedbackUsing AI to automate operational workReaching Convelio’s first fully profitable quarterTimestamps (00:00) Intro(02:00) How Convelio started(08:00) Copycats and the art market downturn(14:00) Looking inward and shifting to profitability(17:00) Layoffs and the cost of delaying difficult decisions(21:00) Aligning investors and the board(28:00) Rebuilding trust after layoffs(31:00) From asset-light to physical operations, storage and software(39:00) Writing a 65-page leadership manual(42:00) Hiring for strengths(45:00) Mistakes, sloppiness and honest feedback(53:00) Using AI to transform operations(1:01:00) Hard decisions, easy life and reaching profitability

The AI market is moving from proving the technology works to proving who can actually capture the value. In this episode of This Week in European Tech, Dan Bowyer, Mads Jensen and Priyanka Savjani of SuperSeed discuss the pressure building across AI infrastructure, Nvidia’s growing influence as both investor and supplier and why founders need to think carefully about strategic dependency. They also explore how AI agents could reshape ecommerce and distribution, where European founders can build harder-to-copy advantages and why physical AI, manufacturing and resilient supply chains remain important opportunities for Europe. Highlights Why AI investors are asking who actually gets paidWhere the risks sit in AI infrastructureWhat Nvidia’s investment strategy means for foundersWhy distribution matters for AI agentsWhere European founders can build defensible advantagesEurope’s opportunity in physical AI and manufacturingHow founders should think about China in their supply chainsWhether EU Inc. can still move the needle

Europe’s manufacturing sector faces a growing labour shortage, while much of the continent’s industrial base remains difficult to automate with traditional robotics. In this conversation from the EUVC Summit & Awards Show 2026, Tomaz Stolfa, Co-Founder and CEO of Sunrise Robotics, joins Patrick Murphy, Partner at Tapestry VC, to discuss what it takes to bring robotics into high-mix, low-volume manufacturing, where flexibility and reliability matter as much as the technology itself. Tomaz explains why manufacturers care less about the label of “AI-driven robotics” than whether a system can reliably take repetitive work off people’s hands, why even 99% robustness can fall short on a factory floor and how Sunrise is reducing automation projects that typically take 12 to 18 months to a matter of weeks. They also discuss Europe’s advantages in robotics, the importance of getting hardware into production early and why building a deep-tech company requires investors who are aligned for the long term. Highlights Europe’s growing manufacturing labour gapWhy traditional automation struggles with high-mix productionWhat manufacturers actually need from roboticsWhy 99% reliability is not enoughHow Sunrise is cutting deployment times from months to weeksWhy Europe has an advantage in industrial roboticsWhat it takes to finance deep tech for the long term Timestamps (00:00) Intro(01:00) Europe’s manufacturing labour gap(03:00) Why traditional automation falls short(04:20) Cutting deployment from 12–18 months to weeks(06:00) Why 99% reliability is not enough(08:00) Physics, safety and actually shipping robotics(09:00) Getting robots onto factory floors and scaling production(11:00) Why Europe is a strong place to build robotics(13:00) Choosing investors for a 15-year journey

AI’s footprint is visible in the energy, water and infrastructure required to run it. Its positive impact is harder to capture in a single number, which can make the costs of AI easier to see than the value it creates. In this talk, Harry Haeck, Partner at Smartfin, looks at both sides of that equation. He starts with the story of San Marcos, Texas, where residents rejected a $1.5 billion data centre investment over concerns about water use, before examining why greater efficiency does not necessarily mean lower overall resource consumption. Harry then turns to AI’s “handprint”, highlighting examples across drug discovery, agriculture, methane detection, accessibility and the recovery of ancient texts to show where the technology is already creating tangible benefits. The session closes on the question of how investors, technologists and society can reduce AI’s footprint while directing more of its capabilities towards problems that matter. Highlights Why AI’s footprint is easier to measure than its positive impactWhat the San Marcos data centre dispute reveals about AI infrastructureWhy efficiency gains can still lead to higher overall resource useHow AI is already creating impact across science and societyThe difference between AI’s footprint and its “handprint”Why we still have agency over where AI is applied This session was recorded at the Love Tomorrow Summit, where EUVC curated the investor-focused programme. Timestamps (00:00) Intro(01:00) From bedroom DJ to talking AI at Tomorrowland(02:00) When a $1.5B data centre competes with water(03:05) The growing energy and water footprint of AI(04:10) Why greater efficiency can increase consumption(05:15) From AI’s footprint to its handprint(06:00) How AI is already creating impact in the real world(09:55) Why AI’s positive impact is harder to measure(11:35) Why we can still steer the future of AI

Europe’s strongest AI opportunity may not be building the biggest general-purpose model. It could be applying AI where the region already has an advantage in science, engineering and specialised industries. In this episode of This Week in European Tech, Dan Bowyer⁠, ⁠Mads Jensen⁠ and ⁠Priyanka Savjani⁠ of ⁠SuperSeed⁠ discuss what London-built Isomorphic Labs tells us about that opportunity and why AI for science could become a distinctive area of strength for the UK and Europe. They also examine who is paying for the AI infrastructure boom, why falling model prices can still lead to rising total costs, how Mistral fits into Europe’s sovereignty ambitions and why Anthropic’s potential IPO could become a benchmark for the wider AI market. The conversation also turns to closer UK-EU cooperation and whether sector-specific agreements could strengthen Europe’s technology ecosystem. Highlights Why Europe’s AI advantage may be strongest in scienceWhat Isomorphic Labs could signal about the UK’s AI opportunityWho is ultimately paying for the AI boomWhy cheaper AI can still mean higher overall spendingWhere Mistral fits into the sovereign AI debateWhy price-performance matters more than headline model sizeHow Anthropic’s IPO could reshape AI valuationsWhether deeper UK-EU cooperation could benefit European tech------- We’re pleased to be partnering with Luxembourg Venture Days on October 14–15 at Luxexpo The Box. Explore the agenda and register here: venture-days.lu -------