Welcome to a new episode of the EUVC podcast, where our good friends Dan Bowyer and Mads Jensen from SuperSeed in a discussion with Andrew J. Scott, Founding Partner at 7percent Ventures and Karin Nielsen, Product & Growth Advisor at Unruly Labs, cover recent news and movements in the European tech landscape 💬
Watch it here or add it to your episodes on Apple or Spotify 🎧 chapters for easy navigation available on the Spotify/Apple episode.
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✍️ Show notes
“Buy European”: Vision for Growth or Road to Mediocrity?
Our discussion weighed the idea of buying European products instead of US alternatives, spotlighting a website (buy-european-made.eu) that urges consumers to choose local brands. Mads called the initiative “noble” but warned it risks mediocrity if Europe merely focuses on protectionism rather than producing world-class offerings.
Dan noted the surreal aspects of labeling certain companies “American” or “European,” given cross-border roots (e.g., booking.com from the Netherlands, Fanta’s origins in Nazi Germany).
Karin emphasized that the true path to a stronger European ecosystem lies in fostering innovation, better policies, and a supportive regulatory environment—ensuring that top-notch products emerge from Europe without relying on patriotic purchasing alone.
Andrew similarly pointed out that while “Buy European” can preserve local ecosystems in theory, it often dampens competitiveness. Instead, the group stressed how Europe should tackle underlying friction, such as limited capital and cumbersome regulations, so that its businesses can thrive globally.
Europe’s Productivity Puzzle: Growth vs. Regulatory Headwinds
The discussion highlighted Europe’s persistent struggle with lower productivity and slower growth compared to the US. Referencing Stripe’s annual letter and Mario Draghi’s EU report, they noted that while the region is brimming with talented founders and more startups than ever, it faces a capital shortfall, particularly in growth-stage funding, and burdensome labor regulations. The group stressed that these structural hurdles limit Europe’s ability to create global category leaders, as high-growth businesses often look elsewhere for more flexible policies and deeper capital pools.
At the same time, there was optimism about Europe’s capacity to improve. Calls for capital market reform, such as opening pension funds to venture investment, would go a long way toward bridging the continent’s funding gap. Panelists also argued for leaner regulations and more pro-business policymaking to reverse stagnation. The overarching message: without bold, founder-friendly reforms, Europe’s productivity potential remains underexploited, and its entrepreneurs may continue seeking opportunities elsewhere.
Accelerating Europe: Bridging the Funding and Productivity Gap
The “Accelerating Europe” report by Dealroom and Dealflow highlights that while Europe boasts 35,000 startups—the highest count globally—the region’s productivity still lags behind the US. FX differences contribute significantly to this divergence; for example, the UK is roughly 24% below US levels when measured on a PPP basis, and GDP per hour worked reveals even wider gaps.
The report also shows a steep decline in VC-backed startups from 24,000 in 2018 to about 9,000 today, along with a $375 billion funding gap, underscoring the challenge of scaling high-growth tech companies in Europe. In contrast, the US economy, now twice the size of the EU compared to 2008, is largely driven by robust consumer spending, which accounts for over two-thirds of its $30 trillion GDP.
The panel discussion further examined whether boosting consumer spending might be the key to European growth, given that personal consumption expenditure forms the beating heart of the US economic machine. However, they stressed that simply increasing consumer confidence is not enough; Europe must also address its structural issues, such as limited growth-stage capital and regulatory constraints, to build world-leading tech companies.
AI Corner: High Costs, Marginal Gains, and the Race for Application Value
GPT-4.5 and Anthropic’s Claude 3.7 have entered the scene with notable improvements—GPT-4.5, trained with 10x the compute of its predecessor, offers warmer, more intuitive, and emotionally nuanced conversations. However, there’s a growing debate: while many applaud the enhanced "vibes," critics question if the marginal improvements justify the steep costs. Sam acknowledged that GPT-4.5 is a “giant, expensive model” costing around $500M to train, with pricing per million tokens being 10-25 times higher than competitors. This has led to split opinions on whether these advances are transformative or simply akin to overpriced headphones.
On the competitive front, scaling models alone is not seen as a direct path to AGI; instead, the true value is emerging in the application layer—the “wrapper” around these AI models. Reflecting broader market dynamics, a Chinese company announced a 75% price cut during off-peak hours to align with US/EU daytime rates, signaling rapid adoption and a strategic pricing move to undercut Western offerings. The discussion underscores the pressing need to balance high development costs with real-world application value, pushing the industry to reconsider if current investments in scaling are sustainable in the long term.
Back to the Office: Balancing Hustle Culture with Flexibility
Industry leaders like Sergey Brin, Nik Storonsky, and Tobi Lutke emphasize that in-person work drives productivity, with Lutke recommending office attendance every weekday and a "60-hour work week" as the productivity sweet spot. At the same time, most mid-sized and large organizations—especially in the UK and across the EU—have adopted flexible work policies, with comprehensive directives for paternity, parental, and carer leave established as recently as August 2022. This debate comes amid a renewed appreciation for Silicon Valley’s hustle culture, as some argue that the pendulum swung too far in favor of work-life balance.
However, the push to mandate long office hours is seen as counterintuitive by many; issues like commuting, distractions, and inefficient meetings can disrupt deep work. Rather than a one-size-fits-all solution, the effectiveness of remote versus in-office work appears to depend on organizational culture and hiring practices. High-functioning remote teams—such as those at GitLab and Linear—demonstrate that when companies intentionally build for remote competencies, they can outperform traditional setups. In contrast, many big tech companies, which were not originally designed for remote work, face challenges retrofitting such models and risk losing valuable AI talent to more agile startups and AI labs.
Future of AI: Perspectives for Startups
The report, curated from leading investors and founders like Elad Gil, Chamath Palihapitiya, Yoav Shoham, Arvind Jain, and Dylan Fox, presents diverse perspectives on AI's role in the startup ecosystem. Gil argues that AI is massively underhyped, marking the early stages of a transformative wave with traditional machine learning maturing and generative AI still in its infancy. Chamath envisions AI drastically shrinking the multi-trillion-dollar "Software Industrial Complex," while Yoav dismisses the notion of AGI as a distracting myth. In contrast, Arvind Jain suggests that AI should drive top-line growth and open up new opportunities rather than merely cutting costs, and Dylan Fox cautions that enterprise AI adoption will likely be slower due to unresolved "last mile" implementation issues.
The report emphasizes that, despite widespread beliefs that AI will augment human productivity and creativity, significant concerns around reliability, privacy, and security remain unaddressed. It challenges the narrative that AI will seamlessly replace existing systems, arguing instead that real value lies in its application layer. For startups, this means focusing on how AI can create new revenue streams and competitive advantages, even as big enterprises might lag in adoption. Ultimately, the report urges founders to prepare for a future where AI reshapes industries incrementally, with 2025 serving as a critical juncture for transformation.
Data-Driven VC: Over or Just Evolving?
Recent discussions suggest that the era of pure data-driven VC might be coming to an end, particularly at the seed stage. While ML-driven approaches have shown impressive results at Series B—for example, Storonsky’s team at Revolut outperformed 95% of other firms in deal selection—the seed stage lacks the rich data necessary for these methods. With limited insights beyond founder CVs and commoditized industry research, the emphasis shifts from raw data to softer factors like brand strength and emotional intelligence (EQ). Lawrence Lundy-Bryan from Lunar VC argues that as data and AI democratize access to startup information, VCs will soon have an “all-access pass” to every founder, leveling the playing field.
This evolving landscape means that unless a VC is a well-established tier-one player, the focus must shift towards building an irrationally strong brand and carving out a specific niche. The traditional data-driven model may be giving way to a strategy where messaging and positioning outweigh sheer analytical prowess. In this bifurcated industry, where what you say you do and what you actually do can differ significantly, the power of a compelling narrative and strong network becomes the ultimate differentiator for winning deals.
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Ertan Can is the Founder & Managing Partner of Multiple Capital, Europe’s first tech-focused fund of micro funds. With over 20 years of experience in asset management, VC, and fund of funds investing, he has backed 31+ early-stage VC funds and built a portfolio of 500+ companies. His mission is to democratize access to early-stage tech funds across Europe and the US.
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