We’re joined by Professor Tim Minshall, a leading authority on innovation and industrial strategy, and one of the most influential voices shaping how ideas move from labs into the real economy.

Tim is a Professor of Innovation at the University of Cambridge and head of the Institute of Manufacturing there, where he has spent decades working at the intersection of research, manufacturing, entrepreneurship, and policy. His work focuses on one deceptively simple question: why do so many great ideas fail to scale—and what does it actually take to turn innovation into impact?

In this episode we unpack on why advanced manufacturing still matters deeply for economic resilience, why the UK and Europe struggle to scale technologies they invent, and what policymakers, founders, and institutions consistently misunderstand about innovation systems.

We dive into:

-Why innovation fails at the scaling stage—not the idea stage

-The missing link between research, startups, and manufacturing

-Why advanced manufacturing is a strategic asset, not a legacy industry

-University spinouts: what works, what doesn’t, and why most fail

-The difference between invention, innovation, and impact

-Why “more startups” is the wrong innovation metric

-The role of systems thinking in national competitiveness

-What policymakers get wrong about industrial strategy

-How to build innovation ecosystems that actually deliver outcomes

-Lessons from Cambridge’s innovation model—and its limits

Key Takeaways from the Episode:

 1.⁠ ⁠Innovation Is a System, Not a Moment: Breakthrough ideas mean little without manufacturing, supply chains, skills, and institutions that support scale.

 2.⁠ ⁠Scaling Is Harder Than Inventing: Most countries are good at generating ideas—but poor at turning them into globally competitive products.

 3.⁠ ⁠Manufacturing Is Where Value Is Locked In: Design, production, and integration determine who captures value—not who publishes first.

 4.⁠ ⁠Universities Are Necessary but Not Sufficient: Spinouts succeed only when they’re embedded in broader industrial and financial ecosystems.

 5.⁠ ⁠Startups Are Not the Whole Story: Large firms, supply chains, and incumbents play a critical role in diffusing innovation at scale.

 6.⁠ ⁠Industrial Strategy Is About Capability, Not Picking Winners: Governments should focus on skills, infrastructure, and coordination—not chasing the next hype cycle.

 7.⁠ ⁠Innovation Metrics Are Often Misleading: Counting patents, startups, or venture funding misses what actually drives productivity and prosperity.

 8.⁠ ⁠The UK and Europe’s Structural Challenge: Strong science bases don’t automatically translate into global industrial leadership.

 9.⁠ ⁠Systems Thinking Beats Silver Bullets: Sustainable innovation requires alignment across education, finance, industry, and policy.

10.⁠ ⁠Impact Is the Only Metric That Matters: Innovation should ultimately be judged by whether it improves lives, competitiveness, and resilience.

Timestamps:

(00:00) – Introduction to Tim Minshall and innovation systems (03:10) – Invention vs innovation vs impact (06:40) – Why most innovations fail to scale (11:30) – The role of manufacturing in capturing value (16:20) – University spinouts and the reality behind them (21:00) – Startups, incumbents, and innovation diffusion (26:10) – What policymakers misunderstand about innovation (31:40) – Industrial strategy without hype (36:20) – The UK, Europe, and global competitiveness (41:10) – Measuring innovation the right way (46:00) – Systems thinking and long-term resilience (50:30) – Final reflections on building innovation that lasts

This episode is a grounded, systems-level look at how innovation really works—beyond buzzwords, hype cycles, and startup mythology.

Follow (@iwaheedo) for more conversations on innovation, industry, and the future of economic progress.

We kick off 2026 with a special episode with Luc de Leyritz, General Partner at Re7 Social, a first-check crypto fund, and one of the most philosophically grounded investors operating at the frontier of blockchain, DeFi, and AI-driven venture capital.

Luc’s journey is anything but conventional. From studying philosophy, to working at France’s DARPA-equivalent on advanced national security research, to building conviction around crypto as the next foundational layer of finance, this conversation unfolds as both an intellectual exploration and a practical guide to where money, markets, and capital formation are heading.

We go deep into what crypto is actually good for beyond speculation. Luc breaks down why stablecoins, DeFi lending, and prediction markets represent genuine product–market fit, how financial settlement is moving from T+3 to T0, and why permissionless systems fundamentally reshape who gets access to opportunity.

This episode also explores Luc’s experimental work with Farcaster, an autonomous, AI-driven venture fund sourcing and evaluating startups directly from decentralized social graphs like Farcaster. It’s a glimpse into a future where venture capital itself becomes programmable.

Throughout the conversation, we zoom out to ask bigger questions: -Is finance ultimately about allocating risk to the right people? -Can prediction markets outperform polls and pundits? -And what happens when trust in institutions declines, but neutral digital infrastructure becomes stronger?

Key Takeaways from the Episode:

1.⁠ ⁠DeFi Has Real Product–Market Fit: Borrowing instantly against assets, trading without intermediaries, and accessing capital without permission are already working today — especially for those outside traditional banking systems.

2.⁠ ⁠Settlement Speed Is the Hidden Revolution: Traditional finance still runs on T+3 or T+5 settlement. Crypto-native systems move value at T0, collapsing time, cost, and intermediaries.

3.⁠ ⁠Prediction Markets as Truth Machines: Unlike betting platforms, prediction markets aggregate collective intelligence. Their prices reflect real probabilities — often outperforming polls, experts, and media narratives.

4.⁠ ⁠Permissionless Capital Changes Venture Economics: In crypto, anyone can be an early investor. Access is no longer the edge — information and signal processing are.

5.⁠ ⁠AI Agents Will Reshape Venture Capital: Luke explains how autonomous agents excel at reading, filtering, and synthesizing massive information flows — redefining sourcing, diligence, and decision-making.

6.⁠ ⁠Farcaster vs. Social Hype Cycles: Why Farcaster’s developer-first ecosystem differs fundamentally from viral but fragile experiments like FriendTech — and what sustainable crypto-social networks actually require.

7.⁠ ⁠Digital Art, Scarcity, and Ownership: Why NFTs were directionally right but product-incomplete — and how new models may finally allow creators to monetize digital work without dilution.

8.⁠ ⁠A Bullish Long-Term Macro Thesis: Declining trust in institutions, rising liquidity, and regulatory clarity all point toward crypto becoming a core layer of global financial infrastructure.

Timestamps: (00:00) – Luc’s background: philosophy, national security, and venture capital (04:00) – What crypto is actually useful for today (08:30) – DeFi lending vs traditional credit systems (13:30) – Why stablecoins and instant settlement matter (18:00) – Prediction markets vs gambling and polls (24:30) – Truth, incentives, and betting on the future (30:00) – Monetizing knowledge in a permissionless world (36:00) – Digital art, NFTs, and scarcity economics (42:00) – Farcaster: an autonomous AI venture fund (50:00) – Farcaster, social graphs, and crypto-native networks (58:30) – Macro outlook: trust, liquidity, and regulation (1:05:00) – Where crypto, AI, and venture are heading next

This is a wide-ranging, first-principles conversation on money, technology, and the systems shaping our future.

Follow (@iwaheedo) for more conversations on crypto, capital, philosophy, and emerging technologies.

We’re joined by Mehran Gul, author of The New Geography of Innovation, who paints a detailed picture on how innovation power is shifting from Silicon Valley to unexpected places - China, Singapore, Switzerland, and beyond.

As a former advisor at the World Economic Forum and World Bank, Mehran has spent years studying the frontier of technological development, institutional evolution, and national strategy. His research spans eight countries across three continents summarised in his new book which challenges Western innovation orthodoxy—and offers a compelling vision for a more distributed, more inclusive innovation future.

We dive into:

-How Chinese talent is shaping the Global AI landscape

-Why innovation isn’t just unicorns and startups, but includes state-led infrastructure

-Singapore’s invisible excellence: no unicorns, but global digital leadership

-Switzerland’s surprising dominance in R&D and public transport innovation

-The cultural and structural flaws in Europe’s startup scene

-What stable governance, national purpose, and civic trust do for innovation

-What people get wrong about AI, disruption, and the future of work

Key Takeaways from the Episode:

1. China Is No Longer a Copycat: China's MSRA lab published the most cited scientific paper of the 21st century—training a generation of AI researchers that now dominate the global talent pipeline.

2. Singapore and Switzerland Show Us a Different Model: Forget unicorns. These countries focus on systems-level innovation—urban planning, transport, digital governance—that directly improve lives.

3. Government Can Drive Real Innovation: Singapore’s GovTech and digital twin strategy prove that with the right institutions, even small countries can lead the world.

4. Europe's Cultural Challenge: While Europe has capital and talent, its innovation suffers from risk aversion, private mindsets, and a fear of visible failure.

5. Stock Options as a Cultural Lens: The difference between PayPal's billionaire mafia and Skype's 11 millionaires reveals how equity culture influences ambition and scale.

6. Unicorns Are a Poor Innovation Metric: Mehran critiques the obsession with unicorn counts and valuations. True innovation should be measured by quality of life, productivity, and institutional resilience.

7. The Real AI Debate Isn’t Job Loss: We overhype automation and job loss. The real question is: who controls the models, who benefits, and how do we ensure global equity?

8. Innovation Will Be Multipolar: The future isn’t a US-China binary. Countries like Canada, South Korea, and Estonia are becoming quiet powerhouses of tech progress.

9. Infrastructure Is Innovation: Switzerland’s trains, Korea’s chip fabs, and China’s urban ecosystems all show that building real-world infrastructure is just as innovative as launching apps.

10. Innovation Must Be Contextualized: What works in San Francisco doesn’t always work in São Paulo or Jakarta. Mehran urges us to localize innovation strategies for real impact.

Timestamps:

(00:00) – Introduction to Mehran Gul and the new geography of innovation (02:45) – Why China’s MSRA lab transformed the AI talent pipeline (06:15) – Singapore’s silent innovation model: no unicorns, huge impact (10:00) – Switzerland’s success: trains, CERN, and the quality of life index (14:45) – The structural flaws in Europe’s innovation culture (20:00) – PayPal vs. Skype: why startup equity design matters (24:30) – How Canada built world-class AI labs with public funding (28:30) – Unicorns vs. real progress: rethinking innovation metrics (33:00) – What most people get wrong about AI and automation (37:00) – National strategy, political trust, and innovation performance (42:00) – Innovation across the Global South: case studies and insights (47:00) – The future of innovation in a multipolar world (51:30) – Final thoughts on building innovation systems that serve humanity

Join us for a powerful, myth-busting journey across the world’s new innovation hotspots—with one of the most insightful thinkers on global tech strategy.

Follow our host (@iwaheedo) for more conversations on technology, power, and emerging markets.