What happens when you hear your own hit song playing in public, but never receive the royalty?

In this episode of Riding Unicorns, James sits down with Ryan Edwards, Founder & CEO of Audoo, the music technology company rebuilding how public performance royalties are measured and distributed.

The idea for Audoo came from Ryan’s own experience as a musician. After hearing one of his songs playing in a London department store and discovering there was effectively no reliable way to track the royalty, he started investigating how the system actually worked.

What he found was an industry still relying heavily on proxy data, manual surveys and people physically visiting venues with clipboards.

Audoo’s answer is the Audio Meter, a small connected device that identifies music being played in public venues without recording or storing conversations. The resulting data allows collecting societies to understand what was actually played and distribute royalties more accurately to artists and rights holders.

Today, Audoo operates across 16 countries, with its technology deployed in environments ranging from cafés and retailers to gyms and leisure centres.

Ryan shares how he built the first prototype on a Raspberry Pi at his kitchen table, validated the idea with the former Chairman of PRS for Music, and launched the first real-world deployment on the other side of the world in Australia during COVID.

We also discuss the unusual group of investors Audoo has attracted along the way, including Björn Ulvaeus of ABBA, Paul McCartney, Elton John, Adam Clayton of U2 and Adele, and how those relationships have helped build credibility and open doors across the music industry.

Topics Covered

• Why the public performance royalty system needed rebuilding
• The personal experience that led Ryan to start Audoo
• Building the first Audio Meter prototype on a Raspberry Pi
• Why privacy had to be designed into the technology from day one
• The challenges of combining software, data and physical hardware
• Landing Audoo’s first major deployment in Australia during COVID
• Why venues are willing to install Audio Meters
• How better music recognition data changes royalty distributions
• Raising capital from some of the biggest names in music
• Expanding Audoo across 16 countries and into the Middle East
• What Ryan has learned from eight years as a founder
• Why founders need to celebrate wins and know when something can wait until Monday

This is a conversation about spotting an antiquated system, using technology to rebuild it from first principles, and creating the data infrastructure that could finally ensure artists are paid accurately when their music is played.

What does it take to build a frontier AI model lab in a world dominated by OpenAI, Anthropic and Google?

In this episode of Riding Unicorns, James and Hector sit down with Yang Li, Co-Founder & CEO of Cosine, one of the UK's leading frontier AI companies building sovereign AI models for enterprise and government.

Cosine began by fine-tuning foundation models for software engineering before evolving into a full frontier AI lab, training its own models from scratch. Today, the company works with organisations across defence, financial services and critical national infrastructure, deploying AI securely inside highly regulated environments.

The conversation explores why sovereign AI has become a strategic priority, how smaller model labs can compete with the biggest players, and what the future of enterprise AI will look like.

Yang also shares how AI is changing software engineering, why synthetic data has become a competitive advantage, and the lessons he's learned building one of Europe's most ambitious AI companies.

Topics Covered

• How Cosine evolved from AI coding tools into a frontier AI model lab
 • Why sovereign AI is becoming critical for governments and enterprises
 • Competing with OpenAI and Anthropic without billions in funding
 • Building AI models using synthetic data and post-training techniques
 • Why defence, banking and healthcare are driving enterprise AI adoption
 • The future of software engineering in the age of AI coding agents
 • Air-gapped AI, on-premise deployment and enterprise security
 • The geopolitical race for AI infrastructure and compute sovereignty
 • Hiring world-class AI talent and building high-performance teams
 • Founder lessons on conviction, resilience and staying alive long enough to win

This is a conversation about the future of frontier AI, the growing importance of sovereign technology, and what it takes to build an AI company that competes on the global stage.

What happens when computing reaches the limits of classical physics?

In this episode of Riding Unicorns, James and Hector sit down with Ashley Montanaro, Co-Founder & CEO of Phasecraft, one of Europe's leading quantum computing companies.

Backed by Episode 1, Phasecraft is building the software and algorithms that will unlock the commercial potential of quantum computers. While much of the industry focuses on hardware, Ashley explains why the real breakthroughs will come from the software layer, and why better algorithms could be worth orders of magnitude more than incremental hardware improvements.

The conversation explores what quantum computing actually is, why "quantum advantage" could become one of the defining technology milestones of the next decade, and how quantum and AI will work together to accelerate scientific discovery.

Ashley also shares what it's really like building a deep tech company, how non-dilutive funding helped Phasecraft grow, and why the next generation of computing could transform industries ranging from energy and pharmaceuticals to materials science and cybersecurity.

Topics Covered

• What quantum computing actually is and why it matters
 • Why software may create more value than quantum hardware
 • The race towards practical quantum advantage
 • How quantum algorithms unlock problems classical computers cannot solve
 • The future of materials discovery, batteries, pharmaceuticals and chemistry
 • Why AI and quantum computing will reinforce each other
 • The cybersecurity implications of post-quantum computing
 • Building a deep tech company with long development cycles
 • Raising over £5m in non-dilutive funding through grants and government programmes
 • Commercialising frontier research before the market fully exists
 • Lessons from building one of Europe's leading quantum software companies
 • Why radically new computing architectures could define the next generation of technology

This is a conversation about one of the most important technological revolutions still to come, why quantum computing is moving from theory to commercial reality, and what it takes to build a company at the frontier of science and software. 

How do you build AI for one of the world's largest, most valuable, and least digitised industries?

In this episode of Riding Unicorns, James and Hector sit down with Dr. Kate Jarvis, CEO & Co-Founder of Fifth Dimension, the AI company transforming how institutional real estate investors make decisions.

With a PhD from Stanford in machine learning and linguistics, Kate has spent her career applying AI to complex industries. Today, Fifth Dimension is building what she describes as the Bloomberg Terminal for real assets, helping some of the world's largest property investors replace spreadsheets, PDFs and manual workflows with AI-powered decision intelligence.

The conversation explores why commercial real estate has remained decades behind other financial markets, how AI is finally unlocking the sector, and what it takes to build enterprise software for one of the world's most relationship-driven industries.

Kate also shares candid insights on fundraising in today's AI market, founder-led sales, pricing AI products, and why Europe may have a unique advantage in the next wave of vertical AI companies.

Topics Covered

• Why commercial real estate remains one of the world's least digitised industries
 • Building the Bloomberg Terminal for institutional property investors
 • How AI transforms underwriting, portfolio management and investment decisions
 • Why decision intelligence matters more than simply collecting more data
 • The challenge of changing behaviour in relationship-driven industries
 • Founder-led sales and scaling enterprise go-to-market teams
 • Pricing AI products while managing token costs and unit economics
 • Building vertical AI companies versus foundation models
 • The differences between fundraising in Europe and the US
 • Why Europe could become the leader in vertical AI applications
 • The realities of raising venture capital as an AI founder
 • Founder resilience, conviction and building through uncertainty

This is a conversation about applying AI where it creates the greatest economic value, why enterprise transformation is ultimately about people rather than technology, and what it takes to modernise one of the world's biggest industries. 

Laura Modiano leads Founder Experience at OpenAI, a newly created function designed to help startups build, grow, and scale on the world's leading AI platform.

Having previously worked with startups at AWS and now at OpenAI, Laura sits at the intersection of founders, technology, and the future of company building.

In this episode, Laura shares how AI is fundamentally changing the startup journey, why founders can now build companies faster than ever before, and what OpenAI is doing to support the next generation of builders from day one.

We discuss:

• Why OpenAI created the Founder Experience team
• How startup building is changing in the AI era
• What founders need from AI platforms beyond infrastructure
• The difference between building a feature and building a company
• Why AI-native founders are moving faster than ever before
• How OpenAI gathers feedback directly from founders
• The rise of non-technical founders building technical products
• Why anyone can now learn, build and create with AI tools
• How Laura uses Codex to automate workflows and increase productivity
• The future relationship between startups and AI platforms
• Lessons from AWS, healthcare, startups and OpenAI
• What makes great founders stand out in a rapidly changing market

Laura also shares her thoughts on the future of AI applications, the opportunities for founders building on top of foundation models, and why curiosity, speed and continuous learning are becoming the most valuable skills in technology.

This is a conversation about the future of entrepreneurship, the democratisation of software creation, and what happens when anyone with an idea can build a company.

What does it take to build an AI company a decade before the world realises AI is the future?

In this episode of Riding Unicorns, James and Hector sit down with Barney Hussey-Yeo, Founder & CEO of Cleo, the AI financial assistant helping millions of consumers make smarter money decisions.

Barney started building Cleo years before ChatGPT brought AI into the mainstream. Today, Cleo has grown into one of the UK's leading fintech success stories, reaching $400M ARR and becoming a category-defining consumer AI company.

The conversation explores the realities of scaling from zero revenue to hundreds of millions in ARR, surviving the shift from the ZIRP era to COVID, and building a product-led company that endured long before AI became fashionable.

Barney also shares how AI is transforming the way Cleo operates internally, why every executive team member is now shipping code, and how founder behaviour, company culture, and execution speed are changing in the age of AI.

Topics Covered:

• Building an AI company before the AI boom
 • The origins of Cleo and the vision for an AI financial assistant
 • Growing from $0 to $400M ARR
 • Why the first $100M is the hardest milestone
 • Surviving COVID and finding product-market fit
 • Building data moats and defensibility in AI
 • Why AI has transformed customer acquisition
 • How Cleo uses AI internally across engineering and operations
 • The rise of AI-native companies and the future of work
 • Why some employees thrive with AI and others fall behind
 • The best AI tools Barney is using today
 • Advice for founders on fundraising, execution, and building great products
 • The next generation of AI startups and future unicorn predictions

A candid conversation about ambition, execution, AI, and what it really takes to build a generational technology company.

What happens when software adapts to humans, rather than humans adapting to software?

In this episode of Riding Unicorns, James and Hector sit down with Jonathan Sanders, Founder & CEO of Light, the AI-native finance platform redefining how businesses manage money.

Jonathan's journey spans investment banking, consulting, Pleo, founding Juni, and now building Light. Along the way, he has developed a unique perspective on technology, AI, and what the next generation of business software will look like.

The conversation explores Jonathan's concept of "organic software" where AI agents learn, adapt, and operate alongside teams, reducing complexity and transforming finance from a reporting function into a strategic intelligence layer.

Jonathan shares real-world examples of AI agents managing company spend, monitoring compliance, automating finance workflows, and generating insights that would have been impossible just a few years ago.

The discussion also covers founder psychology, building through uncertainty, AI-first organisations, and how leadership teams must evolve in a world where software development, product design, and operations are increasingly powered by AI.

Topics Covered:

• Jonathan's journey from finance and consulting into startups
• Why founding a company is one of the hardest ways to create change
• The concept of "organic software" and AI-native business tools
• How AI agents learn from company behaviour and improve over time
• Building finance software that tells stories instead of generating reports
• Real-world examples of autonomous finance workflows
• Why AI is changing the role of CFOs and finance teams
• How Light uses AI internally across product, engineering, and operations
• The rise of AI-first organisations and new ways of working
• Founder resilience, stress, and the realities of building companies
• Why software development is changing faster than most people realise
• The future of business operations in an AI-native world

This is a conversation about the next generation of software, the future of work, and what happens when AI becomes a true operating system for businesses.

Steve Domin, Founder & CEO of Duffel, the company rebuilding the infrastructure layer of the global travel industry.

Duffel is taking on one of the most complex and outdated sectors, creating modern, developer-first APIs for flights, hotels, and more. Backed by investors including Index Ventures and Benchmark, the company has raised over $50M to transform how travel is bought and sold.

Steve shares the journey of building Duffel from scratch, including:

•  Why the travel industry is fundamentally broken 
•  The insight that led to Duffel’s API-first approach 
•  Building deep supply-side integrations with airlines and incumbents 
•  Navigating COVID when travel demand dropped to zero 
•  The painful reality of scaling, resetting, and rebuilding product-market fit 
•  Where long-term defensibility comes from in complex infrastructure businesses 

We also explore:

•  What makes companies like GoCardless “talent factories” 
•  How AI is changing how modern engineering teams are built 
•  The future of smaller, highly efficient companies 
•  Steve’s view on the next generation of AI-native products 

This is a masterclass in persistence, infrastructure thinking, and building through uncertainty.

Mahdi Yahya, Founder and CEO of Ori, is now part of Radiant following its partnership with Brookfield.

Mahdi is building at the centre of one of the most important shifts in technology: the global race to scale AI infrastructure.

We cover:

•  From telecoms to data centres: lessons from building infrastructure businesses from age 20 
•  Why Ori chose the harder path of building for a future that did not yet exist 
•  What “AI infrastructure” actually means, from GPU clusters to orchestration software 
•  The Radiant model: combining capital, power, compute and software into a single platform 
•  Why AI is becoming sovereign infrastructure and what that means for governments 
•  Where value will accrue in the AI stack across hardware, infrastructure and applications 
•  The importance of vertical integration and marginal gains in a capital-intensive market 
•  Two pivotal decisions that shaped the company, including early acquisition and moving into physical infrastructure 
•  Founder resilience and the simple rule: stay alive 

Mahdi also shares his perspective on the next wave of AI companies, the opportunity in inference, and why robotics could be the next breakout category.

This is a conversation about building at civilisational scale and what it takes to operate where technology, capital and infrastructure collide.

This week on Riding Unicorns, we’re joined by Charlotte Palmer, Vice President of Venture Capital at Integra Global Advisors.

Charlotte sits on the other side of the table as an LP, backing emerging venture funds globally. In this episode, she lifts the lid on how LPs actually evaluate VCs, what really matters beyond headline performance, and why many GPs still get fundraising wrong.

We cover:

• How LPs really underwrite venture funds and why early DPI is often misunderstood
• What matters more than performance in the early years of a fund
• Why access and ownership drive returns more than anything else
• The reality of backing emerging managers and why smaller funds win
• Team dynamics, attribution, and how LPs assess partners under the hood
• Why fewer funds are getting backed and what’s changed in the market
• The shift in venture towards early-stage and how late-stage AI impacts LP strategy
• Portfolio construction from an LP perspective and how diversification actually works
• The role of co-investments and why LPs increasingly lean into them
• How GPs can create urgency in fundraising and what actually cuts through

Charlotte also shares practical advice for GPs, including how to re-engage LPs, how to position a fund without strong DPI, and why most outreach fails to land.

A clear, honest view from the LP side on what it takes to get backed and build a fund that lasts.