An Hour of Innovation: AI, Product, Tech and Career Growth – Details, episodes & analysis

Cancer care still forces patients and doctors to guess! Learn how functional precision medicine is replacing that uncertainty by testing cancer drugs before treatment even begins.

In this episode of An Hour of Innovation podcast, host Vit Lyoshin speaks with Jim Foote, co-founder and CEO of First Ascent Biomedical, an innovator who is challenging one of the most uncomfortable truths in modern medicine: many cancer treatments are chosen without knowing if they will actually work.

First Ascent Biomedical is a company focused on transforming personalized cancer treatment through functional precision medicine and data-driven decision support.

In this conversation, they explore how functional precision medicine differs from traditional precision medicine and why testing drugs on patients’ live tumor cells changes everything. Jim explains how AI, robotics, and large-scale drug testing help doctors move from trial-and-error to a true test-and-treat approach. The discussion also covers the risks of ineffective or harmful treatments, the economic cost of cancer care, and what must change for this model to become part of standard oncology practice.

Jim Foote is a former technology executive turned healthcare innovator whose work is deeply shaped by personal loss and firsthand experience with cancer care. He is best known for advancing functional precision medicine by combining genomics, live-cell drug testing, and AI-driven analysis to guide treatment decisions. His perspective matters because it connects real clinical outcomes with the technology needed to give doctors and patients clearer, faster, and more humane options.

Takeaways

* Cancer treatment still relies heavily on trial-and-error, even with modern medical technology.

* Two biologically different patients often receive the same cancer treatment based on population averages.

* Precision medicine based on DNA and RNA sequencing still cannot confirm if a drug will work before it’s given.

* Functional precision medicine tests drugs directly on a patient’s live tumor cells before treatment begins.

* Some FDA-approved cancer drugs can be completely ineffective or even make a patient’s cancer worse.

* Testing drugs outside the body can prevent patients from being exposed to harmful or useless treatments.

* AI and robotics enable hundreds of drug tests to be completed in days instead of weeks or months.

* In a published study, 83% of refractory cancer patients did better when treatment was guided by this approach.

* Knowing which drugs won’t work is just as important as knowing which ones will.

* Personalized, test-and-treat cancer care has the potential to improve outcomes while reducing overall healthcare costs.

Timestamps

00:00 Introduction

02:46 The Core Problem in Modern Cancer Care

04:16 Functional Precision Medicine Explained

06:42 How AI, Robotics, and Data Are Changing Cancer Treatment

10:01 How Cancer Drugs Are Tested Before Treatment

13:20 Personalized, Patient-Centric Cancer Care

18:22 Cost, Access, and the Economics of Cancer Treatment

22:19 The Future of Cancer Care and Patient Empowerment

25:21 Real Patient Outcomes and Success Stories

26:50 Why Functional Precision Medicine Is the Future

31:18 Predicting, Detecting, and Preventing Cancer Earlier

34:27 Where to Learn More About Functional Precision Medicine

36:12 Transforming Healthcare Beyond Trial-and-Error

37:27 Regulations, FDA Pathways, and Scaling Innovation

40:09 Why Cancer Is Affecting Younger Patients

41:17 Innovation Q&A

Support This Podcast

* To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Connect with Jim

* Website: https://firstascentbiomedical.com/

* LinkedIn: https://www.linkedin.com/in/jim-foote/

* TEDx Talk: https://www.youtube.com/watch?v=CqLCgNxUhVc

Connect with Vit

LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

X: https://x.com/vitlyoshin

Website: https://vitlyoshin.com

Podcast: https://www.anhourofinnovation.com/

Music education is quietly undergoing a massive shift, and most people haven’t noticed yet.

AI tutors are no longer just tools; they’re starting to shape how musicians learn, practice, and improve. But here’s the real question: where does human creativity and mentorship still matter in an AI-driven world?

In this episode of An Hour of Innovation podcast, host Vit Lyoshin sits down with John von Seggern, a longtime musician, educator, and founder of Futureproof Music School, to unpack what’s actually changing, and what isn’t, in the future of music education. John has spent over a decade designing online music education programs and now works at the intersection of AI, creativity, and human mentorship.

In this conversation, they explore how AI is personalizing music education in ways traditional schools struggle to scale. John explains how AI tutors can analyze music, guide students through complex production workflows, and surface the one or two things that matter most at each stage of learning. They also dig into why AI still falls short in mastery, taste, and creative judgment, and why human mentors remain essential. They discuss the hybrid model of AI tutors and human teachers, the future of music production learning, and what this shift means for creators trying to stay relevant in a fast-changing industry.

John von Seggern is a musician, producer, educator, and music technologist who has worked with film composers and contributed sound design to Pixar’s WALL·E. He previously helped lead and design one of the world’s most respected electronic music programs before founding Futureproof Music School, where he’s building AI-powered, personalized music education systems. His work matters because it goes beyond hype, offering a practical, grounded view of how AI can support creativity without replacing the human elements that make music meaningful.

Takeaways

* AI tutors are most effective when they surface only one or two actionable fixes, not long reports that overwhelm learners.

* Music education improves dramatically when AI can analyze your actual work (like mixes), not just answer theoretical questions.

* The biggest limitation of AI in music is that elite, professional knowledge is often undocumented, so models can’t learn it.

* Human mentors remain essential at advanced levels because taste, judgment, and creative intuition can’t be automated.

* Personalized learning paths outperform one-size-fits-all programs, especially in creative and technical fields like music production.

* Generative AI tools are fun, but most professionals prefer AI that assists the process, not tools that generate finished music.

* AI acts best as an intelligence amplifier, helping creators move faster rather than replacing their role.

* The future of music education isn’t AI-only, but a hybrid model where AI accelerates learning, and humans guide mastery.

Timestamps

00:00 Introduction

03:02 How AI Is Transforming Music Education

07:50 Why AI + Human Mentorship Works Better Than Music Schools

11:43 Why Music Education Curricula Must Evolve Faster

15:04 How AI Personalizes Music Learning for Every Student

19:38 Building an AI-Powered Education Business

24:22 What Students Really Say About AI Music Education

26:20 Electronic Music vs Learning Traditional Instruments

27:58 The Future of AI in Music and Creative Industries

30:28 Why Artists Still Matter in AI-Generated Art

32:21 Who Owns Music Created With AI?

36:50 How Creators Can Survive and Thrive Using AI

42:24 Innovation Q&A

Support This Podcast

* To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Connect with John

* Website: https://futureproofmusicschool.com/

* LinkedIn: https://www.linkedin.com/in/johnvon/

Connect with Vit

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

* Website: https://vitlyoshin.com/contact/

* Podcast: https://www.anhourofinnovation.com/

In this episode of An Hour of Innovation podcast, host Vit Lyoshin sits down with longevity entrepreneur and author Jon Sabes to explore why healthspan, not just lifespan, is the future we should all be planning for.

We dive into Jon’s powerful framework from his book Healthy, Wealthy, Longevity and unpack how your health, wealth, and purpose must work together to prepare for a longer, more vibrant life. Jon explains the real cost of poor health, the impact of living longer on your financial future, the lessons from Blue Zones, and why your older self will either thank you or regret your choices. He also introduces a new financial product that flips the traditional insurance model: one that rewards you for living longer.

Jon Sabes is a serial entrepreneur and the founder of Longevity Financial Partners, where he’s building innovative tools to help people prepare for longer lifespans. He previously led FOXO Technologies, where he worked on cutting-edge longevity biomarkers and epigenetics. Jon is also the author of Healthy, Wealthy, Longevity, and has spent nearly two decades at the intersection of financial services, molecular health, and aging science.

Support This Podcast

* Please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Takeaways

* Living longer without a plan can become your biggest financial risk.

* Health and wealth are deeply connected; poor health is financially expensive.

* Blue Zones offer a real-world model for how to live longer, healthier, and with purpose.

* Healthy aging depends on four things: eat wisely, move often, live with purpose, and connect with others.

* Your physical environment plays a major role in shaping good habits and reducing temptation.

* The worst-case scenario of aging: being alone and broke. Start preparing early to avoid it.

* You don’t need to be rich to live a long and healthy life; lifestyle matters more than wealth.

* Insurance should evolve to reward longevity.

* Jon’s company, LongevityFP, is building innovative financial products for longer lives.

* Movement doesn’t have to mean gym workouts; walking and small daily actions count.

* Processed food and sugary snacks are the silent killers.

* Purpose isn’t one big life mission; it can be small daily goals and routines.

* Staying connected socially becomes harder with age and remote work; build intentional relationships.

* AI and biotechnology are unlocking new ways to track aging and extend healthspan.

* Investing in self-care is no longer optional; it’s your hedge against an uncertain future.

* Think of your 90-year-old self and make choices they’d thank you for.

Timestamps

00:00 Introduction: Why Longevity Is the New Wealth

01:06 Inside “Healthy, Wealthy, Longevity”: Jon Sabes’ Breakthrough Book

03:51 Ads

05:06 How Health, Wealth, and Longevity Intersect, and Why It Matters

08:07 Start Early: Planning Now for a Longer, Healthier Life

11:38 Longevity Financial Partners: Redefining Financial Security for Longer Lifespans

15:44 The Blue Zones Formula: 4 Habits for Healthy Aging

22:58 Movement as Medicine: Simple Ways to Stay Active Without a Gym

25:38 Nutrition That Extends Healthspan: Small Changes, Big Results

29:29 Finding Purpose: The Mental Fitness Behind Longevity

32:00 The Power of Connection: Building Strong Social Networks as You Age

36:26 AI and Technology for Health and Longevity: What’s Coming Next

45:35 Motivation That Lasts: How to Stick to Healthy Habits

48:04 Innovations in Longevity Finance: The Future of “Reverse Insurance”

51:27 Leaving a Legacy: Agency, Control, and Designing Your Future Self

Connect with Jon

* Website: https://longevityfp.com/

* LinkedIn: https://www.linkedin.com/in/jon-sabes-14368257/

Connect with Vit

* Website: https://vitlyoshin.com/contact/

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

Vit’s Projects

* Podcast: https://www.anhourofinnovation.com/

* AI Assistant to build apps: https://appforgelab.com/

In this episode of An Hour of Innovation podcast, host Vit Lyoshin sits down with Nesrine Changuel, former product leader at Google, Spotify, and Microsoft, and author of the Product Delight book.

Together, they explore the power of emotional design in product management and why building products people truly love requires more than functionality. The conversation covers how emotional motivators shape user behavior, the story behind Chrome’s inactive tabs feature, and why Nesrine insists on moving beyond B2B vs. B2C to embrace B2H: business to human.

She also shares her Delight Framework, a practical method for balancing functionality with emotion, her 50-40-10 roadmap model, and lessons from Spotify’s hack weeks that sparked major innovations like Discover Weekly. The discussion also touches on UX design, innovation culture, and the future of humanizing AI in product development.

Nesrine Changuel is a seasoned product leader, speaker, and innovation coach. She has shaped global products at companies like Google, Spotify, and Microsoft, where she worked on Chrome, Meet, Skype, and Spotify’s user experiences. Nesrine is the creator of the Delight Framework, helping teams bring emotional connection into product design, and she is the author of Product Delight, a book that makes emotional design actionable for product managers, designers, and innovators worldwide.

Support This Podcast

* To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Takeaways

* An emotional connection is just as important as functionality in product design.

* Users remember how a product makes them feel, not just what it does.

* Motivational segmentation goes deeper than demographics or behaviors by focusing on why users engage.

* Spotify users aren’t just there for music; they seek inspiration, connection, and productivity.

* Product management is not B2B or B2C, it’s B2H: business to human.

* The Delight Framework helps teams systematically design for emotional connection.

* Roadmaps should balance features using the 50-40-10 model (functional, deep delight, and surface delight).

* Hack weeks at Spotify produced major features like Discover Weekly and AI DJ.

* Emotionally connected users stay longer, buy more, and refer more than satisfied users.

* Delight can be measured with metrics like NPS, CSAT, and Google’s HaTS survey.

* Emotional design applies even in “unsexy” industries like GitHub and Jira.

* Humanizing AI requires culture and leadership that embrace it, not block it.

* The best products remind users that real humans are behind the experience.

Timestamps

00:00 Introduction

01:00 Why Emotional Design Matters

03:43 What Is Emotional Connection in Products?

05:10 Ads

06:26 Chrome Tabs Story: Reducing Stress Through UX Design

10:43 Emotional Motivators: The Real Reason Users Choose Products

13:31 B2B vs B2C vs B2H (Business to Human)

15:27 The Delight Framework: 4 Steps to Build Emotional Products

20:24 How to Identify and Implement Emotional Motivators

21:54 Measuring Emotional Connection: Metrics That Matter

25:37 Balancing Functionality vs Emotion in Roadmaps (50-40-10 Rule)

29:16 Emotional Design in “Unsexy” Industries (GitHub, Jira, Atlassian)

32:40 From PhD Scientist to Product Leader

36:20 How Innovation Happens at Spotify and Google (Hack Weeks)

39:41 The Role of AI in Humanizing Products

45:21 Humanizing Products: Making Users Feel Real Humans Behind the Tech

49:02 Product Delight Book: Making Emotional Design Actionable

Connect with Nesrine

* Website: https://nesrine-changuel.com/product-delight-book/

* LinkedIn: https://www.linkedin.com/in/nesrinechanguel/

* Substuck: https://substack.com/@nesrinechanguel

Connect with Vit

* Website: https://vitlyoshin.com/contact/

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

Vit’s Projects

* Podcast: https://www.anhourofinnovation.com/

* AI Assistant to build apps: https://appforgelab.com/

In this episode of An Hour of Innovation podcast, host Vit Lyoshin sits down with Eric Müller, an engineering leader and security expert at Work & Co, to explore how AI is reshaping software development and why tools like GitHub Copilot and other AI code assistants must be treated like junior developers: fast, eager, and potentially dangerous without proper oversight.

We dive into the emerging trend of “vibe coding”, the practice of relying heavily on AI to generate code without fully understanding or validating it. Eric unpacks the hidden risks this creates, including hallucinated libraries, security vulnerabilities, and long-term maintainability challenges. He shares actionable insights on how developers and leaders can use AI responsibly, how to grow junior talent in an AI-assisted world, and what engineering managers should be doing to prevent burnout and maintain team health. We also discuss what makes a good manager, the role of psychological safety, and how to lead with trust in high-performing teams.

Eric Müller is an experienced engineering leader and cybersecurity expert. He currently leads product engineering and digital security efforts at Work & Co. Over his 20+ year career, Eric has held leadership roles at companies like Presence, Razorfish, and Edelman, helping teams build secure, high-quality digital products. He is known for his thoughtful approach to engineering culture, developer experience, and security-first product development.

Support This Podcast

To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Takeaways

* AI tools act like junior devs, fast but risky without oversight

* Vibe coding skips thinking and leads to bad code

* AI can hallucinate libraries, opening security holes

* Always review, test, and secure AI-generated code

* Great for prototyping, not solving new problems

* Junior devs are still essential, don’t stop hiring them

* Managers should remove blockers, not micromanage

* Burnout signals: too much pressure, no time off

* Watch team health via Slack activity and standups

* Best leaders listen, trust, and protect their teams

Timestamps

00:00 Introduction to AI, Developers & Software Innovation

03:36 Ads

04:50 How AI Coding Tools Are Changing Software Development

13:19 AI Limitations, Hallucinations & Common Misconceptions

17:00 Security Risks of AI-Generated Code & Maintenance Challenges

22:58 Why We Still Need Junior Developers in the Age of AI

28:02 What Makes a Great Engineering Manager in Modern Teams

31:48 Building Accountability & Psychological Safety in Dev Teams

36:25 Preventing Burnout & Promoting Work-Life Balance in Tech

41:30 How to Measure Team Health, Performance & Productivity

44:36 Transitioning to Engineering Leadership: Listening & Trust

46:42 The Future of AI in Secure & Scalable Software Development

Connect with Eric

* Website: https://work.co/

* LinkedIn: https://www.linkedin.com/in/ericmullersf/

Connect with Vit

* Website: https://vitlyoshin.com/contact/

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

Vit’s Projects

* Podcast: https://www.anhourofinnovation.com/

* AI Assistant to build apps: https://appforgelab.com/

In this episode of An Hour of Innovation, host Vit Lyoshin sits down with Galvin Widjaja, founder and CEO of Lauretta.io, to explore how AI in the real world is moving beyond counting people to actually predicting human behavior.

They discuss how computer vision AI is reshaping malls, airports, and casinos, why context is everything when it comes to intent detection, and how balancing privacy and ethics is critical for the future of AI surveillance.

Galvin shares how Lauretta.io’s technology can detect suspicious behavior, from identifying someone planting a bomb without ever witnessing the act, to uncovering hidden demand in shopping malls, to supporting casino security systems that resemble something straight out of Ocean’s Eleven. He also explains why Loretta.io is designed to “forget who you are” by default, and why that ethical choice matters as predictive AI expands into the physical world.

Galvin is the founder and CEO of Lauretta.io, an AI company that focuses on understanding human experiences in physical spaces through computer vision and non-biometric tracking. His background spans finance, consulting, and data optimization, which led him to spot early opportunities in AI surveillance and intent-based analytics. With a deep focus on AI ethics and privacy, Galvin is helping shape how predictive AI will be adopted in industries from retail to security. He also shares his advice for AI founders, thin vs thick AI, and why most AI startups will fail if they don’t choose wisely.

Support This Podcast

To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Takeaways

* AI in the real world is shifting from counting people to predicting human intent.

* Context matters: the same action means different things in different places.

* The AI technology can infer behavior, like spotting someone planting a bomb, even if the act isn’t seen.

* Retail use cases: understanding shopping behavior, hidden demand, and improving mall analytics.

* Security use cases: airports, public spaces, and casinos with thousands of surveillance cameras.

* AI acts as an assistant to human security guards, extending their attention span.

* Lauretta.io is built to forget identities by design, prioritizing privacy and ethics.

* Consent is key: identity is only linked when explicitly given or under legal security boundaries.

* Embodied AI is coming, think robot dogs in homes that track movement and behavior.

* Future AI will make intent detection more precise, but it raises ethical questions about preventive security.

* Galvin stresses the importance of responsible AI design to avoid privacy abuses.

* Galvin introduces the Thin vs Thick AI concepts: startups built on single models vs layered systems.

* Most AI startups will fail if they rely too heavily on one public model.

* Successful AI companies must focus on fundamental technology and long-term differentiation.

Timestamps

00:00 Introduction

01:04 Galvin’s Journey into AI

06:52 Ads

08:06 AI in the Real World: Understanding Human Experience

14:23 Lauretta.io Technology: Computer Vision & Non-Biometric Tracking

18:06 Context Matters: How AI Predicts Human Intent

22:53 AI for Retail vs Security: Business Insights & Threat Detection

27:32 Casino Surveillance: The Ocean’s Eleven of AI

33:11 Robot Dogs, Embodied AI & The Future of Surveillance

39:06 Ethics and Privacy: Why Lauretta.io Forgets Who You Are

43:25 The Future of Predictive AI & Security

48:00 Advice for AI Founders & Innovators

Connect with Galvin

* Website: https://lauretta.io/

* LinkedIn: https://www.linkedin.com/in/galvinw/

* X: https://x.com/galvinw

Connect with Vit

* Website: https://vitlyoshin.com/contact/

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

Vit’s Projects

* Podcast: https://www.anhourofinnovation.com/

* AI Assistant to build apps: https://appforgelab.com/

In this episode of An Hour of Innovation podcast, host Vit Lyoshin sits down with Ben Carle, CEO of FullStack Labs, to explore the real-world impact of AI in software development.

Ben is a PhD-trained computer scientist, engineering leader, and the driving force behind FullStack Labs, a software consultancy known for building AI-powered tools for enterprises that want scalable, modern applications.

Together, they unpack whether AI can truly replace engineers, how agentic AI is being used (and misunderstood), and what “code testing with AI” looks like in practice. Ben shares behind-the-scenes insights from FullStack’s internal AI systems, including a tool that now grades 80% of developer interviews, and how enterprise clients are adopting AI responsibly by starting with better data, stronger architecture, and measurable ROI.

Ben also shares practical lessons from the frontlines: how AI is transforming developer workflows, why junior engineers can't just "vibe code" with AI, and what engineering leaders need to know before integrating large language models into production environments.

With nearly a decade of experience scaling FullStack Labs, Ben brings a rare blend of technical depth and business clarity. His approach to AI adoption is grounded, ethical, and results-driven, making this episode a must-listen for engineers, product leaders, and founders navigating the future of software development.

Support This Podcast

To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Takeaways

* AI helps senior devs, not replaces them.

* Agentic AI = smarter automation, not magic bots.

* AI testing is harder, so non-deterministic outcomes need new QA methods.

* FullStack's AI grades 80% of developer interviews.

* Enterprise clients focus on data readiness, not flashy tools.

* Proof-of-concept first: no ROI, no build.

* AI audits live phone calls for compliance more accurately than humans.

* Companies forget to capture training data from human workflows.

* AI is improving UX in complex spaces like healthcare.

* Vibe coding doesn’t work at enterprise scale.

* Trust in AI is growing, but slowly in large orgs.

Timestamps

00:00 Introduction

04:12 Ads

05:27 Navigating AI in Enterprise Solutions

06:38 Why Aren’t Enterprise Companies Jumping into AI

09:51 What Expertise Enterprises Lack

12:26 Quality Assurance in AI Applications

15:14 Internal AI Tools and Processes

18:08 How to Hire Developers

20:29 AI in Developer Assessment and Certification

21:42 AI is Changing Developers' Behavior

26:25 AI's Role in Software Design and Architecture

28:49 Use Cases and the Future of AI in Development

33:32 The Integration of AI in Software Development

41:12 Identifying Suitable Use Cases for AI

50:01 Navigating Challenges in AI Adoption

54:32 Preparing for the Future of AI

58:24 Agentic AI

Connect with Ben

* Website: https://www.fullstack.com/

* LinkedIn: https://www.linkedin.com/in/bencarle/

Connect with Vit

* Website: https://vitlyoshin.com/contact/

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

Vit’s Projects

* Podcast: https://www.anhourofinnovation.com/

* AI Assistant to build apps: https://appforgelab.com/

In this episode of An Hour of Innovation podcast, host Vit Lyoshin speaks with Brian Perks, founder and Chief Strategy Officer of Five by Five.

Brian is a seasoned data strategist and entrepreneur with nearly two decades of experience in the data industry. The conversation explores how data co-ops are disrupting the traditional broker model, why “no one’s data is as good as everyone’s data,” and how real-world usage is the most effective way to validate information. The discussion also covers identity verification, fraud prevention, privacy trade-offs, and the role of AI in analyzing data, identifying patterns, and enabling precise targeting. Other highlights include insights into the future of publishing in the AI era, the balance between personalization and privacy, and why efficiency in data activation benefits both businesses and consumers.

Brian Perks has held leadership roles at ZoomInfo, Bombora, and Pipl, where he specialized in data acquisition, licensing, and identity solutions. Today, as co-founder of Five by Five, he is pioneering a cooperative model that democratizes access to high-quality, continuously validated data. His entrepreneurial journey reflects a vision for disrupting outdated systems, building trust in digital ecosystems, and empowering companies of all sizes to innovate with reliable data. Widely regarded as a thought leader, Brian continues to shape conversations around data strategy, privacy, and the evolving role of AI in business.

Support This Podcast

To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Takeaways

* How 5x5 Data was born out of necessity, turning an informal data exchange into a full cooperative model.

* The surprising truth: “No one’s data is as good as everyone’s data.”

* How billions of daily validation signals (emails, phone numbers, IPs) create a more accurate “identity graph.”

* The most reliable way to validate data is to consume it in real-world use cases.

* A live email address is worth more than your Social Security number on the dark web.

* The trade-off between privacy and personalization, and why 70% of people actually prefer targeted ads.

* Why efficiency in targeting matters: the best data isn’t a big list - it’s knowing who will actually buy.

* How better targeting can reduce marketing waste and even lower product costs for consumers.

* The hidden risk for publishers: AI tools are reducing their traffic by up to 90%, similar to Napster’s effect on music.

* Why publishers may need a new licensing model as AI “answer engines” replace traditional search.

* The limits of AI: it can accelerate data processing, but it can’t synthesize personal identifiers like emails or phone numbers.

* Controlling data through brokerage stifles innovation - democratizing access enables it.

* Data has no intrinsic value - it only matters in how you activate it.

Timestamps

00:00 Introduction

02:29 Ads

03:45 The 5x5 Concept and Data Utilization

06:17 Understanding the Work Co-op Model

08:26 Joining the 5x5 Community

11:26 Diverse Use Cases Beyond Marketing

13:58 Ensuring Data Integrity and Privacy

15:51 Navigating Privacy Concerns

18:12 The Trade-offs of Privacy and Personalization

21:59 Efficiency in Marketing and Sales

27:37 The Impact of AI on Product Development

29:37 Challenges in AI and Data Licensing

33:12 Source of Hallucinations and Mistakes in AI

38:00 Utilizing Data for Targeting Audiences

42:47 Social Media

45:38 Application will Do More

49:37 Entrepreneurial Insights and Advice

55:33 Advice from Brian

Connect with Brian

* Website: https://5x5data.com/

* LinkedIn: https://www.linkedin.com/in/briangperks/

Connect with Vit

* Website: https://vitlyoshin.com/contact/

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

Vit’s Projects

* Podcast: https://www.anhourofinnovation.com/

* AI Assistant to build apps: https://appforgelab.com/

In this episode of An Hour of Innovation podcast, host Vit Lyoshin sits down with Rowan Stone, CEO of Sapien, to explore how human knowledge powers the next generation of artificial intelligence. Together, they dive into the importance of high-quality data, the challenge of bias in AI, the role of blockchain payments in rewarding contributors, and the future balance between human input and machine learning.

Rowan shares his journey from energy executive to crypto entrepreneur, building early DeFi protocols, co-creating Coinbase’s Layer 2, and eventually launching Sapien, a decentralized data platform that connects enterprises with a global network of contributors. He explains why data is the true bottleneck in AI, how Sapien incentivizes contributors from everyday people to doctors and engineers, and why human oversight remains essential even as AI becomes more advanced.

Rowan Stone is a seasoned entrepreneur whose career spans energy, crypto, and AI. He co-founded multiple ventures in the blockchain space, including projects acquired by Coinbase, where he spent three years leading initiatives around stablecoins, tokenization, and Layer 2 solutions. Today, as CEO of Sapien, he focuses on sourcing and structuring human data for specialized AI models used in fields like autonomous vehicles, robotics, and healthcare. His mission is to democratize access to AI’s growth by enabling people everywhere to monetize their knowledge while ensuring enterprises get the high-quality data they need.

Support This Podcast

To support our work, please check out our sponsors and get discounts: https://www.anhourofinnovation.com/sponsors/

Takeaways

* AI is only as smart as the quality of data it’s fed.

* The true bottleneck in AI is data, not algorithms or compute.

* Everyone’s knowledge, from experts to everyday people, has value for training AI.

* Global diversity in data contributors is key to reducing bias in AI.

* Politically correct outputs can still be factually wrong, as seen in the Viking ship AI fail.

* AI can enhance doctors’ diagnostic power while creating new income opportunities.

* Self-driving cars still struggle because training is highly city-specific.

* Incentive systems like staking and slashing help ensure high-quality data for AI.

* Stablecoin payments enable instant, global compensation for AI contributors.

* Human input will always be needed to handle real-world randomness and context.

Timestamps

00:00 Introduction

01:14 From Energy to Crypto: A Personal Journey

05:56 Understanding Sapien: The Decentralized Data Foundry

10:33 Quality of AI Data: What Does It Mean?

12:17 Contributors and Their Role in Data Annotation

14:13 Scaling Contributor Networks and Quality Control

20:47 Addressing Bias in AI Data

25:31 Expert Contributors: Recruitment and Qualification Process

29:28 AI as a Diagnostic Tool for Healthcare

32:03 Challenges in Autonomous Vehicle Development

35:01 The Intersection of Crypto and AI

39:32 The Future of Human Expertise in AI

43:39 The Role of Creativity in AI

48:15 Getting Started with AI Model Training

Connect with Rowan

* Website: https://earn.sapien.io/

* LinkedIn: https://www.linkedin.com/in/rowan-stone/

* X: https://x.com/rowanrk6

* Other: https://www.sapien.io/

Connect with Vit

* Website: https://vitlyoshin.com/contact/

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

Vit’s Projects

* Podcast: https://www.anhourofinnovation.com/

* AI Assistant to build apps: https://appforgelab.com/

In this episode of An Hour of Innovation podcast, host Vit Lyoshin sits down with Nick Cawthon, a seasoned UX designer, researcher, and educator, to explore the evolving role of user experience in the age of AI. Nick shares insights on how UX has transformed from the early days of the internet to today’s standardized design systems, and why research remains at the heart of building products people love. We discuss the British Design Council’s Double Diamond framework, balancing qualitative and quantitative data, and how AI tools are reshaping research, prototyping, and usability testing. Nick also warns about the risks of replacing human connection in research with automated tools and why maintaining a human-centered approach is more important than ever. The conversation is filled with practical examples, including a memorable story about a taqueria that manages to juggle orders from eight different delivery apps.

Nick Cawthon is the founder of Gage, a user experience consultancy, and a faculty member at the California College of the Arts, where he teaches UX and data visualization. With over two decades of experience, Nick has worked across startups and Fortune 500 companies, helping teams bridge the gap between design and development. He is known for his deep expertise in research operations, design systems, and the integration of emerging technologies into UX workflows. Passionate about both the craft and the strategy of design, Nick brings a rare mix of practical know-how and visionary thinking to the conversation.

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Takeaways

* How the iPhone and standardized design systems shifted UX from aesthetics to experience-first thinking.

* Why the Double Diamond Framework is still one of the best ways to ensure you build the right thing before building it right.

* Nick shares a vivid story of a taqueria struggling to manage orders from eight delivery platforms.

* How blending numbers with human stories creates deeper, more persuasive insights.

* How AI speeds up surveys, persona creation, and testing, but risks losing authentic human insights.

* Why algorithms can’t replace empathy and genuine human connection.

* The importance of moving beyond Figma handoffs to integrated design-to-code workflows.

* Why modern UX designers must understand developer workflows and component libraries.

* Why safeguarding data and respecting consent are essential in AI-powered design.

* Why designers should preserve proven design patterns instead of reinventing the wheel.

* Why moving too fast with AI-driven features can frustrate users and erode loyalty.

Timestamps

00:00 Introduction

03:12 The Evolution of User Experience

06:31 Research Methodologies in UX

09:42 Starting Research: The Double Diamond Approach

12:14 The Importance of User Observation

14:30 Balancing Qualitative and Quantitative Data

18:03 AI's Impact on User Experience

19:56 The Shift from Voice to Chat Interfaces

24:00 AI and Emotional Companionship

25:13 AI's Impact on UX Research

28:52 The Future of UX Research

31:18 Skills for Emerging Designers

35:54 The Role of AI in Design

37:57 Ethics of AI and Personal Data

39:59 Innovative Tools and Methods

41:35 Designing for User Satisfaction

Connect with Nick

* Website: https://gauge.io/

* LinkedIn: https://www.linkedin.com/in/nickcawthon-ux-digital-agency-product-design-leadership/

* X: https://x.com/ncawthon

* Other: http://nickcawthon.com/

Connect with Vit

* Website: https://vitlyoshin.com/contact/

* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/

* X: https://x.com/vitlyoshin

Vit’s Projects

* Podcast: https://www.anhourofinnovation.com/

* AI Assistant to build apps: https://appforgelab.com/