In this episode, Mehmet sits down with Tamara Laine, Founder and CEO of MPWR, to explore how AI and agentic systems are reshaping the future of lending.

They discuss why traditional credit scores fail gig workers and modern professionals, how alternative data can unlock financial inclusion, and what it really means to build human-centered fintech in an AI-first world.

From explainable AI to ethical lending and the future of work, this conversation goes deep into how finance must evolve to serve the new economy.

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👤 About the Guest: Tamara Laine

Tamara Laine is the Founder and CEO of MPWR, an AI-native fintech company building agentic ecosystems for inclusive lending.

With a background in journalism and startups, Tamara focuses on system-level change in finance, helping underserved and “thin-file” borrowers access fair credit through behavioral and alternative data.

She is a strong advocate for ethical AI, transparency, and human-centered technology design.

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🔑 Key Takeaways

• Why traditional credit scores exclude more than 50% of potential borrowers

• How AI enables more accurate and fair lending decisions

• The role of behavioral and alternative data in modern credit models

• Why explainability is critical in financial AI systems

• How regulation can enable or block innovation

• The future of work and its impact on financial systems

• Why purpose still matters in an AI-driven economy

• How founders can build startups through complementary partnerships

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🎯 What You’ll Learn

By listening to this episode, you’ll learn:

• How agentic AI is changing lending infrastructure

• Why gig workers and freelancers are underserved by banks

• How financial identity may become portable in the future

• What “human-in-the-loop” means in fintech

• How to design ethical, transparent AI systems

• Why unintended consequences matter in technology

• How entrepreneurship is evolving in the AI era

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⭐ Episode Highlights

• The limitations of legacy credit scoring systems

• AI-powered cashflow and behavior analysis

• Explainable lending decisions in real time

• Financial inclusion for nomadic workers

• Surveillance vs. personalization in finance

• Universal Basic Income and purpose

• The rise of one-person, AI-powered companies

• Founder dynamics and team building

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⏱️ Timestamps

00:00 – Introduction & Guest Background

02:00 – Why Credit Systems Are Broken

04:00 – Gig Economy and Underserved Borrowers

06:00 – Alternative Data in Lending

08:30 – Portable Financial Identity

11:00 – Regulation and Global Credit

13:30 – Explainable AI in Finance

15:30 – Trust, Transparency, and Surveillance

18:00 – Ethical AI and Unintended Consequences

22:00 – Future of Work and Solopreneurs

25:30 – Universal Income and Purpose

29:00 – Building Startups Through Partnerships

32:00 – Final Thoughts & Where to Find Tamara

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🔗 Resources Mentioned

• MPWR Website: https://mpwrai.com/

• MPWR Money Platform: https://mpwr.money

• Connect with Tamara on LinkedIn: https://www.linkedin.com/in/tamaralaine/

In this episode of The CTO Show with Mehmet, Mehmet sits down with Ewelina Kurtys, Strategic Advisor at FinalSpark, to explore one of the most radical frontiers in technology: biological computing powered by living neurons.

FinalSpark is building next-generation processors using human neurons instead of silicon, aiming to solve AI’s biggest challenge: energy efficiency and scalability.

From AI infrastructure to neuroscience, ethics, and commercialization, this conversation dives deep into what it really takes to move computing beyond chips and into biology.

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About the Guest: Ewelina Kurtys

Ewelina Kurtys is a neuroscientist and Strategic Advisor at FinalSpark. With a background spanning academia, startups, and artificial intelligence, she now works at the intersection of AI, hardware, and biology.

At FinalSpark, she helps shape the strategy behind building the world’s first remote-access biocomputing platform using living neurons.

https://www.linkedin.com/in/ewelinakurtys/

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🔍 Key Takeaways

• Why silicon is reaching its physical and economic limits

• How living neurons are up to 1 million times more energy efficient than traditional chips

• The hidden cost of AI and why current models are unsustainable

• How biological processors are programmed and trained

• Why biocomputing may reshape AI infrastructure

• The ethical and regulatory dimensions of using human cells

• Why centralized “bio-servers” may replace traditional data centers

• What it takes to commercialize deep science innovation

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🎯 What You’ll Learn

By listening to this episode, you will learn:

• How biological computing works in practice

• Why AI’s future depends on new hardware paradigms

• What makes neurons powerful information processors

• How startups can compete with Big Tech through radical innovation

• The investment and research timeline behind deep tech breakthroughs

• How biocomputing could reduce AI’s carbon footprint

• Where philosophy, ethics, and engineering intersect

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⏱️ Episode Highlights & Timestamps

00:00 – Introduction to biocomputing and FinalSpark

02:00 – Why living neurons beat silicon on efficiency

04:00 – From AI software to biological hardware

06:00 – The real cost of running large AI models

08:00 – How neurons are programmed and trained

10:00 – Using dopamine and chemical signals for learning

12:00 – Sourcing stem cells and neuron lifespan

14:00 – Commercial use cases for bio-computers

15:00 – Why portable bio-AI is unlikely (for now)

17:00 – Climate impact and energy efficiency

18:30 – Open innovation and university partnerships

20:30 – Ethics and public perception

22:00 – Responding to skeptics

23:00 – Is it still “artificial” intelligence?

24:30 – Brain-computer interfaces and future implications

26:00 – The 10-year roadmap and funding plans

27:30 – Advice for young scientists

28:30 – Where to learn more

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📚 Resources Mentioned

• FinalSpark Website: https://finalspark.com

• FinalSpark Research Paper (Frontiers): https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2024.1376042/full

In this episode of The CTO Show with Mehmet, Mehmet sits down with Peadar Coyle, Co-Founder and CTO of AudioStack, to explore how AI is transforming audio production from a creative craft into scalable infrastructure.

Peadar shares how AudioStack built production-grade AI systems for media and brands worldwide, why audio is becoming a systems problem, and how founders and CTOs can balance speed, quality, and creativity in the age of generative AI.

From programmatic advertising in the UAE to shipping daily in fast-moving startups, this conversation dives deep into the technical, strategic, and cultural realities of building AI-powered platforms.

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👤 About the Guest: Peadar Coyle

Peadar Coyle is the Co-Founder and CTO of AudioStack, an AI-native audio production platform serving global media and entertainment companies.

With a background in data engineering, open-source development, and philosophy, Peadar brings a rare blend of technical depth and human-centered thinking to AI systems design. He is passionate about building reliable, ethical, and scalable infrastructure for creative industries.

https://www.linkedin.com/in/peadarcoyle/

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🔑 Key Takeaways

• Why audio production is shifting from “creative workflows” to “AI infrastructure”

• How AI accelerates creativity instead of replacing it

• The importance of shipping small, fast, and safely

• Why observability and human-in-the-loop systems still matter

• How to scale generative AI without losing trust

• What founders get wrong about “AI prototypes vs real products”

• How to build strong engineering culture in fast-changing environments

• Why the last 10% of AI products is still the hardest

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🎯 What You’ll Learn in This Episode

• How AudioStack automated large-scale localized audio campaigns

• How to balance customer demands with technical quality

• How CTOs should rethink productivity with AI agents

• What “production-ready AI” really means

• How AI is changing product, engineering, and leadership roles

• Why creativity remains a human advantage

• How to prepare teams for continuous technological change

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⏱️ Episode Highlights & Timestamps

00:00 – Introduction & Peadar’s background

02:00 – Why AudioStack was founded

03:30 – Audio as infrastructure vs creativity

05:00 – How AI accelerates creative iteration

07:00 – UAE use case: Programmatic localized ads

09:00 – Orchestration, latency, and reliability challenges

11:00 – Observability and human-in-the-loop AI

14:00 – Evaluating AI systems in production

16:00 – Ethics, copyright, and trust in generative audio

18:30 – Shipping fast: Engineering culture at AudioStack

20:30 – Balancing customer needs with technical debt

23:00 – Building culture in the AI era

26:00 – How CTO roles are changing

28:00 – Product + Engineering convergence

30:00 – What makes great audio in the future

32:00 – Advice for founders in creative AI

35:00 – Final thoughts and recommendations

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📚 Resources Mentioned

• AudioStack Platform: https://www.audiostack.ai

• Claude Code & AI Agents

• AI Evaluation & Observability Tools

• ISO/IEC 42001 (AI Management Systems)

• SOC 2 Compliance Standards