The CTO Show with Mehmet Gonullu

In this conversation, Mehmet sits down with Amos Bar-Joseph, Founder and CEO of Swan AI, to unpack what it really means to build an autonomous company.Amos shares how he moved away from the traditional “growth at all costs” startup model toward a lean, intelligence-driven approach powered by human-AI collaboration.Together, they discuss: • Why headcount is no longer the main growth lever • How founders can become “100x operators” with AI • The future of GTM in an agentic world • Why autonomy beats bureaucracy • How to scale without losing cultureThis is a deep dive into the next-generation startup playbook.⸻👤 About the GuestAmos Bar-Joseph is the Founder and CEO of Swan AI.A serial entrepreneur with two prior exits, Amos is building one of the first truly autonomous businesses. His work focuses on human-AI collaboration, agentic workflows, and redefining how modern companies scale.He is also the author of The Big Shift newsletter and a leading voice on AI-native organizations.⸻🎯 Key Takeaways • Startups can scale with intelligence, not headcount • AI should amplify human “zones of genius,” not replace them • GTM success depends on how buyers want to buy, not how founders want to sell • Context engineering is becoming a core GTM skill • Flat, autonomous teams require stronger leadership, not less • Decision velocity is the biggest startup advantage • Capital matters, but leverage matters more⸻📚 What You’ll LearnBy listening to this episode, you’ll learn:✅ How to design an autonomous business model✅ Where humans should stay in the loop with AI✅ How to use agents to accelerate product-market fit✅ Why relevance beats personalization in outreach✅ How to build scalable GTM systems✅ How leadership changes in flat organizations✅ How to preserve culture while scaling⸻⏱️ Episode Highlights & Timestamps00:00 – Introduction & Amos’ background02:00 – Why the traditional startup model is broken04:30 – Building with three people and AI07:00 – Zone of Genius + AI amplification09:30 – Human-in-the-loop GTM strategy12:00 – Choosing the right growth model15:00 – Selling with empathy18:00 – Personalization vs relevance21:00 – Context engineering in GTM24:00 – AI and product-market fit27:00 – Decision velocity as a startup advantage31:00 – Autonomous leadership challenges35:00 – Culture without hierarchy38:00 – Fundraising in an AI-native world41:00 – The “Swan” philosophy vs unicorns44:00 – Future vision for Swan AI46:00 – Where to follow Amos47:00 – Closing remarks⸻🔗 Resources Mentioned • Swan AI Platform: https://getswan.com/ • Amos Bar-Joseph on LinkedIn: https://www.linkedin.com/in/amos-bar-joseph/ • Autonomous GPT (ChatGPT Store): https://chatgpt.com/g/g-6800e20892b8819181df24a31ccdbf96-autonamos

In this deep and thought-provoking episode, Mehmet sits down with Alessandro Grampa, Founder of Whole Grain Wisdom, to explore what it truly means to be a “Quantum Founder” in the age of AI, hyper-growth, and burnout.From panic attacks and founder stress to meditation, neuroscience, ancient wisdom, and artificial intelligence, Alessandro shares his personal transformation and the framework he now uses to help high performers reconnect with purpose, resilience, and inner coherence.This is not a typical startup conversation. It is a masterclass on conscious leadership, mental resilience, and building meaningful companies without losing yourself in the process.⸻👤 About the Guest: Alessandro GrampaAlessandro Grampa is the Founder of Whole Grain Wisdom, a platform that bridges modern science with ancient wisdom to help entrepreneurs and high performers unlock their highest potential.With over 13 years of entrepreneurial experience, Alessandro transitioned from hustle-driven burnout to becoming a guide for founders seeking balance, clarity, and purpose. His work integrates neuroscience, meditation, biohacking, quantum physics, and spiritual practices.Today, he works with select founders through deep transformation programs focused on mind, body, and consciousness alignment.https://www.linkedin.com/in/alessandro-grampa/⸻🎯 Key Takeaways • Why 3 out of 4 founders struggle with mental and emotional health • How external validation drives burnout in entrepreneurship • What “Quantum Founder” really means • The hidden role of meditation and retreats among elite founders • Why consistency alone is not enough for real growth • How AI can amplify self-awareness and consciousness • The link between neuroscience, ancient wisdom, and leadership • How founders can rewire their mindset for long-term success • Why purpose matters more than ever in the AI era⸻📚 What You’ll Learn in This EpisodeBy listening to this episode, you’ll learn: • How to manage founder stress and prevent burnout • Why many successful entrepreneurs still feel “empty” • How to develop inner clarity in high-pressure environments • The difference between hustle culture and conscious growth • How top founders use meditation, retreats, and reflection • How to use AI as a tool for self-development • Why consciousness is becoming a leadership advantage • How to reconnect with your original purpose as a founder⸻⏱️ Episode Highlights & Timestamps00:00 – Introduction and Alessandro’s journey02:10 – From panic attacks to meditation05:30 – Discovering Eastern philosophy and biohacking08:40 – Why most founders hide mental struggles11:50 – External validation vs inner coherence15:20 – What is a “Quantum Founder”?18:30 – How elite founders use meditation retreats22:10 – Recognition vs repetition in personal growth26:40 – Science meets ancient wisdom30:50 – Consciousness and reality perception35:10 – AI as a tool for self-awareness38:45 – The future of leadership in the AI era42:30 – When is the right time to start inner work?45:10 – How to work with Alessandro47:00 – Final reflections and closing⸻🔗 Resources Mentioned • Whole Grain Wisdom: https://wholegrainwisdom.com

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.⸻👤 About the Guest: Tamara LaineTamara 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.⸻🔑 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⸻🎯 What You’ll LearnBy 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⸻⭐ 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⸻⏱️ Timestamps00:00 – Introduction & Guest Background02:00 – Why Credit Systems Are Broken04:00 – Gig Economy and Underserved Borrowers06:00 – Alternative Data in Lending08:30 – Portable Financial Identity11:00 – Regulation and Global Credit13:30 – Explainable AI in Finance15:30 – Trust, Transparency, and Surveillance18:00 – Ethical AI and Unintended Consequences22:00 – Future of Work and Solopreneurs25:30 – Universal Income and Purpose29:00 – Building Startups Through Partnerships32:00 – Final Thoughts & Where to Find Tamara⸻🔗 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.⸻About the Guest: Ewelina KurtysEwelina 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/⸻🔍 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⸻🎯 What You’ll LearnBy 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⸻⏱️ Episode Highlights & Timestamps00:00 – Introduction to biocomputing and FinalSpark02:00 – Why living neurons beat silicon on efficiency04:00 – From AI software to biological hardware06:00 – The real cost of running large AI models08:00 – How neurons are programmed and trained10:00 – Using dopamine and chemical signals for learning12:00 – Sourcing stem cells and neuron lifespan14:00 – Commercial use cases for bio-computers15:00 – Why portable bio-AI is unlikely (for now)17:00 – Climate impact and energy efficiency18:30 – Open innovation and university partnerships20:30 – Ethics and public perception22:00 – Responding to skeptics23:00 – Is it still “artificial” intelligence?24:30 – Brain-computer interfaces and future implications26:00 – The 10-year roadmap and funding plans27:30 – Advice for young scientists28:30 – Where to learn more⸻📚 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.⸻👤 About the Guest: Peadar CoylePeadar 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/⸻🔑 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⸻🎯 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⸻⏱️ Episode Highlights & Timestamps00:00 – Introduction & Peadar’s background02:00 – Why AudioStack was founded03:30 – Audio as infrastructure vs creativity05:00 – How AI accelerates creative iteration07:00 – UAE use case: Programmatic localized ads09:00 – Orchestration, latency, and reliability challenges11:00 – Observability and human-in-the-loop AI14:00 – Evaluating AI systems in production16:00 – Ethics, copyright, and trust in generative audio18:30 – Shipping fast: Engineering culture at AudioStack20:30 – Balancing customer needs with technical debt23:00 – Building culture in the AI era26:00 – How CTO roles are changing28:00 – Product + Engineering convergence30:00 – What makes great audio in the future32:00 – Advice for founders in creative AI35:00 – Final thoughts and recommendations⸻📚 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

In this episode of The CTO Show with Mehmet, Mehmet sits down with David Soileau, Co-Founder and CRO of Gophr, to explore how modern software, AI, and disciplined leadership are transforming industrial logistics.David shares his journey from the Marine Corps to building a nationwide on-demand delivery platform. He explains how Gophr pivoted during COVID and natural disasters, rebuilt its business model around accountability, and scaled with minimal overhead.The conversation dives deep into operational excellence, trust in B2B platforms, AI-powered logistics, and what it really takes to survive in a low-margin, high-pressure industry.⸻👤 About the Guest: David SoileauDavid Soileau is the Co-Founder and Chief Revenue Officer of Gophr, an on-demand logistics platform serving industrial, pharmaceutical, and enterprise customers across the United States.Before entrepreneurship, David spent 12 years in the U.S. Marine Corps and worked in industrial operations. His background in discipline, execution, and mission-driven leadership has shaped Gophr’s culture and growth strategy.Today, he leads revenue, partnerships, and expansion efforts while helping enterprises modernize their delivery infrastructure.⸻🎯 Key Takeaways • Why accountability and visibility are the foundation of trust in logistics • How Gophr successfully pivoted during COVID and hurricanes • The role of AI in vehicle selection, documentation, and compliance • How to scale a logistics company with only five full-time staff • Why low-margin industries demand technology-first thinking • Lessons from military leadership applied to startup execution • How to balance automation with human oversight⸻📚 What You’ll LearnBy listening to this episode, you’ll learn: • How to design logistics platforms that enterprise buyers actually trust • Why real-time tracking and digital documentation matter more than features • How AI can reduce operational errors in physical infrastructure businesses • How founders can grow under pressure without burning cash • What operational excellence looks like in practice • How to build resilience into your business model⸻⏱️ Episode Highlights & Timestamps00:00 – Introduction and David’s background02:10 – From marketplace to industrial logistics platform04:30 – The hidden costs of unreliable delivery07:20 – Building accountability through tracking and visibility10:15 – Operational metrics that matter in logistics13:40 – Scaling discipline and execution16:30 – AI-powered features at Gophr18:50 – Human-in-the-loop vs full automation22:00 – Risk management during crises24:40 – Margins and running lean in logistics27:10 – Military leadership in startups30:45 – Goal-setting and execution frameworks34:20 – Common founder mistakes in operations-heavy businesses36:50 – Gophr’s growth vision39:00 – Final advice for entrepreneurs⸻🔗 Resources Mentioned • Gophr Website: https://gophrapp.com/ • David Soileau on LinkedIn: https://www.linkedin.com/in/davidtheguy/

In this episode, Mehmet sits down with Andrew Ackerman, two-time founder, early-stage investor with 70+ investments, accelerator leader, entrepreneurship professor, and author of The Entrepreneur’s Odyssey.Andrew shares hard-earned insights from running accelerator programs, investing across decades, and coaching founders at their most fragile moments. The conversation dives deep into why startups fail, what truly separates winning founders, how coachability beats ego, and why storytelling is more powerful than advice.They also explore how AI is reshaping entrepreneurship, why the bar for founders keeps rising, and why building faster is no longer a competitive advantage on its own.⸻👤 About the GuestAndrew Ackerman is a seasoned entrepreneur, investor, educator, and author. • Two-time startup founder • Investor in 70+ early-stage companies • Former accelerator leader (DreamIt) • Entrepreneurship professor • Author of The Entrepreneur’s Odyssey: A Novel Approach to Startup SuccessAndrew has spent decades working at the intersection of founders, investors, and large enterprises, giving him a rare inside view of what actually makes startups succeed or fail.http://www.linkedin.com/in/andrewbackerman⸻🧠 Key Takeaways • Startups fail due to broken links, not a single bad idea • Coachability matters more than confidence or experience • The best founders hold strong opinions loosely • Storytelling drives action better than direct advice • AI lowers the cost of building, but raises the bar for funding • First-mover advantage is weak without a real moat • Empathy is the hidden superpower behind great founders, salespeople, and storytellers⸻🎓 What You’ll Learn • Why startups should be viewed as chains, not ropes • How accelerators compress the learning curve for investors and founders • How to spot coachable founders early • Why experimentation beats gut instinct • How to test ideas cheaply before building • Why many founders hide in their comfort zone instead of doing the hard work • How AI changes the “why now” question for startups⸻⏱️ Episode Highlights & Timestamps00:00 – Introduction and Andrew’s background03:00 – Why running an accelerator changes how you see startups07:00 – Angel investing vs accelerator investing10:00 – Startups as chains, not ropes12:30 – Why startups fail in different ways14:30 – The one trait that separates great founders18:00 – Coachability, ego, and founder decision-making22:00 – Can entrepreneurship really be taught?25:00 – The “looking for money under the streetlight” founder trap28:00 – Why storytelling beats direct advice32:00 – SeatGeek origin story and early validation lessons36:00 – Empathy as a core founder skill40:00 – AI, hype, and what’s actually changing for startups45:00 – Why the investor bar keeps rising50:00 – Final advice for founders and investors⸻📚 Resources Mentioned • The Entrepreneur’s Odyssey by Andrew Ackerman: https://www.amazon.com/Entrepreneurs-Odyssey-Approach-Startup-Success/dp/1032883545/ref=tmm_pap_swatch_0 • Andrew’s website: https://www.andrewbackerman.com/

In this episode of The CTO Show with Mehmet, I’m joined by Max Ivey, known as The Blind Blogger and a leading voice in digital accessibility.Max shares his remarkable journey from growing up in a family-run carnival business to becoming an accessibility advisor helping companies rethink how they design products, websites, and AI tools. We go deep into why accessibility is not a legal checkbox but a business, UX, and growth advantage, and why most modern AI tools are still failing real users.This conversation is a masterclass for founders, product leaders, designers, and executives who want to build inclusive, scalable, and future-proof products.⸻👤 About the GuestMax Ivey is an accessibility expert, entrepreneur, speaker, and host of The Accessibility Advantage podcast. Blind since birth, Max brings decades of lived experience navigating technology, entrepreneurship, and digital products without sight.He advises startups and enterprises on building truly accessible and usable products, helping them move beyond fear-driven compliance toward inclusive design that benefits all users.⸻🧠 Key Takeaways • Accessibility improves UX for everyone, not just people with disabilities • WCAG compliance alone does not guarantee usability • Many AI tools are unintentionally scaling inaccessibility • Inclusive design builds brand loyalty, trust, and advocacy • Small companies can outcompete big players by embracing accessibility early • Designing with a keyboard-first mindset changes everything⸻📚 What You’ll Learn in This Episode • Why accessibility should be treated as a competitive advantage • How blind and disabled users actually navigate digital products • The hidden accessibility debt in AI-generated content • Practical principles for accessible and inclusive product design • The real business case behind accessibility, beyond legal risk • How founders can avoid common UX mistakes that cost revenue⸻⏱️ Episode Highlights & Timestamps00:00 – Introduction and welcome02:10 – Max Ivey’s journey from carnival business to accessibility advocate06:40 – Why Max chose to be open about his disability online10:30 – Teaching himself HTML to get online14:50 – How early tech limitations shaped Max’s mindset18:30 – Why many AI tools are still inaccessible23:10 – The danger of scaling inaccessible AI content27:40 – Why WCAG compliance is not enough31:20 – Keyboard-first navigation and real-world usability36:10 – Minimalist design and why complexity breaks accessibility41:30 – Accessibility, trust, and customer loyalty45:20 – The $21 trillion accessibility market opportunity49:40 – Accessibility as a growth and branding strategy54:10 – Perseverance vs stubbornness in entrepreneurship58:30 – Advice for founders facing adversity01:03:10 – Where to find and connect with Max01:05:00 – Final thoughts and closing⸻🔗 Resources Mentioned • Max Ivey’s website: theaccessibilityadvantage.com • Connect with Max on LinkedIn: Maxwell Ivey: https://www.linkedin.com/in/maxwellivey/ • The Accessibility Advantage podcast: https://podcasts.apple.com/us/podcast/the-accessibility-advantage/id1740242884?uo=4

In this episode of The CTO Show with Mehmet, I’m joined by Ahmad Saleem, Founder and CEO of Podyssey.Ahmad’s journey is anything but linear. From working as a geologist in mining and natural resources to earning a PhD in economics, moving into private equity, and eventually founding an AI startup, his path reflects deep curiosity, resilience, and systems thinking.We dive into why podcast discovery is fundamentally broken, how AI and natural language processing can unlock the real value hidden inside long-form audio, and what it takes to build and scale a product in an uncertain, fast-moving market.This conversation blends founder storytelling, product strategy, and honest reflections on failure, team building, and the future of content discovery.⸻👤 About the GuestAhmad Saleem is the Founder and CEO of Podyssey, an AI-powered search engine designed to help people discover specific insights within podcasts rather than just episodes.With a background spanning geology, economics, private equity, and natural language processing, Ahmad has been involved in nearly 20 ventures across his career. His work today focuses on applying AI to large-scale content discovery problems, particularly in long-form audio and multilingual environments.https://www.linkedin.com/in/ahmad-saleem-ansari/⸻🧠 Key Takeaways • Why podcast discovery is harder than ever despite the explosion of content • How AI and NLP enable searching inside conversations, not just titles • The difference between finding podcasts and finding relevant moments • Why categories and genres no longer work for modern podcast discovery • Lessons learned from nearly 20 ventures and how failure reshapes founders • How to build lean, distributed teams that move fast without sacrificing clarity • Where AI agents fit and do not fit in long-form content consumption⸻🎯 What You’ll Learn • How Podyssey is rethinking podcast discovery at a global scale • Why transcripts alone are not enough to understand context • How founders should think about feature creep after product-market fit • What changes when you build AI products in a remote, asynchronous world • How experience with failure changes decision-making and leadership⸻⏱ Episode Highlights & Timestamps • 00:00 Introduction and Ahmad’s background • 02:00 From geology and mining to economics and startups • 05:00 Why podcast discovery is broken • 09:00 AI, accents, transcription, and context challenges • 12:00 From episodes to snippets: rethinking podcast consumption • 15:00 Podyssey’s business model and monetization paths • 17:00 Avoiding feature overload after product-market fit • 20:00 Building lean, remote AI teams • 25:00 AI agents and the future of long-form content • 27:00 Failure, resilience, and restarting as a founder • 33:00 The global future of podcasting and multilingual discovery⸻🔗 Resources Mentioned • Podyssey platform: https://www.podyssey.com/

Agentic AI is moving faster than enterprise readiness.Boards are pushing adoption. Teams are deploying agents at speed. But security, control, and operational discipline are lagging behind.In this episode, Mehmet sits down with Craig McLuckie, the co-creator of Kubernetes and founder of Stacklok, to unpack why most agentic AI initiatives break after the demo and what enterprises must do differently to make them durable, secure, and production-ready.From MCP and context engineering to eval-driven development and why AI agents should never be treated like interns, this conversation goes deep into the realities CTOs, VPs of Engineering, and security leaders are facing right now.This is not a hype conversation. It’s an operator’s reality check for 2026.⸻👤 About the GuestCraig McLuckie is a foundational figure in modern cloud infrastructure. He is the co-creator of Kubernetes, founder of the Cloud Native Computing Foundation, and former VMware executive behind the Tanzu portfolio.Today, Craig is the founder and CEO of Stacklok, where he is focused on helping enterprises securely connect agentic AI systems to real-world infrastructure through open, controlled, and auditable platforms.https://www.linkedin.com/in/craigmcluckie/⸻🧠 Key Takeaways • Why agentic AI represents a true epoch shift, not just another tooling cycle • The real difference between demos, POCs, and production AI systems • Why MCP is powerful but dangerous without proper control layers • How context engineering is becoming more important than writing code • Why eval-driven development replaces test-driven development in AI systems • How enterprises should think about permissions, scope, and agent autonomy • Why most AI failures are workflow problems, not model problems • What 2026 realistically looks like for agentic AI adoption in the enterprise⸻🎯 What You’ll Learn • How to operationalize agentic AI without exposing your infrastructure • Why treating AI agents like humans is a security mistake • How to design guardrails without slowing teams down • Where CTOs should focus investment to move from hype to ROI • How leadership metrics and engineering evaluation must evolve in the AI era⸻⏱ Episode Highlights & Timestamps • 00:00 – Introduction and Craig’s journey from Google to Kubernetes • 03:10 – Why agentic AI feels like a historic inflection point • 06:05 – MCP explained and where enterprises get it wrong • 10:45 – The security risks nobody is talking about • 14:20 – Why AI agents should never be treated like interns • 18:30 – The danger of permission sprawl and tool pollution • 23:10 – Why most AI initiatives fail after the demo • 28:40 – Eval-driven development vs traditional software thinking • 34:15 – Context engineering as the new leverage point • 38:50 – How engineering leadership and metrics must change • 43:30 – What realistic agent adoption looks like in 2026 • 46:20 – Open source, ToolHive, and building durable AI platforms⸻🔗 Resources Mentioned • Stacklok: http://stacklok.com/ • ToolHive (Open Source MCP Platform): https://stacklok.com/toolhive/

In this episode, Mehmet sits down with Ghazenfer Mansoor, Founder and CEO of Technology Rivers, to unpack why so many software products fail quietly and what actually separates ideas that ship and scale from those that die early.Drawing on two decades of experience and over 60 shipped applications, Ghazenfer shares hard-earned lessons on customer discovery, feature bloat, technical debt, AI with real ROI, and building system-powered businesses that scale sustainably, especially in regulated industries like healthcare.This is a practical, no-fluff conversation for founders, CTOs, and operators building real products in a noisy AI-driven world.⸻👤 About the GuestGhazenfer Mansoor is the Founder and CEO of Technology Rivers, a custom software development company with deep expertise in healthcare, HIPAA-compliant systems, and AI-driven operational automation.He began his career as an early startup engineer, entered mobile development in its earliest days, and has since helped build and scale dozens of products. Ghazenfer is also the author of the upcoming book Beyond the Download, focused on building mobile apps people actually love and use.https://www.linkedin.com/in/gmansoor/⸻🧠 Key Takeaways • Why most startups fail by building solutions before validating problems • How feature bloat quietly destroys velocity, quality, and scalability • The hidden cost of technical debt and why postponing it always backfires • Why AI tools fail without clean data and mapped workflows • How regulated industries can innovate without breaking compliance • The shift from people-powered growth to system-powered growth • Why founders should think like acquirers from day one⸻🎯 What You’ll Learn • How to identify the real problem worth solving before writing code • How to prioritize features without killing your product roadmap • Where AI delivers real ROI versus where it’s just pitch-deck noise • How to design internal systems that create defensibility and valuation • Why compliance and innovation are not opposites • How to build products that users return to, not just download⸻⏱️ Episode Highlights & Timestamps • 00:02 Ghazenfer’s journey from early mobile engineering to healthcare software • 05:10 Why most startup ideas fail before reaching scale • 08:00 Feature race vs focus and why more features hurt products • 10:15 Technical debt explained in simple, practical terms • 14:00 AI in practice vs AI in pitch decks • 17:30 Why workflows matter more than tools • 19:45 Innovating in healthcare without breaking HIPAA • 23:00 RAG, hallucinations, and building safe AI systems • 26:45 Beyond the Download and building retention-first products • 35:30 Moving from people power to system power growth • 41:00 Thinking like an acquirer from day one • 46:00 Final advice on AI, innovation, and staying relevant⸻📚 Resources Mentioned• Technology Rivers https://technologyrivers.com/ • Beyond the Download by Ghazenfer Mansoor: https://technologyrivers.com/l/beyond-the-download/ • HIPAA compliance principles • Retrieval-Augmented Generation (RAG) architectures • AI tools including Claude, ChatGPT, and Gemini

In this episode of The CTO Show with Mehmet, Mehmet sits down with Michael Ferranti, a seasoned tech executive and product leader at Unleash, to explore why DevOps alone can no longer meet the reliability, speed, and risk demands of modern software systems.From real-world outages at Google and Cloudflare to the rise of AI-driven delivery, this conversation introduces FeatureOps as the missing control plane that allows teams to move faster without breaking production.⸻👤 About the GuestMichael Ferranti is a tech executive with over a decade of experience across DevOps tooling, infrastructure software, open source, and enterprise platforms. He has played key roles in scaling developer-focused technologies and advises organizations on balancing innovation, reliability, and governance at scale. Today, he focuses on FeatureOps as a foundational capability for modern engineering teams.⸻🧠 Key Takeaways • DevOps optimizes deployment, but FeatureOps governs runtime behavior • Many large-scale outages are caused by “big bang” releases without kill switches • Feature flags are not just for UI experiments, they are safety mechanisms • FeatureOps enables faster shipping and lower risk at the same time • AI-driven engineering increases the need for runtime control, not less⸻🎯 What You’ll Learn • Why DevOps alone breaks down at scale • How FeatureOps differs from traditional feature flagging • Lessons from Google and Cloudflare outages • When open source helps and when it complicates GTM • How AI changes release management and reliability decisions • Why human-in-the-loop control still matters in autonomous systems⸻⏱️ Episode Highlights & Timestamps • 00:02 – Michael’s journey from early cloud evangelism to FeatureOps • 04:00 – Scaling Portworx and why technology alone is not enough • 07:30 – Open source as a GTM strategy, myths and realities • 15:00 – Kubernetes, scale assumptions, and overengineering traps • 21:30 – What FeatureOps actually is and why it matters • 24:30 – Google outage case study and the cost of big bang releases • 27:30 – Cloudflare, kill switches, and runtime control • 31:00 – FeatureOps vs DevOps explained clearly • 35:00 – AI in release decisions and risk management • 43:00 – Human-in-the-loop engineering and future architectures⸻🔗 Resources Mentioned • Unleash Feature Management Platform: https://www.getunleash.io/ • Google SRE Handbook • DORA Reports on High-Performing Engineering Teams • ThoughtWorks Feature Management Practices⸻🔗 Connect with the Guest • Michael Ferranti on LinkedIn: https://www.linkedin.com/in/ferrantim/

In this episode, Mehmet Gonullu sits down with Nat Natarajan, Chief Operating Officer and Chief Product Officer at Globalization Partners, to explore what it really takes to deploy AI in highly regulated environments.From labor laws and compliance across dozens of countries to human-in-the-loop AI systems, Nat shares how Globalization Partners built explainable, trustworthy AI that enterprises can actually rely on. This is a grounded, operator-level conversation on moving beyond AI hype toward real productivity and trust.⸻👤 About the GuestNat Natarajan is the Chief Operating Officer and Chief Product Officer at Globalization Partners, a pioneer in global employment solutions. He previously held senior leadership roles at companies including TurboTax (Acquired by Intuit), PayPal, RingCentral, Ancestry.com, and Travelocity. Nat brings decades of experience at the intersection of technology, regulation, and large-scale enterprise systems.https://www.linkedin.com/in/natrajeshnatarajan/⸻🧠 Key Takeaways • Why black-box AI fails in regulated industries • How human-in-the-loop design builds trust and adoption • The role of proprietary, vetted data in enterprise AI • Where general-purpose LLMs fall short for compliance-heavy use cases • Why AI should augment humans, not replace them • How CHROs and boards are rethinking AI as a “digital workforce”⸻🎯 What You’ll Learn • How to design AI systems that can explain their decisions • When to keep humans in the loop and when automation works best • How enterprises can deploy AI responsibly without slowing innovation • What makes AI adoption succeed inside large, global organizations • Why regulated complexity is an advantage, not a blocker, for AI⸻⏱️ Episode Highlights & Timestamps • 00:00 – Introduction and Nat’s background • 02:00 – Why regulated environments are ideal for AI, not hostile to it • 05:00 – Lessons from TurboTax and encoding legal reasoning into systems • 08:00 – Designing AI that avoids the black-box problem • 12:00 – Human-in-the-loop systems and guardrails • 16:00 – Why proprietary data beats generic models • 19:00 – Enterprise vs startup AI adoption dynamics • 23:00 – AI as a collaborator inside HR teams • 27:00 – Explainability, trust, and employee-facing AI • 32:00 – The CHRO’s role in an AI-powered workforce • 36:00 – From hype to real productivity with agentic AI • 40:00 – Final thoughts and advice for leaders adopting AI⸻📚 Resources Mentioned • Globalization Partners : https://www.globalization-partners.com/ • GIA:  http://www.g-p.com/gia • Prediction Machines (Updated & Expanded Edition) – referenced by Mehmet

AI models are becoming commoditized, but deploying AI systems that deliver real ROI remains hard. In this episode, Mehmet sits down with Bryan Wood, Principal Architect at Snorkel AI, to unpack why data-centric AI, evaluation, and domain expertise are now the true differentiators.Bryan shares lessons from working with frontier AI labs and highly regulated enterprises, explains why most AI projects stall before production, and breaks down what it actually takes to deploy AI safely and at scale.⸻👤 About the GuestBryan Wood is a Principal Architect at Snorkel AI, where he works closely with frontier AI labs and enterprises to design high-quality, AI-ready datasets and evaluation frameworks.He brings over 20 years of experience in financial services, with a unique background spanning banking, engineering, and fine art. Bryan specializes in data-centric AI, programmatic labeling, AI evaluation, and deploying AI systems in high-compliance environments.https://www.linkedin.com/in/bryanmwood/⸻🧠 Key Takeaways • Why AI success is less about models and more about data and evaluation • How enterprises misunderstand ROI and why most projects stall before production • The difference between benchmark performance and real-world trust • Why evaluation must be bespoke, not off-the-shelf • How frontier labs approach data as true R&D • Why partnering beats building AI entirely in-house today • What’s realistic (and unrealistic) about autonomous agents in the near term⸻🎯 What You’ll Learn • How to move from AI experimentation to production deployment • How to design data that reflects real enterprise workflows • How to identify where AI systems actually fail, and why • Why regulated industries are proving grounds, not laggards • How startups can overcome data and talent constraints • Where AI is heading beyond today’s LLM plateau⸻⏱️ Episode Highlights & Timestamps00:00 – Introduction & Bryan’s background02:30 – Why data is now the real AI bottleneck05:00 – Models are commoditized. So what actually matters?07:45 – Why AI evaluation is harder than building AI11:30 – Enterprise misconceptions about AI readiness15:10 – Hallucinations, RAG failures, and finding the real problem18:40 – Why most AI projects fail to show ROI22:30 – Partnering vs building AI in-house26:00 – AI in regulated industries: myth vs reality30:10 – Startups, cold start problems, and data moats33:40 – Scaling data operations with small teams36:00 – What’s next: agents, data complexity, and AI timelines39:00 – Final thoughts and where AI is really heading⸻📌 Resources Mentioned • Snorkel AI – Data-centric AI and programmatic labeling: https://snorkel.ai/ • Enterprise AI evaluation frameworks • Frontier AI lab research practices • MIT studies on AI ROI and enterprise adoption

Live events generate massive attention, yet most venues have no idea who is actually attending. In this episode, Mehmet Gonullu sits down with Matt Zarracina, CEO and Co-Founder of True Tickets, to unpack the hidden infrastructure problem behind ticketing, identity, and audience ownership.Matt shares how legacy ticketing systems optimized for transactions, not relationships, and why “shadow audiences” have become one of the biggest blind spots in live event tech. The conversation spans SaaS innovation in legacy industries, blockchain learnings, AI-driven personalization, and what it truly takes to build mission-critical infrastructure at scale.⸻About the GuestMatt Zarracina is the CEO and Co-Founder of True Tickets, a ticket custody and identity platform helping venues understand who is actually attending their events.His background spans the U.S. Naval Academy, helicopter aviation, systems engineering, an MBA, M&A consulting at Deloitte, and corporate innovation leadership before founding True Tickets full-time in 2018.https://www.linkedin.com/in/zarracina/⸻Key Takeaways • Why most venues only know 30–40% of their real audience • How “ticket custody” differs fundamentally from ticket sales • Why legacy ticketing systems were never designed for identity or post-sale visibility • The real reason ticket resale abuse and bots persist • How data unlocks personalization, donor growth, and long-term audience relationships • Why mission-critical SaaS cannot “move fast and break things” • Where AI fits next: fraud detection, pricing intelligence, and behavioral patterns⸻What You’ll Learn • What the “shadow audience” really is and why it matters • How True Tickets integrates into legacy ticketing systems without replacing them • Why frictionless UX is not always the goal and what “optimal friction” means • How venues can reclaim ownership from secondary markets • Lessons from building SaaS inside conservative, legacy industries • Why consultants and operators can become strong founders⸻Episode Highlights & Timestamps(Approximate, optimized for Spotify & YouTube chapters) • 00:00 – Introduction and Matt’s unconventional journey • 03:45 – The origin of True Tickets and discovering ticketing’s blind spot • 07:30 – Defining the “Shadow Audience” problem • 10:45 – Bots, resale markets, and why legislation alone fails • 14:00 – Real-world example: turning attendees into donors • 17:45 – What True Tickets actually does under the hood • 21:30 – SaaS in legacy industries and mission-critical systems • 26:00 – Balancing security, friction, and user experience • 30:45 – The future of ticketing: data, AI, and personalization • 35:00 – Global expansion and market opportunity • 38:30 – Founder lessons from consulting to scale-up CEO • 43:30 – Final reflections and where to learn more⸻Resources Mentioned • True Tickets Website: https://www.true-tickets.com/ • ROI Calculator and Product Demo (available on True Tickets’ site) • Super Founders by Ali Tamaseb

In this episode of The CTO Show with Mehmet, I’m joined by Ahikam Kaufman, Co-Founder and CEO of Safebooks.ai, a seasoned finance executive turned entrepreneur with deep experience across startups, public companies, and large-scale acquisitions.We explore why finance has lagged behind other functions in digital transformation, how AI is fundamentally reshaping financial governance, and why the modern CFO is becoming a transformation leader, not just a financial steward.This conversation goes beyond buzzwords and dives into real-world problems: broken audit trails, fragmented systems, compliance risk, and how AI agents can finally deliver real-time financial truth.⸻👤 About the GuestAhikam Kaufman is the Co-Founder and CEO of Safebooks.ai.He began his career in accounting, served as a CFO in Silicon Valley startups, experienced multiple acquisitions including by Hewlett-Packard and Intuit, and spent over a decade as an entrepreneur.Today, Ahikam is focused on modernizing the Office of the CFO by applying AI to financial data governance, auditability, and compliance at scale.https://www.linkedin.com/in/ahikam-kaufman-688310/⸻🎯 Key Topics Covered • Why finance was never designed for today’s data complexity • The two biggest blind spots in modern financial organizations • What “audit trail” really means and why it’s so hard to achieve • How AI agents bridge structured system data and unstructured documents • From quote to cash: tracing transactions across fragmented systems • Why compliance failures are often data problems, not intent problems • The evolving role of the CFO in the AI era • Where humans still matter and where machines outperform • Why AI makes regulation easier to meet, not harder • Practical advice for founders building in finance and compliance⸻🧠 Key Takeaways • Finance teams deal with massive data but are not trained as data teams • Fragmented systems create hidden compliance and cash-flow risks • AI can monitor 100% of financial transactions, not just samples • Real-time governance is now technically possible for the first time • CFOs are becoming transformation leaders, not just scorekeepers • The future of finance is continuous, automated, and exception-driven⸻🎓 What You’ll Learn • How AI changes financial accuracy from “material” to near-perfect • Why most financial errors happen even when teams do “everything right” • How AI reduces headcount pressure without removing human oversight • What founders must understand before building in fintech or compliance • How finance can finally get its own “single pane of glass”⸻⏱️ Episode Highlights (Timestamps) • 00:00 – Ahikam’s journey from CFO to AI founder • 05:00 – The two unsolved problems in corporate finance • 09:30 – Why audit trails break across modern systems • 14:00 – What really goes wrong when financial data is wrong • 18:30 – How AI understands contracts and financial documents • 24:00 – Humans vs machines in financial decision-making • 30:00 – The CFO’s evolving role in AI transformation • 36:00 – Regulation, compliance, and AI realities • 43:00 – Advice for founders building in finance⸻🔗 Resources Mentioned • Safebooks.ai • Topics: AI agents, financial audit trails, CFO transformation, data governance

In this episode of The CTO Show with Mehmet, I sit down with Khaled Nazif, COO of DSquares, one of the most influential yet quietly powerful enterprise loyalty platforms in the MENA region.Khaled shares his journey from Stanford and Silicon Valley back to the region, where he helped scale DSquares into a 150M+ end-user platform serving banks, telcos, governments, and large enterprises across 16 countries.We go deep into what loyalty really means today, why most companies still misunderstand it, how culture breaks at scale if you are not intentional, and what founders in emerging markets can learn from Silicon Valley without copying it blindly.This is a conversation about scale, systems, leadership, and long-term thinking.⸻👤 About the GuestKhaled Nazif is the Chief Operating Officer at DSquares, a leading white-labeled loyalty and engagement platform powering some of the largest enterprises and government programs across MENA and Africa.Before returning to the region, Khaled spent nearly a decade in Silicon Valley, earning his MBA from Stanford, founding a B2B SaaS startup, and later working at Zendesk. He brings a rare blend of operator discipline, startup grit, and enterprise execution to scaling regional platforms.https://www.linkedin.com/in/khalednazif/⸻🧠 Key Takeaways • Why loyalty is misunderstood and often wrongly treated as a cost center • How DSquares scaled without VC hype and stayed bootstrapped for 13 years • What it really means to move from a “pirate” startup culture to a “navy” scale-up • Why government loyalty programs are not an oxymoron • The importance of productization when scaling enterprise platforms • How culture breaks after ~150 people and what leaders must do proactively • What MENA founders can learn from Silicon Valley and what they should ignore • Why failure must be normalized for ecosystems to truly mature⸻🎯 What You Will Learn • How to scale enterprise platforms across multiple countries and cultures • How loyalty, data, and behavior change intersect at scale • Why leadership transitions matter more than founder heroics • How to think long-term when building in emerging markets • Why execution discipline beats hype cycles every time⸻⏱ Episode Highlights & Timestamps00:00 – Welcome and introduction02:00 – Khaled’s journey from Stanford to Silicon Valley05:30 – What DSquares really does and why most people don’t know it09:00 – Scaling loyalty across banks, telcos, and governments13:30 – Loyalty vs transactions: what most companies get wrong18:00 – Using data and gamification to influence behavior23:00 – Loyalty as a revenue driver, not a cost center27:30 – Bootstrapping DSquares and resisting VC pressure33:00 – Replacing a founder and scaling leadership responsibly38:30 – The 150-employee culture breaking point45:00 – Pirate vs Navy mindset and operational maturity51:00 – Silicon Valley lessons that actually work in MENA57:00 – Failure, risk-taking, and ecosystem maturity01:03:00 – Advice for founders building in emerging markets01:08:00 – Closing thoughts and where to connect with Khaled⸻🔗 Resources & Mentions • DSquares – Enterprise Loyalty & Engagement Platform : https://dsquares.com/ • Book referenced: Blitzscaling by Reid Hoffman

In this episode of The CTO Show with Mehmet, I’m joined by Alex Schlager, Founder and CEO of AIceberg, a company operating at the intersection of AI, cybersecurity, and explainability.We dive deep into why AI agents fundamentally change enterprise risk, how shadow AI is spreading across organizations, and why monitoring black-box models with other black boxes is a dangerous mistake.Alex explains how explainable machine learning can provide the observability, safety, and security enterprises desperately need as they adopt agentic AI at scale.⸻👤 About the GuestAlex Schlager is the Founder and CEO of AIceberg, a company focused on detection and response for AI-powered workflows, from LLM-based chatbots to complex multi-agent systems.AIceberg’s mission is to secure enterprise AI adoption using fully explainable machine learning models, avoiding black-box-on-black-box monitoring approaches. Alex has deep expertise in AI explainability, agentic systems, and enterprise AI risk management.https://www.linkedin.com/in/alexschlager/⸻🧠 Key Topics We Cover • Why AI agents create a new and expanding attack surface • The rise of shadow AI across business functions • Safety vs security in AI systems and why CISOs must now care about both • How agentic AI amplifies risk through autonomy and tool access • Explainable AI vs LLM-based guardrails • Observability challenges in agent-based workflows • Why traditional cybersecurity tools fall short in the AI era • Governance, risk, and compliance for AI driven systems • The future role of AI agents inside security teams⸻📌 Episode Highlights & Timestamps00:00 – Introduction and welcome01:05 – Alex Schlager’s background and the founding of AIceberg02:20 – Why AI-powered workflows need new security models03:45 – The danger of monitoring black boxes with black boxes05:10 – Shadow AI and the loss of enterprise visibility07:30 – Safety vs security in AI systems09:15 – Real-world AI risks: hallucinations, data leaks, toxic outputs12:40 – Why agentic AI massively expands the attack surface15:05 – Privilege, identity, and agents acting on behalf of users18:00 – How AIceberg provides observability and control21:30 – Securing APIs, tools, and agent execution paths24:10 – Data leakage, DLP, and public LLM usage27:20 – Governance challenges for CISOs and enterprises30:15 – AI adoption vs security trade-offs inside organizations33:40 – Why observability is the first step to AI security36:10 – The future of AI agents in cybersecurity teams40:30 – Final thoughts and where to learn more⸻🎯 What You’ll Learn • How AI agents differ from traditional software from a security perspective • Why explainability is becoming critical for AI governance • How enterprises can regain visibility over AI usage • What CISOs should prioritize as agentic AI adoption accelerates • Where AI security is heading in 2026 and beyond⸻🔗 Resources Mentioned • AIceberg: https://aiceberg.ai • AIceberg Podcast – How Hard Can It Be? https://howhardcanitbe.ai/

Raising capital looks easy from the outside. In reality, it is one of the most misunderstood parts of building a startup.In this episode, Mehmet sits down with Daniel Nikic, a global investment researcher who has analyzed over 15,000 companies across the US, Europe, and the Middle East. Together, they unpack the hard truths founders need to understand about fundraising, investor psychology, market geography, and why most rounds fail long before the first term sheet.This is a grounded, no-hype conversation about what actually drives investment decisions in 2025 and why “easy money” is often the biggest illusion founders believe.⸻About the GuestDaniel Nikic is the founder of Coherent Research and a global investment research professional with deep experience across North America, Europe, and emerging markets. Originally from Canada and now based in Croatia, Daniel has worked with investors, family offices, and founders worldwide, helping evaluate companies across stages, industries, and geographies.His work focuses on due diligence, market opportunity analysis, and understanding the human and cultural factors behind investment decisions.⸻Key Topics Discussed • Why most fundraising fails before it even starts • The biggest misconceptions founders have about “easy capital” • How geography actually impacts investment decisions • Why the Middle East is not fast money despite capital availability • Founder psychology, stress, and emotional control as investment signals • What investors look for beyond pitch decks and valuations • The difference between angels, VCs, family offices, and accelerators • Why urgency and FOMO often kill deals instead of closing them • How AI is changing investment behavior and decision-making • Realistic timelines for closing funding rounds in emerging markets⸻Key Takeaways • Capital is not free money. Investors expect returns, discipline, and execution. • Geography still matters, but trust and relevance matter more. • Founders who rush fundraising often lose credibility. • Investors back people they trust, not just ideas or decks. • Being organized and prepared beats hype every time. • Fundraising is a relationship-building process, not a transaction.⸻What You Will Learn • How to target the right investors at the right stage • Why mixing angels, VCs, and family offices too early backfires • How investors think about risk, timing, and founder maturity • What “smart money” really means beyond capital • How long fundraising realistically takes and why patience matters⸻Episode Highlights & Timestamps(You can fine-tune timestamps once audio is finalized) • 00:00 – Introduction and Daniel’s global background • 04:00 – Patterns from analyzing 15,000+ companies • 07:30 – Geography vs psychology in startup success • 10:45 – The Middle East investment misconception • 15:20 – Why capital follows trust, not hype • 18:30 – Choosing the right investor type early on • 22:40 – Check sizes, valuations, and regional differences • 27:00 – AI, FOMO, and modern investment behavior • 32:00 – Why urgency kills fundraising deals • 36:30 – Realistic timelines to close a round • 41:00 – Final advice for founders raising capital⸻Resources & Links • Daniel Nikic on LinkedIn: https://www.linkedin.com/in/daniel-nikic/ • Website: https://www.danielnikic.com/

In this episode, Gabriel Jarrosson, founder and managing partner at Lobster Capital, breaks down what truly drives breakout startups inside the world’s most competitive ecosystem.Before becoming a YC-focused investor, Gabriel built seven startups, failed four, and bootstrapped one to one million ARR alone — no co-founder, no employees, no AI.Today he invests exclusively in YC companies and shares how he evaluates founders, why early traction beats everything, how YC creates unstoppable momentum, and how AI is reshaping the next generation of builders.⸻About Gabriel JarrossonGabriel Jarrosson is a serial founder turned YC-specialized investor and managing partner at Lobster Capital. He has built seven companies, exited three, and invested in more than 100 YC startups. Gabriel also hosts The Lobster Talks and has grown a fast-rising media presence supporting early-stage founders.https://www.linkedin.com/in/gabrieljarrosson/⸻Key Takeaways • Why solo founders can still win big when they embrace urgency, automation, and creative resourcefulness • The mindset required to scale without waiting for funding or a co-founder • YC founder patterns: technical teams, relentless execution, and high velocity • Why YC attracts the world’s strongest builders and why it’s nearly impossible to replicate • Gabriel’s 2 percent rule for selecting the best companies in every YC batch • Why early revenue and market pull matter more than ideas and hype • How AI is changing the definition of what a “lean team” can achieve⸻What You Will Learn • How top investors evaluate teams, traction, and momentum • How YC creates an environment that rewires founders to move faster • Why some geographies struggle to reproduce Silicon Valley outcomes • How to think about automation, support systems, and scaling with AI • How founders outside the US can become YC-ready • What Gabriel regrets missing as an angel investor — and what he learned from it⸻Episode Highlights & Timestamps00:00 — Introduction01:30 — Seven startups, three exits, four failures03:00 — Bootstrapping to 1M ARR as a solo founder07:00 — The role of AI in scaling today10:00 — Why YC is a category of its own14:30 — What YC founders have in common18:00 — Why “local incubators” fail to replicate YC21:00 — How Gabriel selects winners27:00 — Getting into competitive YC deals33:00 — The media edge in venture37:00 — Becoming YC-ready as a non-US founder46:00 — Gabriel’s biggest miss50:00 — Closing thoughts⸻Resources Mentioned • Lobster Capital: https://www.lobstercap.com/ • The Lobster Talks podcast: https://www.youtube.com/@lobster-talks