The CTO Show with Mehmet Gonullu

Mehmet Gonullu

Broadcasting from Dubai, The CTO Show with Mehmet explores the latest trends in technology, startups, and venture funding. Host Mehmet Gonullu leads insightful discussions with thought leaders, innovators, and entrepreneurs from diverse industries. From emerging technologies to startup investment strategies, the show provides a balanced view on navigating the evolving landscape of business and tech, helping listeners understand their profound impact on our world. mehmet@yassiventures.com

  1. 6d ago

    #615 Gamification Is Not a Feature. It Is Consumer Behavior | Matt Edelman

    In this episode of The CTO Show with Mehmet, Mehmet sits down with Matt Edelman, CEO of Super League. Matt explains why gamification has become a default expectation for younger digital consumers, not an optional engagement tactic. The conversation reframes gaming as a major behavioral and commercial environment rather than a niche media channel. Advertising spending remains concentrated in television and social media even as younger audiences divide significant attention across gaming, while AI is making game creation easier without removing the need for human taste, interpretation, and experience design. If you are building digital products, allocating marketing budgets, or leading customer engagement strategy, this conversation clarifies how gaming behavior is changing product expectations and brand participation. About the Guest Matt Edelman is the CEO of Super League, a NASDAQ-listed company that helps brands and advertisers reach gaming audiences through immersive experiences, playable media, gaming-related inventory, and creator-led content. His career has operated at the intersection of emerging technology, media, content creation, distribution, and audience behavior.  His work gives him direct exposure to how brands measure attention, participation, identity, and action across gaming environments, and why those signals differ from passive advertising. LinkedIn: https://www.linkedin.com/in/mattedelman/ Key Takeaways Gamification is becoming a consumer expectation rather than an optional product feature.Marketing budgets do not reflect the amount of time younger audiences spend gaming.Active participation creates stronger behavioral signals than passive ad impressions.AI will increase game production faster than it improves game quality.Human taste remains essential when interpreting player data and refining experiences.Digital identity can carry as much emotional importance as physical identity.Most brands cannot compete with native creators by building permanent branded games.Timely, useful participation earns more acceptance than an always-on branded presence. Episode Highlights 00:00 — Matt Edelman frames gaming as a business channel 03:00 — Marketing leaders are still learning gaming behavior 06:00 — Active participation changes how advertising is processed 08:30 — Gaming measurement extends beyond basic impressions 12:30 — Advertising budgets underrepresent gaming audience attention 15:00 — AI will dramatically increase game creation 17:30 — Human taste still determines experience quality 19:30 — Digital identity carries real emotional significance 23:30 — Younger consumers now expect gamified digital experiences 26:00 — Most brands should not build permanent games 29:00 — Timely brand participation earns stronger community acceptance 31:00 — Game creation develops transferable operating skills 35:00 — Incentives and psychology determine customer behavior Resources Mentioned Super League: Gaming media and immersive brand experiences http://www.superleague.com/ Listen Now Available on all major podcast platforms and YouTube. Connect with the Show Follow The CTO Show with Mehmet for more conversations at the intersection of technology, startups, and venture capital.

  2. Jul 17

    #614 AI Can Replace Tasks, But Still Can’t Replace Judgment | Dilip Chetan

    In this episode of The CTO Show with Mehmet, Mehmet sits down with Dilip Chetan, founder of DefensibleZone.ai. Dilip brings more than two decades of experience across Google, Meta, Oracle, Salesforce, and Intuit, spanning engineering, product strategy, human factors, and customer research. The conversation challenges the assumption that AI adoption is primarily a technology deployment or workforce reduction exercise. AI can automate tasks, write code, analyze data, and operate agents, but it still struggles with accountability, context switching, taste, and the human judgment hidden inside job descriptions. If you are leading enterprise AI adoption, restructuring technical teams, deploying autonomous agents, or investing in AI-enabled companies, this conversation provides a clearer way to separate useful automation from organizational risk. About the Guest Dilip Chetan is the founder of DefensibleZone.ai, where he is developing a framework to help professionals and organizations identify capabilities that remain valuable as AI expands into more areas of work. He has more than 20 years of technology experience across Google, Meta, Oracle, Salesforce, and Intuit. His background includes engineering, product management, product strategy, user research, customer analysis, and human factors. His Defensible Zone framework focuses on the intersection of natural affinity, market demand, and the areas AI has not yet reached. The framework is designed to move the discussion beyond which tasks can be automated and toward which human qualities remain essential. LinkedIn: https://www.linkedin.com/in/dilipchetan/ Website: https://defensiblezone.ai Personal website: https://dilipchetan.com Key Takeaways AI can replace tasks without replacing the judgment that makes those tasks valuable.Workforce reduction is the wrong starting point for enterprise AI adoption.Job descriptions must change before AI can genuinely free people for higher-value work.Human value extends beyond skills into context, accountability, taste, and judgment.The more accountability a decision carries, the less autonomy an AI agent should receive.Too little context makes AI invent answers, while too much context can reduce its effectiveness.Metrics become dangerous when companies measure activity without connecting it to business purpose.A defensible career depends on understanding natural affinity before evaluating market demand or AI exposure. Episode Highlights 00:00 — Dilip Chetan’s path across major technology companies 05:00 — AI adoption requires organizational redesign, not software deployment 07:00 — Workforce replacement is the wrong AI objective 09:30 — The Defensible Zone separates value from automation 12:30 — Human qualities matter more than task inventories 14:30 — Autonomous agents create value and accountability risk 18:30 — Effective AI use depends on controlled context 21:30 — Judgment can be measured only in parts 25:30 — AI metrics must follow the company’s purpose 31:00 — Leaders need vision beyond AI adoption 35:30 — Natural affinity starts with serious self-examination 39:00 — Where to find Defensible Zone resources Listen Now Available on all major podcast platforms and YouTube. Connect with the Show Follow The CTO Show with Mehmet for more conversations at the intersection of technology, startups, and venture capital.

  3. Jul 10

    #613 Innovation Is Not the Bottleneck. Commercialization Is | Roland Austrup

    In this episode of The CTO Show with Mehmet, Mehmet sits down with Roland Austrup, Chief Growth Officer at Innventure. Large companies produce valuable technologies, but they are rarely structured to build new businesses around them. The conversation reframes innovation as only the first stage of value creation. A technology can work, address a real market need, and still fail because productization, leadership, supply chains, financing, and market adoption were treated as secondary concerns. Roland explains why commercialization requires a repeatable operating process, not simply a stronger invention or a larger R&D budget. If you are leading corporate technology, building industrial companies, or investing in AI infrastructure and deep technology, this conversation clarifies where technical promise ends and company-building risk begins. About the Guest Roland Austrup is the Chief Growth Officer at Innventure, a public company that creates and operates businesses built around technologies developed by large multinational corporations. His background includes currency trading, founding an asset management company, helping finance PureCycle Technologies, and supporting its public listing in 2021. At Innventure, he works across company creation, capital strategy, industrial technology commercialization, and portfolio growth. His experience sits directly at the boundary between proven corporate R&D and the operating work required to turn it into an independent company. LinkedIn: https://www.linkedin.com/in/roland-austrup-0874825/ Website: https://www.innventure.com Key Takeaways Large companies are built to improve existing businesses, not create new ones from zero.A working technology is not a business until someone can productize, finance, and distribute it.The first test of a corporate technology is the size and urgency of the unmet market need.Technical validation reduces invention risk but leaves scaling, adoption, and execution risks intact.A strong economic value proposition matters more than whether a product is merely desirable.Capital strategy is part of company building, not an administrative step after product development.AI infrastructure may create more defensible value than easily replicated software applications. What You Will Learn The four evaluation gates Innventure uses before creating a company around corporate technology.Why entrepreneurial company creation requires a different skill set from corporate R&D.How market need, technical readiness, operating costs, and margins shape commercialization decisions.The reasons capital planning must begin before a new company enters the market.How multinational corporations can serve as technology sources, customers, and distribution channels.Why AI growth creates opportunities in cooling, power, grid infrastructure, and industrial systems. Episode Highlights 00:00 — Corporate invention requires a separate company-building capability 04:00 — Large companies rarely start effectively from zero 06:00 — Market need is the first commercialization gate 08:00 — Technical validation does not eliminate scaling risk 13:00 — Company creation fails when one capability is missing 16:00 — Capital strategy is an operating requirement 17:00 — AI infrastructure supplies the picks and shovels 22:00 — Real AI exposure differs from borrowed language 25:00 — Proven technology makes execution more predictable 27:00 — Company creation can become a repeatable process 30:00 — CTOs need external commercialization pathways 35:00 — AI demand creates downstream industrial opportunities 41:00 — The enabling layer may hold greater value 42:00 — Operators create businesses, not investors alone Listen Now Available on all major podcast platforms and YouTube Connect with the Show Follow The CTO Show with Mehmet for more conversations at the intersection of technology, startups, and venture capital.

  4. Jul 3

    #612 The Next EV Race Is on the Water | Alexandre Mongeon

    In this episode of The CTO Show with Mehmet, Mehmet sits down with Alexandre Mongeon, CEO and Co-Founder of Vision Marine Technologies. Alex is building electric marine propulsion systems for family boats, commercial use cases, and future autonomous vessels. The conversation frames marine electrification as the next EV market after cars. The episode reframes electric boats as a commercialization problem, not only a battery or engineering problem. Alex explains why range, charging, customer behavior, third-party validation, rental data, and dealer distribution all decide whether hard tech becomes a real market. The signal is clear: the technology can work years before the market is ready to buy it. If you are building, investing in, or operating in EV infrastructure, hard tech, mobility, or climate-related industrial markets, this conversation shows what adoption looks like when the product is physical, expensive, regulated, and unfamiliar to buyers. About the Guest Alexandre Mongeon is the CEO and Co-Founder of Vision Marine Technologies, a company focused on electric marine propulsion and electric boat systems. He has spent more than a decade working on maritime electrification, including high-performance electric boats, OEM integrations, rental operations, and dealer distribution. Alex brings an operator’s view of how hard tech moves from prototype to commercial demand, with lessons from boat racing, McLaren Engineering validation, customer rentals, manufacturer integrations, and public-market investor conversations. LinkedIn: https://www.linkedin.com/in/alexandre-mongeon-a57354114/ Website: https://visionmarinetechnologies.com/ Retail and rentals: https://www.nauticalventures.com/ Key Takeaways Electric boats are not waiting for invention, they are waiting for market education.Boat range became measurable only after electric systems forced better data.Hard tech credibility depends on third-party validation, not founder conviction.Rental operations gave Vision Marine real customer behavior data before scale.The European marine EV market is more mature than the US market.Distribution can matter more than OEM adoption when large manufacturers move slowly.Investors understand physical technology faster when they experience the product directly.Autonomous electric vessels may become a larger commercial market than recreational boats. What You Will Learn The reason marine electrification is following the EV car market with a delay.How customer education becomes the main constraint after the technology works.Why range anxiety in boats is different from range anxiety in cars.How rental data helped Vision Marine understand real boating behavior.The role third-party engineering validation played in building market credibility.Why Europe may adopt electric boats faster than the US.What commercial and government use cases could change the electric marine market. Episode Highlights 00:00 - Electric boats move beyond a niche category 01:30 - Boat racing exposed the cost of combustion 05:30 - Performance stopped being the right target 07:30 - Customer education becomes the main constraint 11:00 - Family boats become the core market 13:30 - OEM integrations reduce adoption friction 16:30 - AI starts with range and usage data 20:30 - Credibility comes from validation and rentals 24:00 - Europe is ahead in marine electrification 29:30 - Autonomous vessels open commercial demand Listen Now Available on all major podcast platforms and YouTube.

  5. Jun 29

    #611 You Are Probably the Bottleneck And AI Won’t Change That | Jordan Solender

    In this episode of The CTO Show with Mehmet, Mehmet sits down with Jordan Solender, founder of Jordan Solender Coaching and IT Select. The central tension is simple: if every decision still depends on the founder, AI will not fix the business. Jordan argues that most founders are not resource constrained, they are clarity constrained. The conversation reframes AI from a shortcut into a leverage layer that only works when outcomes, SOPs, KPIs, and ownership are clear. Instead of chasing tools, models, and agents, Jordan makes the case for removing the founder from one repeatable process at a time. If you are building, investing in, or operating a founder-led company, this conversation gives you a practical lens for spotting bottlenecks before they become the operating model. About the Guest Jordan Solender is the founder of Jordan Solender Coaching and IT Select. He is an investor, entrepreneur, operator, and founder coach focused on helping business owners remove themselves as the bottleneck in their own companies. His work sits at the intersection of AI, delegation, systems, SOPs, and founder operating models. He is the creator of the 10/80/10 Rule, a framework for maintaining accountability without micromanagement. LinkedIn: https://www.linkedin.com/in/jordansolender/ Website: https://jordansolender.com Coaching: https://jordansolendercoaching.com Key Takeaways AI will not fix a company that depends on the founder for every decision.The behaviors that help founders start companies often limit them later.Delegation starts with documentation, not hiring.Most founders are clarity constrained before they are resource constrained.A delegated task usually fails because the system is unclear, not because the person failed.Founders need visibility into execution, not control over every step.AI agents amplify documented systems and accelerate messy ones.Persistence commits to the outcome, while stubbornness commits to the method. What You Will Learn The early signs that a founder has become the company bottleneck.How to identify one repeatable task that should no longer depend on you.Why SOPs make delegation possible before headcount increases.How the 10/80/10 Rule creates accountability without micromanagement.What AI can handle inside documented business processes.Why small teams can operate with more leverage when systems are clear.When founder persistence becomes ego and blocks company growth. Episode Highlights 00:00 — Founders often become the hidden constraint 02:30 — Scale starts when founders stop deciding everything 05:00 — Every approval path reveals the bottleneck 08:30 — Delegation starts before the first hire 10:00 — Clarity determines what can be delegated 12:00 — Good delegation is measured by outcomes 13:30 — The 10/80/10 Rule reduces micromanagement 16:30 — AI works best inside documented systems 18:30 — Chaos cannot be automated by agents 21:00 — Tool choice follows the business bottleneck 25:00 — AI can remove inbox and coordination drag 27:30 — Flatter companies still need stronger leadership 31:00 — Uncoachable founders blame everything outside themselves 34:00 — Persistence and stubbornness are not the same 36:30 — AI yes-men can amplify founder ego 38:30 — Jordan shares where listeners can find him Listen Now Available on all major podcast platforms and YouTube Connect with the Show Follow The CTO Show with Mehmet for more conversations at the intersection of technology, startups, and venture capital.

  6. Jun 26

    #610 Your POS Should Run the Business. Not Just Take Payments | Ahmed Sameh

    In this episode of The CTO Show with Mehmet, Mehmet sits down with Ahmed Sameh, CMO at Fortis. Ahmed brings a fintech and B2B marketing view on how SMEs are changing the way they run daily operations. The conversation reframes POS as more than a payment terminal. For small businesses, the real constraint is not accepting cards, it is connecting payments, inventory, customer data, loyalty, invoicing, reporting, and AI into one operational system. Ahmed explains why adding more tools often creates more manual work, more blind spots, and weaker decisions. If you are building, investing in, or operating in fintech, SME software, retail technology, or AI-enabled business operations, this conversation shows why the transaction layer is becoming the control point for business intelligence. About the Guest Ahmed Sameh is the CMO at Fortis, a software company focused on helping SMEs manage payments and day-to-day operations. Ahmed has more than 14 years of marketing experience, mainly across B2B and fintech. His background includes work connected to Tap Payments, Mastercard, FAB, and startup launches in the region. He is the right person to frame this topic because Fortis sits at the point where payments, merchant operations, customer data, and AI reporting meet. LinkedIn: https://www.linkedin.com/in/ahmed-samehfa/ Fortis: https://wefortis.com/ Key Takeaways POS is becoming the operating layer for SMEs, not just a payment device.Small businesses lose margin when transactions and inventory are tracked manually.More software does not create efficiency when systems remain disconnected.Customer data becomes useful only when it is tied to actual transactions.AI reporting depends on clean business data before it can support decisions.WhatsApp commerce creates operational blind spots when orders are not captured properly.E-invoicing will push SMEs toward more structured digital operations.SMEs need simplification before they need more tools. What You Will Learn How POS systems are evolving from card machines into business operating platforms.Why traditional payment terminals leave major gaps in customer and inventory data.The operational cost of running SMEs through spreadsheets, paper, WhatsApp, and separate tools.How customer transaction data can support loyalty, offers, and repeat business.Why AI for SMEs starts with structured payments, inventory, and customer records.What e-invoicing means for SME digitization in the UAE.When a small business should choose simplification over another software subscription. Episode Highlights 00:00 — Ahmed Sameh frames Fortis and SME operations 02:00 — SMEs still run critical work manually 06:00 — Traditional POS leaves operational gaps 10:00 — One terminal can shorten service workflows 13:30 — UAE digitization is forcing SME readiness 18:00 — WhatsApp commerce creates hidden operational risk 22:30 — More tools often create less efficiency 26:00 — Mobile-first SMEs need connected systems 29:30 — AI needs transaction data before prompts 33:30 — Agents move into reporting and inventory 36:30 — SME growth depends on usable operational data 39:00 — Fortis focuses first on the UAE market Listen Now Available on all major podcast platforms and YouTube. Connect with the Show Follow The CTO Show with Mehmet for more conversations at the intersection of technology, startups, and venture capital.

  7. Jun 22

    #609 AI Can Assess Leaders. It Shouldn’t Replace Judgment | Logan Yonavjak

    In this episode of The CTO Show with Mehmet, Mehmet sits down with Logan Yonavjak, Co-Founder and CEO of Founder Readiness Engine. Logan brings an investor and operator view into how founders and senior leaders can be assessed beyond resumes, charisma, and gut feel. The conversation reframes leadership assessment as a decision system, not a personality test. Logan explains how transcript data, developmental psychology, quantitative linguistics, and AI can surface signals such as coachability, identity flexibility, strategic complexity, relational intelligence, and resilience. The key tension is clear: AI can improve how leaders are assessed, but humans should not hand over agency to the machine. If you are investing in founders, hiring senior leaders, building leadership teams, or evaluating startup risk, this conversation gives you a sharper way to think about people analytics, founder readiness, and AI-assisted decision-making. About the Guest Logan Yonavjak is the Co-Founder and CEO of Founder Readiness Engine. She is an impact investor turned entrepreneur with experience across private equity, university endowments, farmland investing platforms, sustainable investing, and early-stage technology. She teamed up with a data scientist and psychologist to build a platform that analyzes transcript data and identifies leadership readiness markers. Her work focuses on how founders, senior leaders, investors, and organizations can make better decisions about people under pressure and complexity. LinkedIn: https://www.linkedin.com/in/loganyonavjak/ Website: https://www.readinessengine.io/ Key Takeaways AI can assess leadership readiness, but it should not replace human judgment.Founder evaluation still depends too heavily on gut feel, charisma, and warm references.Coachability and identity flexibility are critical signals for founder growth.Traditional assessments often miss how leaders develop under pressure and complexity.Strategic complexity shows up in how leaders hold multiple perspectives at once.Resilience is not a trait alone, it is a system leaders build around themselves.Relational intelligence can offset blind spots in highly technical or visionary founders.People analytics may become a stronger diligence layer for investors and operators. What You Will Learn How AI can analyze transcript data to identify leadership readiness signals.Why coachability may matter more than credentials in founder evaluation.The limits of traditional assessments such as MBTI, DiSC, StrengthsFinder, and Predictive Index.How strategic complexity appears in the way leaders explain systems and tradeoffs.Why human agency must remain central when AI supports hiring or promotion decisions.What investors often miss when they rely on pattern matching and warm references.How leadership assessment could become part of due diligence, hiring, and lending decisions. Episode Highlights 00:00 — Founder readiness becomes the central question 05:00 — Traditional assessments miss developmental trajectory 09:00 — Negative space reveals what leaders avoid 13:00 — AI should augment, not replace judgment 20:00 — Coachability becomes the strongest founder signal 23:00 — Relational intelligence offsets leadership blind spots 29:00 — Strategic complexity appears in language patterns 31:00 — Resilience depends on systems under stress 35:00 — Leadership data could reshape lending decisions 39:00 — VC still relies heavily on gut checks 43:00 — AI can model a stronger second brain 46:00 — Technology can uncover human blind spots Listen Now Available on all major podcast platforms and YouTube. Connect with the Show Follow The CTO Show with Mehmet for more conversations at the intersection of technology, startups, and venture capital.

  8. Jun 19

    #608 AI Won’t Replace Therapists. It May Replace Guesswork | Dr. Steve Rondeau

    In this episode of The CTO Show with Mehmet, Mehmet sits down with Dr. Steve Rondeau of AxonEG Solutions. Dr. Steve brings more than two decades of work across developmental medicine, EEG brain scans, biomarkers, and mental health diagnostics. The core tension is clear: mental health has too often treated labels as answers, while the brain may be telling a different story. The conversation reframes AI in healthcare as a decision-support layer, not a replacement for clinicians. Dr. Steve explains why two people with the same diagnosis can respond completely differently to treatment, how a database of more than 50,000 brain scans changes the conversation, and why objective biological data can reduce trial and error in care. The episode also connects AI, explainability, human judgment, and empathy in a field where the cost of guessing can be very high. If you are building, investing in, or leading in AI, healthcare technology, digital health, or human performance, this conversation shows where data can improve decisions without removing the human from the loop. About the Guest Dr. Steve Rondeau is with AxonEG Solutions, where his work focuses on EEG brain scans, biological markers, and objective data in mental health diagnostics. He is also the author of Think Like a Brain, a book focused on helping people understand brain patterns, treatment response, and why labels alone do not explain the full picture. His work is built around a database of more than 50,000 brain scans and a central question: why two people with the same mental health diagnosis can respond so differently to treatment. LinkedIn: https://www.linkedin.com/in/dr-steven-rondeau-148aa421/ Website: https://thinklikeabrain.com Key Takeaways Mental health labels describe suffering, but they often fail to predict treatment outcomes.AI can support clinicians by narrowing options, not by replacing human judgment.A single diagnosis can hide thousands of possible biological patterns.Objective brain data can reveal treatment paths that symptom labels may miss.The DSM helps clinicians communicate, but it does not explain each patient’s biology.Human-in-the-loop AI matters most when decisions involve context, culture, and empathy.Personalized mental health requires testing the organ being treated.Psychedelic and neuromodulation treatments need better prediction before wider adoption. What You Will Learn The reason symptom-based diagnosis can miss the biological drivers behind treatment response.How EEG brain scans can add objective data to mental health decisions.Why two patients with the same diagnosis may need completely different treatments.The role AI can play in connecting biomarkers, clinical data, and published research.How human judgment remains essential when algorithms recommend clinical paths.Why treatment prediction matters for psychedelics, ketamine, and neuromodulation.What personalized medicine looks like when the brain is measured directly. Episode Highlights 00:00 — Why mental health needs better data 02:30 — Diagnosis describes symptoms, not treatment outcomes 07:30 — Building a 50,000 brain scan database 12:30 — One diagnosis can hide thousands of patterns 16:30 — A brain scan challenged the symptom label 20:00 — Brain data can open harder conversations 23:30 — Biology and environment shape the same brain 28:30 — AI supports clinicians, not replaces them 31:30 — Predicting who responds before treatment starts 35:00 — Psychedelics need better patient selection 40:00 — Mental health should test the organ it treats 45:30 — Adoption depends on validation, funding, and trust 52:30 — Where to find Dr. Steve Rondeau Listen Now Available on all major podcast platforms and YouTube Connect with the Show Follow The CTO Show with Mehmet for more conversations at the intersection of technology, startups, and venture capital.

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Broadcasting from Dubai, The CTO Show with Mehmet explores the latest trends in technology, startups, and venture funding. Host Mehmet Gonullu leads insightful discussions with thought leaders, innovators, and entrepreneurs from diverse industries. From emerging technologies to startup investment strategies, the show provides a balanced view on navigating the evolving landscape of business and tech, helping listeners understand their profound impact on our world. mehmet@yassiventures.com

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