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. 3d ago

    #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.

    41 min

  2. 6d ago

    #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.

    41 min

  3. 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.

    52 min

  4. 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.

    55 min

  5. Jun 15

    #607 More AI Won’t Help. Better Processes Will | Lara Hamilton

    In this episode of The CTO Show with Mehmet, Mehmet sits down with Lara Hamilton, a technology leader at HelpDesk Realty. The conversation focuses on why more AI will not help companies that have not fixed their processes first. Lara reframes AI adoption as an operations problem rather than a technology problem. The discussion moves from property management and paperless workflows to AI agents, security, documentation, and the practical friction that slows teams down. The core argument is clear: AI can save time, but only when the business knows how the work actually gets done. If you are leading IT, operating a growing business, investing in enterprise technology, or evaluating AI projects, this conversation gives a grounded view of where automation works and where it breaks. About the Guest Lara Hamilton is a technology leader at HelpDesk Realty, where she works across IT operations, support, property technology, and compliance. Her background includes banking operations, process improvement, help desk services, property management systems, cybersecurity practices, and practical AI adoption. Lara brings an operator’s view of AI because she works with the systems, users, reports, tickets, and workflows that determine whether technology succeeds or fails. LinkedIn: https://www.linkedin.com/in/larahamilton-multifamilyit/ Website: https://www.teamtectonic.com/divisions/helpdesk-realty Key Takeaways AI does not fix broken processes, it depends on them being clear first.Undocumented work becomes a major risk when companies try to automate it.Operational friction is often where AI produces the clearest return.Small daily tasks can create large productivity losses when repeated across teams.AI agents can block support when they replace human escalation paths.Security controls fail when users experience them as constant friction.Multi-factor authentication remains unpopular, but it is still necessary.Human knowledge inside teams cannot be replaced by tools alone. What You Will Learn How missing process documentation weakens AI adoption.Why AI projects fail when leaders start with tools instead of workflows.The specific types of operational friction that automation can remove.How ticketing data and reporting tasks can become practical AI use cases.Why AI agents still need human escalation paths.When security controls improve protection without hurting productivity.What property management can teach broader enterprise teams about digital adoption. Episode Highlights 00:00: Lara Hamilton’s path from banking operations to IT 02:00: Repetition creates the strongest case for automation 04:00: Property management still carries manual process debt 05:30: Paperless workflows expose resistance to operational change 08:30: IT leaders must translate vision into execution 09:30: Undocumented processes block better technology outcomes 12:00: AI depends on the foundation beneath it 16:30: Small AI use cases can return hours weekly 22:00: AI agents can break support escalation paths 25:30: Security must balance protection with user behavior 28:00: Digital payments changed property operations after COVID 31:00: Strong IT teams share knowledge across skill sets 33:30: Learning compounds into institutional knowledge 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.

    37 min

  6. Jun 12

    #606 AI Can Generate Code. It Still Can’t Replace Engineering Judgment | Jason Li

    In this episode of The CTO Show with Mehmet, Mehmet sits down with Jason Li, CTO at Laurel. Jason brings experience from enterprise software, Salesforce, Ironclad, and AI-native product development. The conversation reframes AI adoption away from replacing work and toward understanding work. Faster code generation does not eliminate engineering bottlenecks. Quality, technical debt, review processes, and organizational design are becoming the limiting factors. If you are leading engineering teams, building AI products, or investing in enterprise software, this conversation provides a practical view of how AI is changing software development and technical leadership. About the Guest Jason Li is the CTO at Laurel, an AI company focused on time intelligence and productivity. Previously, he worked in enterprise software and held roles at Salesforce and Ironclad. His work spans AI-native products, developer productivity, legal technology, and engineering leadership. His perspective comes from operating AI systems inside production environments while managing the realities of software quality, technical debt, and team structure. LinkedIn: https://www.linkedin.com/in/jasonhli/ Laurel website: https://www.laurel.ai/ Key Takeaways AI shifts bottlenecks from code generation to code quality.Visibility into work creates more leverage than blindly automating tasks.Engineering productivity remains difficult to measure despite new AI tools.Agentic coding increases the speed at which technical debt accumulates.Existing code review processes were not designed for AI-generated code.Senior engineering judgment becomes more valuable in an agent-driven world.AI tools expose weaknesses in processes rather than eliminating them.Rewriting software may become cheaper and more common than in previous generations. What You Will Learn The difference between replacing work and understanding work.How time intelligence creates operational visibility.Why measuring AI ROI remains difficult.How engineering teams are adapting to agentic coding.What skills remain valuable for engineers entering the profession.Why technical debt may increase faster in AI-assisted development.When software rewrites may become preferable to maintaining legacy architectures. Episode Highlights 00:00 — Time intelligence extends beyond billing hours 03:30 — Visibility matters before automation decisions 05:00 — AI should amplify leverage, not replace people 08:00 — Trust and reliability determine AI adoption 12:00 — AI systems inherit organizational weaknesses 15:00 — Measuring AI productivity remains difficult 17:30 — Agentic coding changes software engineering 20:00 — Engineering leadership becomes more hands-on 25:00 — Judgment matters more than coding syntax 30:00 — Technical debt grows faster with AI 35:00 — Wrappers versus foundation model tools 40:30 — Uncertainty creates new opportunities 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, AI infrastructure, cybersecurity, and venture capital.

    45 min

  7. Jun 8

    #605 AI Won’t Fix Broken Organizations. It Exposes Them | Jürgen Dauk

    In this episode of The CTO Show with Mehmet, Mehmet sits down with Jürgen Dauk, advisor, consultant, and creator of the Leadership Operating System. AI is not the real bottleneck. Broken organizational design is. The conversation reframes AI adoption as a leadership and operating model problem rather than a software rollout. Jürgen argues that companies built around control, reporting, and top-down approval are too slow to capture real value from AI. The discussion moves from misaligned KPIs and forecast calls to distributed decision-making, experimentation, and why AI often amplifies the dysfunction already inside the company. If you are leading, investing in, or operating an enterprise technology company, this conversation clarifies why AI value depends less on tools and more on how decisions, teams, and accountability are designed. About the Guest Jürgen Dauk is an advisor and consultant to companies and the creator of the Leadership Operating System. He is the author of The Leadership Operating System and has worked across technology, marketing, sales, customer support, customer success, and management roles. Jürgen’s background includes work with companies such as Oracle and OpenText, as well as transformation work across mid-sized and large organizations. His work focuses on helping companies move away from fear-based control and toward operating models where people, teams, and decision-making can support faster adaptation. LinkedIn: https://www.linkedin.com/in/juergendauk/ Website: https://theleadership-os.com/ Key Takeaways AI does not fix broken organizations. It makes their weak points more visible.Company-wide AI rollouts fail when leaders mistake access for adoption.Control-based operating models create stability, but they also slow decision-making.Misaligned KPIs push sales, marketing, and customer success into internal conflict.AI should not automate bad processes before leaders question why those processes exist.Distributed decision-making becomes a survival issue when competitors move faster.Reporting calls and alignment meetings often create activity without real output.AI can multiply low-value work when organizations use it to produce more noise. What You Will Learn The organizational patterns that prevent companies from benefiting from AI.Why Microsoft Copilot access alone does not create measurable productivity gains.How leaders can move from centralized AI rollouts to team-level problem solving.The role of distributed decision-making in faster AI adoption.Why experimentation culture matters more than formal AI training.How reporting calls, CRM inspection, and dashboards can create false control.What leadership teams must change before AI can create real operational value. Episode Highlights 00:00 — AI exposes the organization behind the tooling 05:00 — Misaligned KPIs turn teams against each other 09:00 — Command and control was built for stability 15:00 — Company-wide AI rollout can produce little value 17:00 — AI works when teams rethink the process 20:00 — Technical expertise belongs inside business teams 22:00 — Experimentation turns failed pilots into useful learning 25:00 — Reporting calls create alignment without real output 29:30 — AI can multiply nonsense work 38:30 — Slow decisions are now existential risk 43:30 — The Leadership Operating System connects the pieces 51:00 — Jürgen shares resources for organizational self-checks Resources Mentioned The Leadership Operating System by Jürgen Dauk: https://www.amazon.com/Leadership-Operating-System-Accelerating-Dominating-ebook/dp/B0GX2TNS92Leadership Operating System website: https://theleadership-os.comDesign thinkingThe Innovator’s Dilemma by Clayton Christensen 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.

    54 min

  8. Jun 5

    #604 AI Can Generate Expertise. It Still Can’t Generate Judgment | Dan Pratl, Founder & CEO, Quadron

    In this episode of The CTO Show with Mehmet, Mehmet sits down with Dan Pratl, Founder and CEO of Quadron. Dan is building infrastructure around trust, credibility, reputation, and human judgment in a world where AI can generate expert-looking work at near-zero cost. The conversation reframes one of the most common assumptions about AI. The scarcity is no longer knowledge creation. The scarcity is verification, judgment, and the ability to demonstrate that a person stands behind a claim. Rather than treating AI as a replacement for expertise, Dan argues that AI increases the value of trusted human judgment. If you are building, investing in, operating, or leading in AI, enterprise software, digital infrastructure, or knowledge-intensive businesses, this conversation provides a framework for thinking about trust, reputation, and value creation in an AI-driven economy. About the Guest Dan Pratl is the Founder and CEO of Quadron, a company focused on creating infrastructure for trust, credibility, reputation, and programmable incentives in the AI era. His background spans regulation, open source software, crowdfunding, decentralized finance, and crypto. Through those experiences, he developed a thesis that human expertise, judgment, and credibility should become measurable, portable, and economically valuable assets. His work focuses on solving a problem that becomes increasingly important as AI-generated content becomes abundant: determining who stands behind information and why that credibility should matter. LinkedIn: https://www.linkedin.com/in/danpratl/ Website: https://quadron.tech/ Personal Site: https://pratl.me Key Takeaways • AI has made knowledge generation abundant, but trust remains scarce. • The value of expertise increasingly comes from judgment rather than content creation. • Traditional credentials and social proof systems are losing effectiveness. • Credibility needs to become portable rather than tied to individual platforms. • Verification must become a byproduct of human ambition and incentives. • Human expertise is an evolving asset that compounds over time. • AI agents can execute tasks, but humans still define what good looks like. • Organizations that capture and reward human judgment will outperform those that only optimize automation. What You Will Learn • Why AI-generated expertise does not eliminate the value of human judgment. • How credibility may evolve into a measurable and portable asset. • The limitations of resumes, endorsements, and traditional reputation systems. • How programmable incentives can encourage verification and trust. • What a credibility wallet could look like in practice. • Why AI agents still depend on humans to define outcomes and quality. • How organizations can preserve and scale expertise in an AI-first environment. Episode Highlights 00:00 — AI Makes Trust More Valuable Than Knowledge 05:00 — Knowledge Becomes Abundant, Verification Becomes Critical 08:00 — Why Judgment Outlasts AI Generated Expertise 11:00 — The Case for a Portable Credibility Wallet 14:00 — Quantifying Reputation Beyond Social Proof 16:00 — Expertise Compounds Through Iteration 18:00 — Turning Judgment Into an Economic Asset 21:00 — Investing in Yourself as a Market 25:00 — Verification Must Reward Participation 30:00 — AI Agents Need Humans To Define Good 33:00 — Companies That Ignore Human Judgment Fall Behind 35:00 — Building a New Category Around Trust Infrastructure Resources Mentioned • MCP (Model Context Protocol) • Skills.md • Red Hat • SEC (U.S. Securities and Exchange Commission) • CFTC (Commodity Futures Trading Commission) 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, venture capital, AI, cybersecurity, and enterprise technology.

    41 min
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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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