Innovator Coffee

Wickeyjw

Welcome to the Innovator Coffee, a podcast that bridges the gap between people and the world of AI and innovation. We're Tom and Wickey. Follow us to explore the top AI products, ecosystem insights, and the emerging trends. Tom Kong *Stanford EE alumni, Founder@ Stanford AGI Adventist Community *AI deployment for 8 years, with NLP and recent LLMs Wickey Wang *BYU alumni and SCU CAAP alumni, Growth fund VC advisor and Angel Investor with cybersecurity and AI https://www.linkedin.com/in/wickey-wang-cisa-six-sigma-green-belt-2aaa913 https://www.linkedin.com/in/thomaskong/

  1. 3 days ago

    Innovator Coffee EP-43 2026 Blackhat: What's Crowded and What's New

    Welcome to the Innovator Coffee, a podcast that bridges the gap between people and the world of AI and innovation. This is Wickey. Follow us to explore the top AI products, ecosystem insights, and the emerging trends. This episode of Innovator Coffee is a special Black Hat edition, bringing back first-hand observations from one of the world's largest security conferences in 2026. The host is joined by a CISO, a cybersecurity-focused VC, and two founders building AI security startups for a roundtable covering which areas at Black Hat felt most crowded this year, which capital flows reflect real demand versus hype, and the entirely new risks AI agents create that traditional tools simply can't see. Guest Introductions Victor Cheng: SVP, CIO, CISO and Platforms of Backstory His career started in IT before moving into payments, where handling PCI compliance in 2006 marked his entry into security and compliance. He has since spent nearly two decades in the field and is also active in venture capital, advising multiple startups. Sian Goldofsky: Founding Partner, SaaS Ventures Israel Founding partner of the Israeli arm of SaaS Ventures, a strategic investor that provides outsized value while taking minimal equity and control with cyber and AI focus with roughly 150 startups; about 40% of the U.S. fund is allocated to cybersecurity. Sian's own background is rooted in cybersecurity, with over a decade of professional experience in the space. Nadav Meiroviz: Co-founder & CEO, Conduct Nearly 15 years in cybersecurity, with military service in Israel's Unit 8200. Nadav co-founded Conduct with a childhood friend he's known since age seven, they went to the same classroom, the same university, and served in the same unit. Conduct is built to solve DLP (data loss prevention) and insider risk in the AI era. Mohan Kumar, Co-founder & CEO, Aira Security 15 years in security, Mohan co-founded his company with a friend of eight years; the two previously worked together at Box before his co-founder moved to AWS as a founding security engineer for Bedrock AgentCore, Amazon's platform for running AI agents in production. The company is a ten months old AI agent security startup, was part of the AWS*Nvidia*CrowdStrike accelerator. 8-Segment Timestamp Summary 1 00:04 – 00:40 The host frames the show and today's Black Hat theme, then introduces the four guests. 2 00:40 – 04:22 Guest introductions 3 04:22 – 06:20 First impressions of Black Hat this year: the intensity and aggressiveness of the shift toward agentic/AI topics exceeded expectations. 4 06:20 – 11:48 The most crowded spaces this year: AI SOC is saturated but still a necessary market; AI governance/posture-management vendors are everywhere; endpoint security is back in focus. 5 11:48 – 23:48 The Build vs. Buy debate and the "citizen developer" risk: AI coding agents let non-engineers build their own apps, fueling the "SaaS is dead" argument. Extends into DPA / sub-processor compliance risk. 6 23:48 – 33:27 New challenges from agentic workflows: short-lived agents are hard to audit or hold accountable; AI shows "ant-colony"-like survival behavior 7 33:27 – 41:03 How AI lowers the barrier to attacks: hyper-personalized phishing, malicious agents bypassing restrictions by hijacking a user's live session; the software supply chain trust-chain problem, the "outrun one bear" analogy, the dilemma between zero-day patching and a "30-day bake" policy, and security teams stuck in a reactive detect-and-respond loop. 8 41:03 – 48:00 Closing round: each guest shares a concrete action they're taking after Black Hat Thanks for Peter Qin helps with the editing Wickey Wang *IT Security Compliance Leader & University Faculty (AI security) *VC advisor and Angel Investor with cybersecurity and AI focus *GAI Security book co-author Questions, Suggestions, Feedback and Comments? You can find us in LinkedIn: https://www.linkedin.com/in/wickey-wang-cisa-six-sigma-green-belt-2aaa913/

  2. 27 Aug

    Innovator Coffee EP-42 Powering The AI Compute Boom

    Welcome to the Innovator Coffee, a podcast that bridges the gap between people and the world of AI and innovation. This is Wickey. Follow us to explore the top AI products, ecosystem insights, and the emerging trends. AI infrastructure is becoming an energy problem as much as a compute problem. In this episode of Innovator Coffee, we talk with Federico Ruilova, founder of GreenPow, about the convergence of AI, compute, and energy. We explore power constraints, distributed compute, energy-aware workload orchestration, and the emerging control layer that could coordinate where and when AI workloads run. Federico also shares GreenPow’s journey and lessons from building ahead of the market. Federico Ruilova is the founder of GreenPow, building an optimization layer at the intersection of AI infrastructure and energy. His work focuses on orchestrating compute across time and geography based on power, cost, infrastructure, and business constraints. His team has experimented with moving compute workloads across three countries and has orchestrated more than 1,300 production services across different regions. 00:04 – 02:45 | AI Infrastructure Meets Energy02:46 – 06:06 | Which AI Workloads Can Move?06:07 – 10:23 | When Power Becomes the Bottleneck10:24 – 14:52 | Inside GreenPow14:53 – 17:31 | Distributed Compute & the Control Layer17:32 – 22:26 | Building Before the Market Was Ready22:27 – 27:14 | Turning Infrastructure Into a Business27:15 – 30:31 | The Next Five Years & Founder Lessons Thanks for Peter Qin helps with the editing Wickey Wang *IT Security Compliance Leader & University Faculty *VC advisor and Angel Investor with cybersecurity and AI focus *GAI Security book co-author Questions, Suggestions, Feedback and Comments? You can find us in LinkedIn: https://www.linkedin.com/in/wickey-wang-cisa-six-sigma-green-belt-2aaa913/ https://www.linkedin.com/in/thomaskong/

  3. 13 Aug

    Innovator Coffee EP-41 Beyond Guardrails: Can AI Learn Human Judgement

    Welcome to the Innovator Coffee, a podcast that bridges the gap between people and the world of AI and innovation. This is Wickey. Follow us to explore the top AI products, ecosystem insights, and the emerging trends. What does it take to build AI we can actually trust? In this episode, Dr. Stuart Armstrong explores why today’s LLMs still struggle with judgment, implicit knowledge, and generalization, and why guardrails alone may not be enough for autonomous agents. We discuss his idea of pre-aligned AI, reliable agents, enterprise AI, and how alignment can move from research into practical, commercially valuable systems. Dr. Stuart Armstrong is an AI alignment researcher and entrepreneur. Formerly at Oxford’s Future of Humanity Institute and founder of Aligned AI, his work focuses on building AI systems that become more aligned with human values as they become more capable. His current focus is the central problem: teaching AIs to generalise human values, so they behave well in situations their designers never anticipated. Building working systems has confirmed his core belief, that this challenge must be solved, can be solved, and will be solved. He is the author of Smarter Than Us, a mentor at the Foresight Institute, and an advisor to the AI Safety Camp 00:00–05:34 — Why AI Safety?05:34–08:03 — How LLMs Changed AI Safety08:03–12:48 — What AI Still Lacks: Judgment12:48–16:29 — Beyond Guardrails: Pre-Aligned AI16:29–19:52 — Reliable Agents & Real-World Applications19:52–22:40 — AI Alignment Inside the Enterprise22:40–24:39 — Think Big, Think Small24:39–30:29 — From Research to Entrepreneurship Thanks for Peter Qin helps with the editing Wickey Wang *IT Security Compliance Leader & University Faculty *VC advisor and Angel Investor with cybersecurity and AI focus *GAI Security book co-author Questions, Suggestions, Feedback and Comments? You can find us in LinkedIn: https://www.linkedin.com/in/wickey-wang-cisa-six-sigma-green-belt-2aaa913/ https://www.linkedin.com/in/thomaskong/

  4. 30 Jul

    Innovator Coffee EP-40 How AI is rewriting the growth

    Welcome to the Innovator Coffee, a podcast that bridges the gap between people and the world of AI and innovation. This is Wickey. Follow us to explore the top AI products, ecosystem insights, and the emerging trends. AI is changing far more than how we build products, it is fundamentally reshaping how startups grow, how teams operate, and how companies compete. In this episode of Innovator Coffee, we bring together founders, growth leaders, and AI practitioners to explore how the AI era is rewriting the traditional SaaS playbook. We discuss the rise of one-person companies, Pieter Levels and the indie hacker movement, why products like Lovable are growing so quickly, and how AI is lowering the barrier to building software. We also dive into product-led growth (PLG), community-led growth, founder branding, influencer marketing, SEO, AI-native go-to-market strategies, and why distribution may become just as important as product itself. Finally, we examine how companies like Ramp are rethinking AI adoption by investing in internal AI infrastructure that enables every employee, not just engineers, to build AI applications. As AI democratizes software development, organizations may need to rethink not only how they build products, but also how they organize growth. Whether you're a founder, builder, marketer, investor, or simply curious about the future of AI-native companies, this conversation offers practical insights into the next generation of startup growth. Guests Joe Zhou: Co-host, Little Train Business Evolution Theory | B2B Startup head of growth Miranda Gao: Growth Marketing Leader, Major Tech Company Nil Ni: Founder, Makeform.ai | Indie Hacker Quanlai Li: Founder, ChatSlide AI | AI Growth & GTM Advisor | Vibe Hacker Timeline 00:00 – 02:25 | Guest Introductions & Why AI Is Creating New Growth Models 02:25 – 08:23 | Pieter Levels, Indie Hackers, and the Rise of One-Person Companies 08:23 – 12:47 | Lovable, Employee Marketing, and Building AI Products for Everyone 12:47 – 20:47 | Why Lovable Grew So Fast: PLG, Community-Led Growth, Branding, and Vibe Coding 20:47 – 27:26 | AI-Native Growth Strategies: Distribution, SEO, GEO, and Finding Product-Market Fit 27:26 – 35:07 | From $1M to $100M ARR: Growth Playbooks, Ramp, and AI Infrastructure 35:07 – 42:41 | Founder Branding, Sustainable Growth, Creator Marketing, and Enterprise GTM 42:41 – 50:50 | Influencer Marketing, Building an Audience, Final Advice, and Closing Thoughts Thanks for Peter Qin helps with the editing Wickey Wang *IT Security Compliance Leader & University Faculty *VC advisor and Angel Investor with cybersecurity and AI focus *GAI Security book co-author Questions, Suggestions, Feedback and Comments? You can find us in LinkedIn: https://www.linkedin.com/in/wickey-wang-cisa-six-sigma-green-belt-2aaa913/ https://www.linkedin.com/in/thomaskong/

  5. 16 Jul

    Innovator Coffee EP-39 How AI Is Changing Entrepreneurship | Stanford Professor on AI Startups, Trust & Customer Validation

    Welcome to the Innovator Coffee, a podcast that bridges the gap between people and the world of AI and innovation. This is Wickey. Follow us to explore the top AI products, ecosystem insights, and the emerging trends. AI has compressed the startup "validation cycle" from six months down to a single week — but is that actually a good thing? In this episode, we sit down with Chuck Eesley, Professor at Stanford's School of Engineering and Faculty Co-Director of the Stanford Technology Ventures Program (STVP), the entrepreneurship center that produced founders like Bobby Murphy (Snapchat) and Kevin Systrom (Instagram). A scholar who studies both how AI is reshaping entrepreneurship and how founders should think about AI safety, Chuck shares three counterintuitive findings: why persistence can actually hurt founders' long-term outcomes, why trust is an underrated competitive advantage in the AI era, and why replacing real customer conversations with AI conversations is one of the most common mistakes founders make. Guest Bios Professor ⁠Chuck (Charles) Eesley⁠ is a Professor in Stanford University's School of Engineering and Faculty Co-Director of the Stanford Technology Ventures Program (STVP), Stanford's Entrepreneurship Center. His research focuses on entrepreneurship, innovation, venture creation, AI, and startup ecosystems. Beyond Stanford, he also co-leads a family foundation supporting entrepreneurship and AI & computer science education for underserved communities around the world. 00:00-03:50Intro & Background: Chuck introduces himself (Stanford Engineering, STVP, family foundation). Opening question: what excites him most about AI right now? His answer: the "compression of the validation cycle" 03:50-10:57 What STVP Actually Teaches: The three pillars of STVP (research, teaching, community); 10:57-14:49 How AI Is Really Changing the Startup Process: It's never been possible to run so fast in the wrong direction. 14:49-22:30 Redefining AI Safety: Chuck argues the biggest misconception is that "AI safety" means "don't build killer robots." 522:30-29:34 Trust as an Underrated Moat + The Economics of Misinformation. 29:34-40:24The Data Truth Founders Refuse to Believe: Why the "solo unicorn founder" is a dangerous myth and team composition matters enormously; the gap between validating enthusiasm ("yeah, I'd use that!") versus validating actual behavior (calendar time, wallet commitment); 40:24-46:53: Pivot Signals and Timing Why growth stalling is often already too late as a signal; results from Chuck's large-scale A/B study (tens of thousands of founders) 46:53-61:18: Lightning Round & Closing 5–10 year AI predictions Thanks for Peter Qin helps with the editing Tom Kong *Stanford EE alumni, *Founder@ Stanford AGI Adventist Community (10K+ members so far from top VC, Engineers, startups from Silicon Valley ) *AI Lecturer, a serial entrepreneur in media and data. Advisor @ techtimes.com and heyboss.ai *AI deployment for 8 years, with NLP and recent LLMs (RAG, Agent, Diffusion) Wickey Wang *IT Security Compliance Leader & University Faculty *VC advisor and Angel Investor with cybersecurity and AI focus *GAI Security book co-author Questions, Suggestions, Feedback and Comments? You can find us in LinkedIn: https://www.linkedin.com/in/wickey-wang-cisa-six-sigma-green-belt-2aaa913/ https://www.linkedin.com/in/thomaskong/

  6. 2 Jul

    Innovator Coffee EP-38 World Models: The Missing Layer Between AI and the Physical World

    Welcome to the Innovator Coffee, a podcast that bridges the gap between people and the world of AI and innovation. Follow us to explore the top AI products, ecosystem insights, and the emerging trends. Guest Bios Dr. ChongKai Gao Dr. ChongKai Gao is a Visiting Ph.D. Student at Stanford University in Dr. Feifei Li’s lab, where he conducts research on robotic manipulation, visual planning, and world models. His work focuses on enabling robots to reason about future physical states, perform long-horizon task planning, and bridge AI perception with real-world decision making. Dr. JunFan Zhu Dr. JunFan Zhu is the organizer of the San Francisco Robotics & World Model Reading Club, bringing together researchers from leading AI labs to discuss frontier advances in robotics, embodied AI, and world models. His interests span world model architectures, evaluation, tactile intelligence, VLA systems, and the future roadmap of physical AI. Episode Description Large Language Models (LLMs) have transformed how AI understands language. But what happens when AI must understand and interact with the physical world? In this episode of Innovator Coffee, Stanford researcher Dr. ChongKai Gao and robotics researcher Dr. JunFan Zhu explain World Models, one of the fastest-growing areas in AI, Robotics, and Embodied AI. We explore how world models differ from LLMs, their relationship with Vision-Language-Action (VLA) models and Spatial Intelligence, and why companies like NVIDIA, Meta, and Google DeepMind are investing heavily in this field. We also discuss the biggest challenges in Physical AI, from data and simulation to evaluation, and what it will take for robotics to reach its own "ChatGPT moment." Timestamps 00:00 – 09:20 | What Is a World Model? World Models vs. Large Language ModelsWhy predicting the future matters more than predicting the next token09:21 – 21:40 | Mapping the World Model Landscape Five major technical routesJEPA, Dreamer, VLA, diffusion models, and hybrid architectures21:40 – 29:45 | Spatial Intelligence vs. Decision Making Fei-Fei Li's Spatial IntelligenceWhy robotics may need action before perfect 3D reconstruction29:45 – 38:30 | Visual Planning for Robot Manipulation Why robots need to "imagine" before actingVisual planning versus language planning38:30 – 46:00 | Research Bottlenecks and Missing Pieces Why deployment is much harder than demosTactile sensing, evaluation, calibration, and the "missing layer" between intelligence and capability46:00 – 55:00 | Where Will World Models Create Real Business Value? Games, autonomous driving, warehouse automation, and roboticsWhich applications may commercialize first?55:00 – 01:10:30 | Robotics' ChatGPT Moment Why robotics doesn't have a scaling law yetData flywheels, simulation, evaluation, and the future of embodied AI01:10:30 – End | Betting on the Future of Physical Intelligence Why leading researchers are investing in world modelsThe biggest open questions and what founders, researchers, and investors should watch next Tom Kong *Stanford EE alumni, *Founder@ Stanford AGI Adventist Community (10K+ members so far from top VC, Engineers, startups from Silicon Valley ) *AI Lecturer, a serial entrepreneur in media and data. Advisor @ techtimes.com and heyboss.ai *AI deployment for 8 years, with NLP and recent LLMs (RAG, Agent, Diffusion) Wickey Wang *IT Security Compliance Leader & University Faculty *VC advisor and Angel Investor with cybersecurity and AI focus *GAI Security book co-author Co-founderQuestions, Suggestions, Feedback and Comments? You can find us in LinkedIn: https://www.linkedin.com/in/wickey-wang-cisa-six-sigma-green-belt-2aaa913/ https://www.linkedin.com/in/thomaskong/

  7. 18 Jun

    Innovator Coffee EP-37 Too young to wait: Inside the minds of two Gen-Z AI founders

    Welcome to the Innovator Coffee, a podcast that bridges the gap between people and the world of AI and innovation. This is Wickey. Follow us to explore the top AI products, ecosystem insights, and the emerging trends. Episode Summary What does it take to build a real company before you're old enough to drive，or before you've finished college? Host Wickey digs into how two young founders found their own way in: the obsession that kept them building, the cold emails and competitions that opened doors, and the moments no one sees, a pitch that fell apart, a failed launch, being underestimated for their age. They get practical too, on pitching investors and going to market, and land on why their generation's real edge is shipping before they feel ready. Equal parts highlight reel and hard knocks, it's a look at what self-made looks like at 15 and 26. Guest Bios Aiden Shankar is a 15-year-old founder from SF Bay Area building SchoolACE, an AI-native ed-tech platform that provides a copilot for teachers and a personalized tutor for students, helping teachers with grading, content creation, and workflow automation, while giving every student personalized tutoring and support. He learned to code on Swift Playgrounds and picked up AI from Andrew Ng's online courses. Following this, he built SchoolACE the summer before high school and got selected as a Top 5 Conrad Challenge Global Finalist, one of the youngest among ~7,500 competitors, as well as winning the Startup World Cup qualifiers and a Stanford Business Competition. His startup is also a part of the NVIDIA Inception Program & Google for Startups. Brandon Chen is the 26-year-old Series A founder of Intent, an AI-translation messaging app serving ~1 million users across 200 countries (within a year). He cold-emailed top university professors at high school until one let him into a lab and published two papers, then pitched his way from pre-seed to Series A. Timeline (8 segments with start & end times) 1 00:03-01:33 Welcome & Introductions Wickey introduces Innovator Cafe; Aiden (15, School) and Brandon (26, Intent) introduce themselves and their companies. 2 01:33-03:19 Realizing They Were Different Each shares the moment their path diverged from peers. 3 03:19-05:48 What Sparked the Journey The origins of their drive: Aiden's obsession with building once he had an idea; Brandon's first-principles cold-emailing of professors from a poor province. 4 05:48-10:17 First Contact with AI & Entrepreneurship Brandon's 2020 GPT-3 experiments and junior-year game studio; Aiden's path from Swift Playgrounds to building School 5 10:17-16:09 Family, Peers & Hidden Struggles Reactions from parents and friends 6 16:09-21:39 The Stage: Competitions & First Pitches Aiden's first-place win at Stanford (15 teams from ~7,000); Brandon's co-founder pitching while he interned; his painful, cry-at-night first pitch and the road from seed to Series A. 7 21:39-30:41 Mistakes, Exhaustion & Resilience Biggest mistakes (confidence; building for self vs. users); turning down a 20% equity offer; Brandon's failed Stanford launch and the solo open-source project that won back his team. 8 30:41- 36:44 Advice & Their Generation Being underestimated for their age; whether their work lasts; advice to beginners ("build it overnight"); founders they admire; one word for their generation,"fearless", and go-to-market on Instagram. Special thanks to Hannah Wang who did the wonderful job to assist to complete this podcast. https://www.linkedin.com/in/hannah-wang-9302421b3/ Host：Wickey Wang *IT Security Compliance Leader & University Faculty *Growth fund VC advisor, VC fellow and Angel Investor with cybersecurity and AI focus *GAI Security book co-author & SafenAI co-founder Questions, Suggestions, Feedback and Comments? You can find us in LinkedIn: ⁠⁠⁠⁠https://www.linkedin.com/in/wickey-wang-cisa-six-sigma-green-belt-2aaa913⁠⁠⁠

  8. 4 Jun

    Innovator Coffee EP-36 Beyond the model - The real challenge of robotics

    Welcome to the Innovator Coffee, a podcast that bridges the gap between people and the world of AI and innovation. This is Wickey. Follow us to explore the top AI products, ecosystem insights, and the emerging trends. Guest Bio Joe Hsy is the Founder and CTO of Chestnut Robotics, a startup building dexterous manipulation platforms designed to address labor shortages in advanced manufacturing. Prior to founding Chestnut Robotics, Joe led end-to-end AI initiatives at XPeng and was an early member of the Foundation Model team at Waymo. Summary In this episode, Joe shares insights on dexterous manipulation, robotics data bottlenecks, foundation models for robots, startup building, and the future of physical intelligence. Joe also reflects on the transition from AI engineer to startup founder, the challenges of building a company from scratch, and why founders must become generalists capable of solving whatever problem is broken that day. Innovator Coffee bridges the gap between people and the world of AI and innovation. We interview founders, investors, researchers, and operators shaping the future of technology. Follow us for conversations on AI, robotics, cybersecurity, venture capital, and emerging technologies. Episode Summary Timeline 00:00 – 07:15 What Is Dexterous Manipulation? 07:15 – 11:55 Building Hardware and Software Together 11:56 – 16:15 Waymo vs. Tesla: Two Innovation Cultures 16:16 – 22:05 From Startup to Product in Nine Months 22:06 – 27:00 Open Source, Data, and the Business Model 27:01 – 32:00 Solving the Robotics Data Problem 32:01 – 40:20 The Road to Commercial Humanoid Robots 40:21 – 44:50 From Technologist to Founder 44:51 – 46:30 The Future of RoboticsKey QuoteAbout Innovator Coffee Special thanks to Hannah Wang who did the wonderful job to assist to complete this podcast. https://www.linkedin.com/in/hannah-wang-9302421b3/ Host：Wickey Wang *IT Security Compliance Leader & University Faculty *Growth fund VC advisor, VC fellow and Angel Investor with cybersecurity and AI focus *GAI Security book co-author & SafenAI co-founder Questions, Suggestions, Feedback and Comments? You can find us in LinkedIn: ⁠⁠⁠https://www.linkedin.com/in/wickey-wang-cisa-six-sigma-green-belt-2aaa913⁠⁠

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About

Welcome to the Innovator Coffee, a podcast that bridges the gap between people and the world of AI and innovation. We're Tom and Wickey. Follow us to explore the top AI products, ecosystem insights, and the emerging trends. Tom Kong *Stanford EE alumni, Founder@ Stanford AGI Adventist Community *AI deployment for 8 years, with NLP and recent LLMs Wickey Wang *BYU alumni and SCU CAAP alumni, Growth fund VC advisor and Angel Investor with cybersecurity and AI https://www.linkedin.com/in/wickey-wang-cisa-six-sigma-green-belt-2aaa913 https://www.linkedin.com/in/thomaskong/

Information

  • Creator
    Wickeyjw
  • Years Active
    2024 - 2026
  • Episodes
    59
  • Rating
    Clean
  • Copyright
    © Wickeyjw
  • Show Website
    Innovator Coffee

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