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Published by Victor Holmin
Audio companions to my writing on strategy, technology, AI, cybersecurity and building technology businesses. Each edition explores one of my published articles through an AI-generated discussion or debate, offering another way to engage with its central ideas. These are not interviews or original podcast episodes, and the voices are not mine. The written article remains the definitive version. This channel is currently a pilot, and the format will evolve as I learn what works.
On the charts
Every published chart this podcast appears in, in the snapshot behind this page. Each one links to the chart it came off.
The Mato Topic Intelligence Platform does not report this podcast as charting in a published category in this snapshot.
From the feed
The latest episodes published to this podcast’s own RSS feed. Titles and descriptions are the publisher’s.
This pilot audio edition explores the argument behind No, You Can’t Budget Your Way to a Strategy . The discussion examines why revenue, margin and cost targets do not constitute a strategy. Budgets and financial models can express ambition, test affordability and expose unrealistic assumptions. They cannot explain why customers will buy, what is preventing better performance or which capabilities the business must develop. It explores strategy as a form of problem solving. This begins with framing the challenge correctly, distinguishing between gaps in effort, capability and strategic choice, then developing actions that reinforce one another. More performance reviews, stronger incentives or increasingly detailed forecasts cannot compensate for an incomplete diagnosis. The discussion also considers the tension involved in transformation. Immediate financial results may obscure the work of building future capabilities, while individually rational decisions across functions can collectively weaken the proposition. Management and boards must therefore examine spending, cost reductions and commercial initiatives in relation to the business they are trying to build. The central question is simple: What must change in the business to make these numbers credible? This is an AI-generated discussion based on my published article. It offers another way to engage with the ideas, but it is not an interview or a recording of me. The written article remains the definitive version. Read the original article on Medium .
This pilot audio edition explores the argument behind If You Were Founding Your Business Today, Would You Build It the Same Way? The discussion examines how AI is changing the economics of building companies and products. Software can be developed and tested faster, while teams across marketing, analysis, support and other functions can experiment and create value with fewer traditional constraints. It asks whether established businesses would choose the same products, structures, processes and investments if they were starting today. The greater opportunity may not be to perform the same work with fewer people. It may be to redirect the capacity created by AI towards innovation, growth and a better customer experience. The discussion also considers what this demands from leaders. Reinvention requires the imagination to see a different company, the technological fluency to understand what has become possible and the courage to reconsider how the business creates value. The gap between that possibility and the company as it operates today is where the transformation agenda begins. This is an AI-generated discussion based on my published article. It offers another way to engage with the ideas, but it is not an interview or a recording of me. The written article remains the definitive version. Read the original article on Medium .
This pilot audio edition explores the argument behind Hype as a Coordination Tool and the Trap of “Irreversible Standards” in AI . The discussion examines how hype can operate as more than marketing. In fragmented AI markets, a compelling narrative can coordinate investment, talent, partnerships and complementary innovation around a common direction. Using Renaissance Florence as a point of comparison, it considers how narrative itself can become a source of strategic influence. It also explores the danger that rapid coordination can turn early frameworks, platforms and business practices into de facto standards before their technical or economic merits are fully tested. Network effects, integrations, specialist skills and sunk costs can then make those choices difficult to reverse, reducing competition and locking the market into inefficient paths. The discussion asks how organisations and policymakers can retain the coordinating benefits of hype while avoiding premature lock-in through open and modular systems, adaptive regulation, careful experimentation and evidence-based adoption. This is an AI-generated discussion based on my published article. It offers another way to engage with the ideas, but it is not an interview or a recording of me. The written article remains the definitive version. Read the original article on Medium .
This pilot audio edition explores the argument behind The Emerging Threat of AI-Powered Cybercrime . The discussion examines how state-affiliated groups linked to China, Iran, North Korea and Russia have used AI to support cyberattacks and influence operations. These uses include reconnaissance, vulnerability research, scripting, malware debugging, phishing and the creation of deceptive online content. The evidence suggests that AI is currently strengthening familiar stages of cyber operations rather than creating fundamentally new attack techniques. However, greater speed, efficiency and accessibility could lower the barriers to sophisticated attacks. More capable systems could also enable persuasive influence campaigns and deeper attacks against critical infrastructure. The discussion considers how organisations and governments should respond through AI-specific security, adversarial testing, collaborative intelligence sharing, trustworthy models, responsible governance and greater transparency around AI misuse. This is an AI-generated discussion based on my published article. It offers another way to engage with the ideas, but it is not an interview or a recording of me. The written article remains the definitive version. Read the original article on Medium .
This pilot audio edition explores the argument behind The Emerging Threat of AI-Powered Cybercrime . The discussion examines how state-affiliated groups linked to China, Iran, North Korea and Russia have used AI to support cyberattacks and influence operations. These uses include reconnaissance, vulnerability research, scripting, malware debugging, phishing and the creation of deceptive online content. The cases examined suggest that AI was primarily enhancing established stages of cyber operations rather than enabling fundamentally new attack techniques. However, greater speed, efficiency and accessibility could lower the barriers to sophisticated attacks. As the technology improves, it could also enable more persuasive influence campaigns and deeper attacks against critical infrastructure. The discussion considers how organisations and governments should respond through AI-specific security, adversarial testing, collaborative intelligence sharing, trustworthy models, responsible governance and greater transparency around AI misuse. This is an AI-generated discussion based on my published article. It offers another way to engage with the ideas, but it is not an interview or a recording of me. The written article remains the definitive version. Read the original article on Medium .
This pilot audio edition explores the argument behind AI Power Demands: Chiplets & the Future Beyond Moore’s Law . The discussion examines how AI’s rapidly growing demand for computing power and energy is colliding with the physical and economic limits of traditional transistor scaling. GPUs have sustained much of AI’s progress, but each generation brings greater power consumption, heat and manufacturing complexity. Performance can no longer depend on Moore’s Law alone. It explores chiplets and heterogeneous integration as an alternative path. By combining smaller components designed for different functions, manufacturers can improve flexibility, production yields and cost efficiency. Advanced packaging, faster interconnects and common standards could make this modular approach fundamental to the future of AI and high-performance computing. The discussion also compares NVIDIA’s cautious adoption of chiplets with AMD’s longer commitment to modular design. AMD may hold structural advantages in flexibility and manufacturing efficiency, while NVIDIA retains a powerful position through CUDA, networking and its integrated computing platform. This is an AI-generated discussion based on my published article. It offers another way to engage with the ideas, but it is not an interview or a recording of me. The written article remains the definitive version. Read the original article on Medium .
This pilot audio edition explores the argument behind Adversarial Attacks on AI: Navigating Emerging Cybersecurity Threats . The discussion examines how AI systems can be manipulated through carefully crafted inputs, poisoned training data, privacy attacks and hidden backdoors. As these systems become embedded in healthcare, finance, defence and other critical environments, failures may no longer remain confined to the model: they can affect the wider services and infrastructure that depend on it. Drawing on research into large language models exploiting web vulnerabilities and adversarial attacks against cooperative multi-agent systems, it considers how increasingly capable AI could make some forms of cyberattack more efficient, affordable and difficult to detect. It also examines the potential interest of state-sponsored actors, while recognising that phishing, social engineering and conventional software exploitation often remain simpler and more effective routes of attack. The discussion asks how organisations can prepare for this evolving threat landscape through adversarial testing, model hardening, continuous monitoring, updated threat models and frameworks such as MITRE ATLAS. It argues that technical safeguards alone are insufficient: effective protection must also address the people, processes and information surrounding the AI system. This is an AI-generated discussion based on my published article. It offers another way to engage with the ideas, but it is not an interview or a recording of me. The written article remains the definitive version. Read the original article on Medium .
This pilot audio edition explores the argument behind Autonomous AI Agents: Redefining Economic Actors in the Digital Age . The discussion examines how AI is moving beyond narrow task automation towards agents that can sense, decide and act within dynamic environments. Drawing on agency theory and experiments such as Project Sid, it considers what happens when AI agents begin coordinating with one another, conducting transactions and forming complex social and economic structures. It also explores the implications for human–AI collaboration, market dynamics, value distribution, business models and the governance required to keep increasingly autonomous agents aligned with human goals. This is an AI-generated discussion based on my published article. It offers another way to engage with the ideas, but it is not an interview or a recording of me. The written article remains the definitive version.
This pilot audio edition explores the argument behind NVIDIA’s CUDA: The Winning Strategy for AI and Computing Innovation . The discussion examines how CUDA transformed NVIDIA’s GPUs from specialised graphics processors into a general-purpose computing platform, and why the company’s long-term investment in programmability became strategically decisive. It considers how developer tools, software libraries and widespread adoption created reinforcing ecosystem effects; how the integration of proprietary software and hardware established a durable competitive advantage; and why CUDA became foundational to advances in high-performance computing, machine learning and AI. This is an AI-generated discussion based on my published article. It offers another way to engage with the ideas, but it is not an interview or a recording of me. The written article remains the definitive version. Read the original article on Medium .
This pilot audio edition explores accelerated computing as a foundation for AI-powered business transformation . The discussion considers how digital operating models use data, analytics, AI and automation to change the economics of scale, learning and innovation. It examines why AI transformation depends not only on models and applications, but also on the computing infrastructure required to process growing workloads efficiently. It also explores the role of GPUs, TPUs and parallel computing in improving performance, scalability, energy efficiency and time to market, and asks what an accelerated infrastructure strategy means for business leaders preparing for AI-driven competition. This is an AI-generated discussion based on my published article. It offers another way to engage with the ideas, but it is not an interview or a recording of me. The written article remains the definitive version. Read the original article on Medium .
This pilot audio edition explores the argument behind NVIDIA’s Strategy: From GPUs to AI Industry Dominance . The discussion examines how NVIDIA moved beyond graphics hardware to build a full computing platform around GPUs, CUDA, networking and application-specific systems. It considers how developer adoption and ecosystem effects strengthened the company’s position, how its expansion into data-centre-scale computing supported the growth of AI, and how Blackwell extended its platform strategy. This is an AI-generated discussion based on my published article. It offers another way to engage with the ideas, but it is not an interview or a recording of me. The written article remains the definitive version.
Ranking source
Apple Podcasts rankings via the Mato Topic Intelligence Platform.
Observed September 21, 2026. Cached outside the daily freshness window; the positions keep the date they were taken on.
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