I have a conversation with Kendra MacDonald in this episode. As CEO of Canada’s Ocean Supercluster, Kendra is helping reshape how industries, governments, researchers, and technologists collaborate around one of the planet’s most important and least understood systems: the ocean. We dive deep into how emerging technologies like AI, autonomous systems, and quantum computing are transforming the ocean economy, while also exploring the organizational and leadership challenges that come with innovation at scale.

Kendra explains how the Ocean Supercluster was created as a national effort to accelerate commercialization, strengthen collaboration, and modernize ocean industries through technology. The conversation expands beyond marine innovation into broader themes of systems thinking, digital transformation, and the importance of solving business problems before deploying technology. Drawing from her background at Deloitte and her work advising organizations on technology adoption, Kendra shares why so many AI initiatives struggle, not because of the tools themselves, but because organizations fail to align culture, governance, and operational goals.

We also explore the tension between innovation and governance, challenging the common belief that controls slow progress. Kendra argues that thoughtful governance, risk management, and cross-functional collaboration actually accelerate innovation by creating trust and reducing downstream failures. The discussion touches on AI risk in high-consequence environments, autonomous shipping, data trust, digital twins, predictive maintenance, and the growing role of AI in optimizing maritime operations.

One of the most compelling parts of the conversation centers on the future of quantum computing and its potential impact on ocean science, logistics, climate prediction, and biodiversity discovery. Kendra and John reflect on how industries can prepare now for technologies that may radically reshape optimization and decision-making in the coming decade.

The episode ultimately becomes a broader reflection on interconnected systems, oceans, organizations, technology ecosystems, and society itself. Kendra offers a powerful reminder that the ocean is not simply a coastal issue, but a global infrastructure system affecting supply chains, climate resilience, communications, energy, and food security. It’s a thoughtful discussion about innovation stewardship, systems thinking, and the responsibility of leaders to build technology strategies grounded in purpose and long-term impact.

I have a conversation with Farhan Sheikh in this episode. We dive deep into W. Edwards Deming’s System of Profound Knowledge and explore how its principles can be applied to modern software development and AI-assisted coding.

Farhan shares his unique journey from developer to QA leader, where he applied Deming’s philosophy, particularly variation, theory of knowledge, and systems thinking, to transform how teams approach quality. Rather than relying on inspection at the end, he emphasizes building quality into the process through better test design, tighter feedback loops, and collaboration between testers and developers.

A central theme is Farhan’s “Darmok” approach: using structured examples and test cases to guide AI systems like Claude, instead of relying heavily on prompts. By feeding AI consistent, well-sequenced patterns, he demonstrates how teams can reduce variation in AI-generated code and achieve more reliable outcomes. This mirrors Deming’s principles, controlling variation and improving systems rather than reacting to defects.

The conversation also explores the evolving role of QA. Farhan argues that testers, with their strength in asking critical questions and creating clear examples, are uniquely positioned to become key players in AI-driven development. This shift blurs traditional roles, pointing toward a new kind of multidisciplinary “AI producer” who integrates development, testing, and system-level thinking.

Psychology and leadership emerge as critical factors. Farhan candidly discusses overcoming fear within teams, aligning motivations through data and experimentation, and the importance of leaders enabling systemic change rather than reinforcing silos.

The episode concludes with a powerful reflection: true digital transformation isn’t about adopting AI tools in isolation, but about rethinking the entire system of work through Deming’s lens, focusing on quality, reducing variation, and empowering people to learn and adapt.

In this episode, Glenn Wilson, a cybersecurity expert, joins me to explore how systems thinking can reshape how we approach cybersecurity, vulnerability management, and modern digital systems.

Glenn shares his journey from writing about DevSecOps to pursuing a master’s degree in Systems Thinking in Practice at the Open University. His motivation came from recognizing a troubling contradiction that, despite massive investments in cybersecurity, data breaches, ransomware incidents, and security failures continue to rise. This led him to question whether the industry’s largely reductionist approach misses the broader system dynamics at play.

A central part of the discussion focuses on Stafford Beer’s Viable System Model (VSM), a cybernetic framework for understanding how organizations maintain balance and adapt to their environments. Glenn explains how VSM’s five subsystems can be used to diagnose why cybersecurity systems often fail. Rather than viewing security as a set of tools or controls, Glenn argues it should be understood as a living system embedded within larger organizational and risk systems.

The conversation then expands into cybernetics, emergence, and AI, touching on Norbert Wiener, Ross Ashby’s law of requisite variety, and John Boyd’s OODA framework. Together, we discuss how feedback loops, adaptation, and emergent behavior shape both human organizations and AI-driven systems. Glenn raises an important concern: if organizations don’t adopt systems thinking, increasing automation and AI could amplify weaknesses rather than solve them.

We close by reflecting on the relationship between humans, AI, and complex systems. Glenn emphasizes that AI should be treated as a tool within a larger system, not anthropomorphized as human intelligence. The key challenge ahead is understanding how humans and intelligent tools coexist within systems that are adaptive, emergent, and increasingly complex.

The big takeaway: cybersecurity cannot be improved by optimizing isolated parts. Real progress requires understanding the entire system and our place within it.