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.

In this episode, I have an insightful and wide-ranging conversation with Carol Houle, CEO of Inspire Digital Consulting. We explore her career journey across software development, lean supply chain transformation, cloud, and DevOps, and how these experiences led her to a central conviction: leadership is the primary bottleneck in digital transformation.

Carol traces her roots back to early exposure to TQM and W. Edwards Deming during her undergraduate studies and her work at Pricewaterhouse Consulting in the 1990s, where lean principles were applied to supply chains. As Carol moved into larger leadership roles, a consistent pattern emerged: transformation efforts stalled not because of teams or tools, but because leaders themselves were the constraint. Yet leadership is rarely examined.

Carol introduces her book and the Inspired Leadership Framework, which grew organically over a decade of observation, writing, and experimentation. Drawing from her experience spanning business, she distills leadership into measurable dimensions.

Looking forward, Carol connects leadership quality to the coming era of agentic AI. AI will amplify whatever already exists. Weak leadership, unclear purpose, or misaligned incentives will scale into systemic risk. She introduces the idea of “benevolent AI agents” that help detect bias, misalignment, and deviations from stated intent.

Show Notes:

You can learn more about Inspired Digital Consulting and take the Inspired Leadership Assessment here - https://inspiredigitalconsulting.com/

Carol Houle's LinkedIn - https://www.linkedin.com/in/carolhoule/