Profound

In this episode of the Profound Podcast, I continue the conversation with Dr. Bill Bellows and Lori Strom, moving deeper into the origins and intent behind the In2:In Thinking Network and what it truly means to “think about our thinking.”Bill shares the lesser-known backstory of how In2:In Thinking came to be, from its early roots as the West Coast Quality Forum to the deliberate choice to move beyond Deming’s name alone. He explains why creating new language matters when changing systems, and how words like “quality,” “thinking,” and even “together” can trap us in old meanings unless we consciously redefine them.The discussion turns to incentives, commissions, and performance management, one of the most difficult and controversial areas of applying Deming’s philosophy. Through real-world examples from sales organizations, manufacturing, and leadership roles, we explore how individual incentives often drive behavior that harms the system as a whole, even when intentions are good. Bill and I unpack why these problems aren’t about “bad people,” but about systems that reward the wrong outcomes.Lori introduces curiosity as a unifying theme, curiosity not just about external problems, but about our own assumptions, beliefs, and patterns of thinking. We connect curiosity to empathy, beginner’s mind, and the ability to see work as “part of” a larger system rather than isolated tasks. From parenting to leadership to organizational design, the conversation highlights how asking better questions can unlock better action.The episode closes by reinforcing a critical point: In2:In Thinking is not about endless reflection. Thinking about thinking must ultimately lead to better decisions, better cooperation, and better results. This balance between mindfulness and action, reflection, and delivery is at the heart of Deming’s work and the mission of the In2:In Thinking Network.

Join Lori Strom, a Deming Scholar and advocate for organizational transformation, and Dr. Bill Bellows, a leader in applying Deming's philosophy, as they dive into the relevance of Deming's ideas today. Lori shares her enlightening journey through the Deming Scholars MBA program, emphasizing a non-competitive, cooperative learning environment. Dr. Bellows reflects on the misinterpretation of Deming's work and the formation of the In2:In Thinking Network, exploring its importance in tackling modern challenges like burnout, education gaps, and the impact of AI.

I have a conversation with Diane Kulisek in this episode. Diane, a veteran in quality systems and regulatory affairs, shares her journey from Gillette to Rocketdyne to Johnson & Johnson, weaving in the principles of Deming and the realities of complex, high-stakes industries. We dive into W. Edwards Deming’s seminal perspectives on quality and how they’ve shaped Diane’s extraordinary career across aerospace, consumer products, and medical device manufacturing. We start with Diane’s early work at Gillette, where she first encountered military-grade quality standards, and move into her groundbreaking experience at Rocketdyne. There, she managed space shuttle main engine avionics and led self-managed teams. Diane highlights the power of elected management and the deep cultural dysfunctions she observed, drawing sharp analogies to adult children of alcoholics and the normalization of deviance in corporate environments.Our conversation then pivots to regulatory complexity. Diane explains how compliance efforts in medical device manufacturing must transcend minimum standards to uphold the priceless value of human life. She critiques the profit-centric motives of insurance companies and exposes the structural misalignments that can compromise quality in favor of greed and speed.We also explore the limitations and potential of AI in auditing, with Diane emphasizing the importance of human experience in identifying risk and systemic failures. She proposes the provocative idea of creating an “AI Deming,” using Deming’s extensive body of work to model principled decision-making.Diane’s reflections bring a critical eye to regulatory frameworks, the ethics of risk management, and the potential of technology to augment human insight. Through it all, she remains grounded in Deming’s enduring vision that quality is a moral imperative and a societal good.This is Diane's LinkedIn Page:https://www.linkedin.com/in/dkulisekShow Notes:1: https://www.scribd.com/document/451480272/MIL-Q-9858A-Quality-Program-Requirements-pdf2: https://adultchildren.org3: https://www.acquisition.gov/far/16.3054: https://www.wsj.com/articles/SB9918626065751548435: https://www.nasa.gov/wp-content/uploads/2015/04/708066main_Shuttle_Bibliography_2-ebook.pdf?emrc=c67e146: https://www.irvinestandard.com/2023/johnson-johnsons-innovation-irvine-roots-and-credo-to-give-back/7: https://asq.org/-/media/ASQ-Supplemental-Media-Import/1/3/9/2/6/ar_1106_105018.pdf8: https://www.dol.gov/sites/dolgov/files/oalj/PUBLIC/WHISTLEBLOWER/REFERENCES/STATUTES/SARBANES_OXLEY_ACT_OF_2002.PDF9: https://store.pda.org/TableOfContents/Risk_Assessment_Ch01.pdf10: https://www.healthcarefinancenews.com/news/class-action-lawsuit-against-unitedhealths-ai-claim-denials-advances11: 

In this episode, I have a conversation with Doug Finke. A 16-time Microsoft MVP and long-time technologist, Doug’s experience ranges from mainframe assembly programming to pioneering AI integrations in software development. We reminisce about the early days of system programming and explore how those foundational skills have enabled technologists like Doug to excel in the rapidly evolving world of AI.Doug shares his journey from COBOL and assembler to becoming a PowerShell innovator, highlighting how his early exposure to structured programming and domain-specific languages now serves as a superpower in working with large language models (LLMs). Our discussion pivots to the game-changing potential of AI, specifically the rise of function calling, modular design, and the Model-Context-Protocol (MCP). Doug explains how these patterns transform AI from simple copilots into powerful collaborators capable of orchestrating entire software systems.We also look at the implications of AI-driven software development for enterprises, examining whether vertical SaaS solutions may soon be disrupted by in-house, AI-built alternatives. Doug emphasizes how AI accelerates both code creation and maintenance, challenging long-held assumptions about whether to buy or build software.Our conversation concludes with a philosophical lens on teaching AI, the evolving role of junior developers, and the importance of naming, structure, and design patterns in crafting software that AI can effectively understand and extend. Whether you're deep into AI tooling or just starting to explore, Doug's perspective offers a clear bridge between classical computing and today's transformative technologies.

Lonnie Wilson, a former Chevron senior manager and dedicated Deming enthusiast, shares his transformative journey through the lens of W. Edwards Deming's philosophies on management and quality. He recounts attending Deming's seminar and grappling with the enigmatic nature of his teachings. The conversation navigates the challenges of applying Deming’s principles in corporate settings, addressing the tension between abstract concepts and practical applications. Lonnie raises intriguing questions about intellectual elitism in management, the nuances of cultural change, and the ongoing relevance of Deming's legacy.

I'm still trying to figure out how to produce the audiobook for Rebels of Reason. This is my first experiment with 11Labs. It's not great. I will have to work on the voice equipment; however, it's a start. I hope you enjoy it. 

In this thought-provoking discussion, Dr. Bill Bellows, co-founder of the In2:InThinking Network, shares his insights on systems thinking inspired by W. Edwards Deming. He delves into the significance of the upcoming In2:InThinking Forum, emphasizing the necessity of psychological safety for innovation. Dr. Bellows highlights how systems thinking can revolutionize fields beyond manufacturing, including software and education. He advocates for a culture of humility and collaboration, aiming to empower professionals to rethink traditional approaches and drive meaningful change.

In this episode, I have a fascinating conversation with Jim Highsmith. We dive into Jim’s six-decade career in software development, his role in the Agile movement, and how his early influences continue to shape his thinking on digital transformation today. Jim shares stories from the punch card era to the Agile Manifesto, offering insight into the evolution of our industry.We begin by exploring Jim's early work at Exxon, debugging code with hexadecimal printouts, and his eventual pivot into structured methods and adaptive development showing a career built on embracing risk, fostering change, and learning through experience.Jim recounts the serendipitous path that led him to the Agile Manifesto in 2001, where he collaborated with figures like Kent Beck and Martin Fowler. He shares how his early thinking around adaptive methodologies aligned with what became known as Agile, even before the term existed. Throughout, Jim highlights how technological shifts, especially the rise of the internet, fundamentally altered software's purpose requiring new development paradigms.In reflecting on Agile’s legacy, Jim contrasts optimization (à la Deming’s statistical process control) with adaptation (rooted in people, learning, and responsiveness). He emphasizes the importance of context in applying any methodology, whether Agile, Lean, or DevOps, and cautions against rigid orthodoxy in favor of flexible thinking. The conversation also touches on Deming’s influence, the missed opportunity for Agile and DevOps convergence, and Jim’s role in fostering integration between the Agile Alliance and the Project Management Institute (PMI).Looking to the future, Jim sees AI as a transformation on the scale of the internet, requiring organizations to adopt adaptive mindsets or risk irrelevance. He warns that those who fail at Agile will likely fail at AI if they don’t build adaptive learning into their culture. He advocates for reimagining agility not as a fixed set of practices, but as a living, philosophical approach responsive to continual change.

Mark Graban, a seasoned consultant and author specializing in Lean and continuous improvement, shares insights from his extensive career in manufacturing and healthcare. He highlights the enduring relevance of W. Edwards Deming’s principles, emphasizing the importance of learning from mistakes and the necessity of psychological safety for innovation. Mark discusses the Red Bead Experiment, illustrating systemic issues in management, and critiques corporate scandals like Wells Fargo, attributing them to systemic pressure rather than individual failings. His latest book focuses on cultivating a culture of learning and innovation.

In this episode, I have a fascinating conversation with Reuven Cohen, someone who I believe is one of the most important voices in AI today.  Reuven recounts his journey in technology, from being an early advocate of cloud computing to now working at the cutting edge of AI and reasoning models. He shares insights into how AI is shifting the nature of work, particularly in fields like software development, business operations, and decision-making. He describes AI as "cloud computing 2.0, but with intelligence," emphasizing its role in cognitive offloading—augmenting human capability rather than merely automating tasks.A key theme of the discussion is AI’s impact on productivity and workforce structure. Reuven shares staggering personal metrics—writing nearly 10 million lines of code in a year, something that would take a traditional developer thousands of lifetimes. He argues that AI is not replacing jobs outright, but fundamentally changing who remains valuable in an organization. He suggests that companies must decide whether to empower their top 10% to become exponentially more productive or replace the bottom 90% with AI-driven automation.The conversation also dives into reasoning models versus instruct models, discussing when to use each in business applications. Reuven explains neurosymbolic AI, a new frontier where AI models don't just process natural language but interact with the world using symbolic logic and mathematics. He believes this approach will be essential for future breakthroughs in AI comprehension and decision-making.As the episode progresses, John and Reuven reflect on the geopolitical landscape of AI, noting that China has become a dominant force in AI development. They discuss DeepSeek, the Chinese-developed reasoning model, and how it has disrupted traditional players like OpenAI and Google.To wrap up, Reuven shares his latest projects, including an AI-driven truth detection system, which sparked ethical debates about transparency, privacy, and misinformation. He envisions a future where AI is not just an assistant but an autonomous force that reshapes industries, economies, and even the nature of work itself.