Profound

In this episode, I invite Tracy Ragan, CEO of DeployHub, on the podcast for an in-depth discussion on the evolution of DevOps, the complexities of modern software systems, and the cultural challenges women face in technology. Tracy's rich history in software development, from working on mainframes in the late 1980s to spearheading DevOps advancements, provides a fascinating lens through which to examine the industry.

Key Topics Discussed:

1. The Historical Context of DevOps: Tracy recounts the industry's shift from mainframe to distributed systems and the lessons learned (and forgotten) along the way. She highlights the recurring mistakes in adopting "shiny new objects" without addressing foundational issues, such as dependency chaos and scripting overuse.
2. AI and Long-Tail Productivity: Tracy and John explore AI's transformative potential, emphasizing that its real impact lies in long-term gains rather than short-term ROI. Tracy draws parallels to past transitions, like the adoption of relational databases, arguing that AI's value will be fully realized only with improved system architectures.
3. The Persistent Challenge of Women in Tech: Tracy candidly discusses her experiences as a woman in a male-dominated industry, noting a regression in gender diversity, particularly post-COVID. She highlights systemic issues, including exclusion from key networking opportunities and persistent biases, advocating for cultural shifts to empower women in tech.
4. DeployHub’s Role in Tackling DevOps Complexity: Tracy introduces DeployHub's innovative approach to managing software supply chains and SBOMs (Software Bill of Materials). By mapping dependencies and automating vulnerability remediation, DeployHub aims to reduce the time and complexity of patch management, addressing critical gaps in modern software pipelines.

In this episode of The Profound Podcast, I sit down with Dr. Jabe Bloom, a researcher and expert in systems thinking, AI, and digital transformation. We explore Eric Lawson’s book The Myth of AI, tackling the contentious debate around artificial general intelligence (AGI). Dr. Bloom offers insights from his dissertation and divides the ongoing discourse on AI into two camps: dogmatists and pragmatists. Dogmatists believe AGI is inevitable, while pragmatists focus on the practical impacts of current AI technology, such as large language models (LLMs), and how these will reshape businesses, education, and society.

Throughout the episode, Dr. Bloom explains his framework for thinking about AI, touching on proactionary versus precautionary approaches to its development and regulation. He also draws connections between these ideas and W. Edwards Deming’s principles, especially around abductive reasoning—a concept that links back to Dr. Bloom’s past discussions about AI’s potential in problem-solving.

The conversation takes a critical view of AGI's feasibility, with Dr. Bloom emphasizing the current challenges AI faces in replicating abductive reasoning, which involves making intelligent guesses—a capability he argues machines have yet to achieve. We also dive into examples from fields like DevOps, healthcare, and city planning, discussing where AI has shown great promise and where it still falls short.

Key takeaways from the episode include the importance of addressing present AI technologies and their immediate impacts on work and society, as well as the ongoing need for human oversight and critique when using AI systems.

In this episode of the Profound Podcast, I speak with Erik J. Larson, author of The Myth of Artificial Intelligence, about the speculative nature and real limitations of AI, particularly in relation to achieving Artificial General Intelligence (AGI). Larson delves into the philosophical and scientific misunderstandings surrounding AI, challenging the dominant narrative that AGI is just around the corner. Drawing from his expertise and experience in the field, Larson explains why much of the AI hype lacks empirical foundation. He emphasizes the limits of current AI models, particularly their reliance on inductive reasoning, which, though powerful, is insufficient for achieving human-like intelligence.

Larson discusses how the field of AI has historically blended speculative futurism with genuine technological advancements, often fueled by financial incentives rather than scientific rigor. He highlights how this approach has led to misconceptions about AI’s capabilities, especially in the context of AGI. Drawing connections to philosophical theories of inference, Larson introduces deductive, inductive, and abductive reasoning, explaining how current AI systems fall short in their over-reliance on inductive methods. The conversation touches on the challenges of abduction (the "broken" form of reasoning humans often use) and the difficulty of replicating this in AI systems.

Throughout the discussion, we explore the social and ethical implications of AI, including concerns about data limitations, the dangers of synthetic data, and the looming “data wall” that could hinder future AI progress. We also touch on broader societal impacts, such as how AI’s potential misuse and over-reliance might affect innovation and human intelligence.

In this episode of The Profound Podcast, I have an enlightening conversation with Dr. Jabe Bloom, a prominent voice in the fields of DevOps and digital transformation. The discussion revolves around the philosophical underpinnings of scientific reasoning and its application to complex systems, particularly through the lens of Charles Sanders Peirce's work on abductive reasoning.

Jabe Bloom begins by exploring Peirce’s contributions to philosophy, particularly how Peirce's concept of abductive reasoning offers a framework for making educated guesses in situations where data is incomplete or variables are unknown. This idea becomes especially pertinent when Bloom contrasts the scientific method typically used in complicated domains, like Lean manufacturing, with the unpredictability of complex systems, where multiple hypotheses might be equally valid.

The conversation further delves into how these ideas connect to digital transformation, especially in organizations navigating the complexities of modern IT and business environments. Bloom highlights the importance of fostering environments where experimentation and educated guessing are encouraged, as this aligns with Peirce's pragmatic approach, which values the usefulness of an idea over its absolute truth.

To wrap up, we also discuss the broader implications of Peirce’s work on modern AI and socio-technical systems, emphasizing the need for a deeper understanding of how these systems operate and how to integrate artificial intelligence into complex human processes.

In this episode of The Profound Podcast,  I speak with Andrew Clay Shafer, a pivotal figure in the DevOps community and a key influencer in the industry. They delve into the evolution of DevOps, its current state, and its implications for the future, particularly in the context of digital transformation.

The conversation begins with a reflection on the early days of DevOps and Agile, highlighting key milestones and the ongoing relevance of foundational principles, such as those proposed by W. Edwards Deming. Shafer emphasizes the timeless nature of these principles and their application beyond any buzzword lifecycle. The dialogue then transitions to the challenges and opportunities within the industry, addressing the impact of macroeconomic forces, the rise of AI, and the buzz around platform engineering.

A significant portion of the discussion revolves around the importance of organizational learning and the necessity for companies to understand and adapt their processes to achieve true transformation. Shafer shares his insights on the common pitfalls organizations face when adopting new methodologies, stressing the need for contextual understanding and incremental improvement rather than superficial adoption of new terms or tools.

The episode also touches on the concept of platform engineering as a continuation of the DevOps philosophy, rather than a separate or novel idea. Then to wrap up, we discuss the marketing dynamics that drive the emergence of new buzzwords and the critical need for genuine integration and alignment within organizations to realize the benefits of these practices.

You can find Andrew Clay Shafer's LinkedIn below:
https://www.linkedin.com/in/andrewclayshafer/

In this episode, I speak with Joseph Enochs, Managing Director of AI/ML and Emerging Technologies at Enterprise Vision Technologies. Known for his extensive background in DevOps and digital transformation, Joseph shares his remarkable journey transitioning into the AI domain.

Joseph begins by recounting how his interest in AI was sparked, notably influenced by the foundational concepts of W. Edwards Deming and the subsequent developments in DevOps. He details the pivotal moments that led him to pursue a master's degree in AI, highlighting the importance of continuous learning and the foresight needed to anticipate technological trends.

The discussion covers the evolution and integration of AI within large enterprises, emphasizing the challenges and strategies for incorporating AI into existing systems. Joseph explains the significance of vector databases, context windows, and the roles of orchestrators and agents in enhancing AI capabilities. He also delves into the practical applications of AI in business, such as improving call center efficiency and automating complex tasks.

In the final segment, Joseph offers practical advice on how to start learning about AI, emphasizing the importance of experimentation and validation of assumptions. The episode concludes with a reflection on the profound impact AI is set to have on the future of technology and business.

In this episode, I sit down with Dr. Barbara Lawton, a distinguished statistician and expert in experimental design. Dr. Lawton shares her journey from studying biology and ecology to diving deep into statistics, eventually finding herself at the Rocky Flats nuclear weapons facility. It was here she experienced a pivotal moment that led her to W. Edwards Deming's teachings.

Dr. Lawton recounts how a significant project at Rocky Flats fell apart due to budget cuts, illustrating Deming's principle that quality is determined in the boardroom. This realization propelled her to attend a seminar by Deming, which profoundly changed her perspective on quality and management. She describes her experience of traveling with Deming, learning from his insights, and understanding the importance of continuous learning and adaptation.

The conversation delves into Deming's System of Profound Knowledge (SoPK), highlighting its relevance in today's fast-evolving world. Dr. Lawton emphasizes the need for an appreciation of systems, understanding of variation, psychology, and theory of knowledge, and expands on these concepts by integrating ideas from physics and ecology. She discusses the role of entropy, thermodynamics, and the dynamic nature of systems, explaining how these principles apply to modern organizations and leadership.

Dr. Lawton also touches on the importance of emotional intelligence, mindfulness, and effective communication in leadership. She advocates for creating environments that foster continuous learning and adaptability, essential for navigating the complexities of today's digital landscape.

You can find Dr. Barbara Lawton's LinkedIn Below:
https://www.linkedin.com/in/barbara-lawton-8b920b6/

Show Notes:
https://www.youtube.com/watch?v=sZ2U7F0RJd0

https://www.youtube.com/watch?v=WWiH5S55iDg&t=25m28s

In this insightful episode of the Profound Podcast, I speak with Angela Montgomery, co-founder of Intelligent Management and author of the upcoming book, The Human Constraint. Angela shares her unique journey from a background in arts to collaborating with physicists. The conversation delves into the artificial barriers within organizations, the importance of systemic thinking, and how integrating Deming's System of Profound Knowledge with the Theory of Constraints can drive meaningful change.

Angela highlights the critical differences between bottlenecks and constraints, emphasizing the strategic value of identifying and managing constraints to enhance organizational flow. She also discusses the challenges of adopting a systemic approach in traditional hierarchical structures and the role of mental models in limiting or advancing organizational potential.

Through practical examples and narrative, Angela illustrates the transformative power of the Decalogue Method, which combines scientific rigor with literary storytelling. She also touches on her collaboration with renowned playwright Donald Freed to ensure the book's narrative is engaging and accessible.

This episode is a must-listen for business leaders and practitioners interested in continuous improvement, conflict resolution, and embedding innovation into daily practice. Angela's insights offer a fresh perspective on leveraging systemic thinking to achieve sustainable organizational success.

In this episode, I had a conversation with Mike Beck. We dive deep into W. Edwards Deming's seminal perspectives on quality and their application in the automotive and healthcare sectors. Mike, with his vast experience at General Motors and Toyota, shares compelling stories and insights on how Deming's principles transformed his approach to engineering and management.

Mike Beck's journey began as a mechanical engineer at General Motors in 1979, a time when the company held a dominant market share. His career took a significant turn after attending Deming’s seminar in 1984, which profoundly influenced his perspective on quality and management. This episode captures Mike's evolution from a reliability and test engineer to a leader in statistical methods and quality improvement at GM.

Key Discussion Points:

1. Early Career and Deming’s Influence:
   • Mike details his early career at General Motors, the transition of GM from the market leader, and his first exposure to Deming’s teachings which significantly shifted his approach towards statistical methods and leadership​​.
2. Implementing Statistical Methods:
   • He discusses his application of statistical methods in engine development, particularly using Taguchi methods and design of experiments (DOE) to tackle the issue of bore distortion in the Quad 4 engine​​.
3. Deming’s Consultancy at GM:
   • Mike shares insights from GM's decision to hire Deming as a consultant, and how this influenced the creation of the Powertrain Statistical Network and a master’s program in statistics, fostering a culture of continuous improvement and statistical thinking within the company​​.
4. Transition to Toyota:
   • His move to Toyota offered a unique comparison between American and Japanese approaches to quality. Mike highlights Toyota’s meticulous production engineering processes, incremental changes, and the profound cultural differences that underpin their success in quality management​​.
5. Cultural and Management Lessons:
   • Mike elaborates on the concept of "catchball" in Hoshin Kanri, emphasizing the importance of alignment and communication in achieving organizational objectives. He also contrasts the Western and Eastern views on time and efficiency, shedding light on how Toyota’s approach to planning and reflection contributes to their sustained excellence​​.

Show Notes:

Mike's Email: [email protected]

In this episode of the Profound Podcast, I have a conversation with Rob Park. Rob shares his journey from early involvement in extreme programming (XP) to his current fascination with W. Edwards Deming's principles and their application in modern software development.

Rob's career path offers a rich tapestry of experiences, from using case tools and adopting scrum practices before they were widely recognized, to working with Kanban and continuous integration/continuous delivery (CI/CD) processes. He reminisces about his introduction to Deming's work through the influence of notable figures in the agile community.

A significant portion of the discussion delves into the integration of Deming's theories into software practices. Rob talks about the impact of statistical process control (SPC) and control charts on his work, emphasizing the importance of understanding variation and employing data-driven decision-making. He highlights the utility of Dr. Donald Wheeler's teachings on process behavior charts and the critical difference between enumerative and analytical statistics.

The episode wraps up with Rob reflecting on the broader implications of Deming's work, advocating for its relevance in addressing contemporary challenges in software development. He shares his experiences of applying Deming's theories in real-world scenarios, illustrating how these timeless concepts continue to drive quality and efficiency in the digital age.

You can find Rob Park's LinkedIn below:
https://www.linkedin.com/in/robpark-4ls/