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.

In this episode, I talk with returning guest Joseph Enochs about the artificial intelligence (AI) world and its implications for businesses and innovation. A major highlight of the conversation is an analysis of DeepSeek, an open-source AI model developed by a Chinese company. Joseph explains how DeepSeek and similar models demonstrate that AI development is becoming increasingly accessible globally. With only a fraction of the computing resources used by giants like OpenAI and Meta, DeepSeek has replicated the performance of cutting-edge models like GPT-4. This, Joseph notes, is a clear example of how creativity and resourcefulness can overcome technological constraints, further accelerating the democratization of AI.The conversation also dives into emergent behaviors, where AI models demonstrate the ability to reason about new and unseen data, similar to human problem-solving. Joseph discusses critical benchmarks like GPQA (Google-Proof Question Answering) and the ARC Prize, which measure these capabilities. He highlights how modern models use reinforcement learning to develop reasoning skills, making them capable of tackling complex tasks at an unprecedented level of sophistication.We also touch on practical business considerations, such as how organizations can evaluate AI models for cost-efficiency and task-specific performance. Joseph advises leaders to use AI-driven frameworks to determine when to invest in high-cost, high-performance models like GPT-4 Omni versus smaller, fine-tuned models for less complex problems. He underscores that open-source innovations will continue to push costs down and improve accessibility for businesses of all sizes.The discussion wraps up with a reflection on the importance of knowledge sharing, applied research, and collaborative learning to accelerate the adoption of AI in solving real-world problems.

In this episode, I continue my conversation with Laksh Raghavan, a cybersecurity leader and systems thinker, diving into profound insights on applying multidisciplinary approaches to organizational challenges. Picking up from Part 1, this discussion illuminates the principles of W. Edwards Deming and other thought leaders in fostering organizational reliability, productivity, and innovation.The episode opens with a discussion on Herbert Simon's "satisficing" and its organizational implications. Laksh emphasizes how businesses like McDonald's excel by prioritizing reliability over perfection, ensuring consistent experiences across global markets. He connects this to Deming's principles of variation reduction, explaining how psychological perceptions of quality—rather than objective measures—often dictate success. This theme extends to companies like Apple, which masterfully align human psychology with technological precision to command premium loyalty and profits.We also explore behavioral science's role in technology and consumer behavior, from Uber's elimination of uncertainty in ride-hailing to Google's laser focus on search quality. They highlight the importance of understanding human psychology when solving organizational problems, as demonstrated by the famous "elevator mirrors" anecdote from Manhattan skyscrapers. Laksh masterfully ties these insights to modern developer productivity, arguing that reducing psychological friction, rather than merely optimizing technical processes, leads to sustainable performance improvements.The conversation crescendos with a deep dive into systems thinking, advocating for leadership frameworks that address interconnected "messes" rather than isolated problems. Laksh shares the vital role of education and storytelling in cultivating systemic thinking within organizations, drawing parallels between Deming’s teachings and modern challenges in cybersecurity and software delivery.You can learn more  about the Cyb3rSyn community and join through the following links below:https://www.cyb3rsyn.com/https://www.cyb3rsyn.com/p/announcing-cyb3rsyn-labs

In this episode of The Profound Podcast, I welcome back cybersecurity expert and systems thinker Laksh Raghavan. Laksh explores how multidisciplinary thinking bridges the gap between theory and practice in solving complex problems.The discussion begins with Laksh's professional journey, highlighting his early dissatisfaction with conventional consulting and his pivot toward systems thinking and complexity science. Inspired by figures like Kurt Lewin, Charlie Munger, and Russell Ackoff, Laksh outlines his approach to integrating insights from diverse disciplines to better address both technical and socio-technical challenges.A central theme of the episode is multidisciplinary thinking, which Laksh describes as synthesizing insights from various fields—physics, psychology, and economics—to build a latticework of mental models. He compares this process to what Charlie Munger advocated for in investing, but applies it internally to organizational design and problem-solving.We delve into foundational concepts like epistemic humility, the "blind men and the elephant" parable, and the challenges of communicating complex ideas to diverse audiences. Laksh critiques what he terms the "Silicon Valley syndrome," where reductive technical solutions often miss the human elements integral to sustainable success. Examples like Elon Musk's organizational strategies and the "doorman fallacy" underscore the need to see systems as adaptive and human-centered.Laksh also highlights the importance of psychological insights in addressing organizational and cybersecurity challenges. He emphasizes education reform and the joy of learning as critical to fostering creativity and resilience in individuals and teams.The conversation concludes with reflections on W. Edwards Deming's principles and their relevance to modern organizations, particularly in viewing systems holistically and embracing uncertainty. Laksh's current work with Cyb3rSyn  embodies this vision, aiming to create environments where multidisciplinary learning thrives.You can learn more  about the Cyb3rSyn community and join through the following links below:https://www.cyb3rsyn.com/https://www.cyb3rsyn.com/p/announcing-cyb3rsyn-labs

In this second part of my conversation with Dr. Bill Bellows, we continue our deep dive into the profound concepts of W. Edwards Deming and their modern applications in leadership, systems thinking, and operational excellence. Dr. Bellows brings his wealth of experience and insight to tackle complex questions about embedding systems thinking within large organizations, balancing tools and strategies, and fostering meaningful collaboration.We begin by examining the challenges of introducing Deming's principles in diverse organizational settings. Dr. Bellows shares his approach of starting small—providing a foundational vocabulary to diverse teams before scaling deeper understanding. He underscores the importance of translating concepts into actionable strategies that resonate within the unique contexts of organizations, using inspiring examples from industries like aerospace.A significant theme in this episode is the interplay between analysis and synthesis in problem-solving. Dr. Bellows advocates for a shift from merely addressing isolated failures to improving system functions holistically—a perspective championed by Deming and Taguchi. We explore examples like defining the function of a weld or a sweater to demonstrate how function-focused improvement prevents trading one failure mode for another.Dr. Bellows also reflects on the diminishing emphasis on human capital investment, such as the decline of leadership development facilities, and connects this to the broader need for fostering systems-level thinking in organizations. Together, we discuss how organizations can avoid reducing education to mere compliance training and instead inspire innovative thinking across all levels.We conclude by revisiting key takeaways, including the critical role of operational definitions in achieving clarity, the importance of defining and measuring function, and the imperative to develop methods that inspire system-wide transformation.

In this episode, I engage with Dr. Bill Bellows in a deep dive into the application of W. Edwards Deming’s systems thinking in software development and DevOps. Dr. Bellows, a veteran in quality management and an expert in Deming’s principles, shares insights on variation, Taguchi loss functions, and the synthesis of parts in a system to highlight gaps in current industry metrics like DORA.Key Topics:Misconceptions About Managing Parts vs. Systems:Dr. Bellows references Russell Ackoff’s assertion that managing individual parts optimally doesn’t guarantee an effective system. He relates this to the tendency in software and manufacturing to assess components in isolation rather than as part of a larger system.The Role of Variation in Quality:Building on Shewhart’s work, Dr. Bellows explains how statistical process control examines stability and variation within components. Taguchi’s insights are introduced to show how variation in individual parts impacts the whole system's functionality.Applying Taguchi to Modern Metrics:The conversation examines how DORA metrics, such as deployment frequency and mean time to recovery, serve as output measures but fail to address the underlying inputs driving these metrics. Dr. Bellows highlights the importance of understanding "failure" through operational definitions and its nuanced variations.Systems Thinking in Feedback Loops:Emphasizing tighter feedback loops, Dr. Bellows ties traditional Deming concepts to the promise of continuous improvement in DevOps. He advocates for a systemic view, where the interplay of individual variances contributes to collective outcomes.Key Insights:Systems must be analyzed holistically to manage complexity and leverage opportunities effectively.Outputs like DORA metrics should inform adjustments to input characteristics rather than serve as the sole focus.Precision in defining failure and understanding its economic implications is critical to refining processes and delivering value.

In this short episode, I reconnect with Dr. Bill Bellows, a frequent guest and advocate for W. Edwards Deming's principles. The conversation focuses on reviving the In2:In Thinking Network, a nonprofit Dr. Bellows co-founded to improve how individuals and organizations work, learn, and think together. Dr. Bellows discusses the origins of the network and its 16-year legacy of bringing together diverse voices inspired by Deming, Russell Ackoff, and others to explore innovative ways of collaboration.We also reveal exciting plans for a 2025 In2:In Thinking Network Conference in Santa Clarita, California. This event aims to merge communities from software development, systems thinking, and various industries to foster cross-pollination of ideas. The goal? An "oasis of sanity in a sea of madness," where passionate learners share experiences and challenge conventional approaches to problem-solving.If you want to learn more or get on the mailing list, reach out to either of us.

In this second installment of my conversation with Dr. David Woods, we continue our exploration of resilience engineering and complexity science, focusing on practical applications and actionable strategies. Building on the foundational concepts from part one, Dr. Woods offers deeper insights into how organizations can thrive in unpredictable environments by embracing resilience as a core competency.We dive into the nuts and bolts of designing systems that can adapt and recover, emphasizing the importance of fostering collaboration, continuous learning, and feedback loops. Dr. Woods connects these practices to W. Edwards Deming’s teachings, particularly the interplay between profound knowledge and operational flexibility. Our conversation also underscores the significance of learning from near misses and small failures, treating them as opportunities to strengthen systems rather than vulnerabilities to hide.Key highlights include:The Adaptive Cycle: Dr. Woods introduces a powerful framework for understanding how systems evolve and adapt over time, offering lessons for IT, healthcare, and manufacturing.Learning from Disruption: Examples of organizations that turned crises into growth opportunities by leveraging resilience principles.Operationalizing Resilience: How leaders can embed resilience thinking into daily operations through deliberate design and cultural shifts, echoing Deming’s focus on systems thinking and constancy of purpose.This episode serves as a practical guide for anyone seeking to bridge theoretical concepts with real-world applications. Dr. Woods leaves us with actionable takeaways on how to lead and thrive in an era of constant change, making this a must-listen for leaders and practitioners alike.

In this discussion, Dr. David Woods, a leading authority on resilience engineering and complexity science, shares his insights on resilience in a rapidly changing world. He emphasizes the importance of adaptive leadership in organizations, particularly in IT and healthcare. Dr. Woods provides real-world examples of successful resilience strategies and warns against oversimplifying complex systems. He connects these ideas to W. Edwards Deming’s principles, stressing that fostering a culture of learning and experimentation can drive innovation and improve organizational adaptability.

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: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.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.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.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.