LLMs and Generative AI in the enterprise.
Inspire, develop, and guide a winning organization.
Understand the unique values and behaviors of a successful organization.
Create visible workflows to achieve well-architected software.
Understand and use meaningful data to measure success.
Integrate and automate quality, security, and compliance into daily work.
An on-demand learning experience from the people who brought you The Phoenix Project, Team Topologies, Accelerate, and more.
Learn how to enhance collaboration and performance in large-scale organizations through Flow Engineering
Learn how making work visible, value stream management, and flow metrics can affect change in your organization.
Clarify team interactions for fast flow using simple sense-making approaches and tools.
Multiple award-winning CTO, researcher, and bestselling author Gene Kim hosts enterprise technology and business leaders.
In the first part of this two-part episode of The Idealcast, Gene Kim speaks with Dr. Ron Westrum, Emeritus Professor of Sociology at Eastern Michigan University.
In the first episode of Season 2 of The Idealcast, Gene Kim speaks with Admiral John Richardson, who served as Chief of Naval Operations for four years.
Exploring the impact of GenAI in our organizations & creating business impact through technology leadership.
DevOps best practices, case studies, organizational change, ways of working, and the latest thinking affecting business and technology leadership.
The debate over in-office versus remote work misses a fundamental truth: high-performing teams succeed based on how they’re organized, not where they sit.
Leaders can help their organizations move from the danger zone to the winning zone by changing how they wire their organization’s social circuitry.
The values and philosophies that frame the processes, procedures, and practices of DevOps.
This post presents the four key metrics to measure software delivery performance.
Revolutionizing Modern Ways of Working
This groundbreaking paper explores how AI and large language models (LLMs) can enhance Industrial DevOps practices, specifically in the context of cyber-physical systems like manufacturing plants, autonomous vehicles, energy systems, and complex industrial infrastructure. The authors present a comprehensive framework for integrating AI capabilities into daily operations, showing how teams building and maintaining these critical systems can leverage AI as a collaborative partner rather than just a tool.
The paper addresses the unique challenges of applying AI in industrial settings where reliability, safety, and regulatory compliance are paramount. It demonstrates how AI can assist in areas like predictive maintenance, quality control, supply chain optimization, and real-time monitoring of industrial processes while maintaining essential human oversight. The authors provide concrete examples of how industrial teams can use AI to enhance their development and operational practices without compromising the rigorous standards required in industrial environments.
Drawing from extensive research and real-world industrial applications, the paper provides practical guidance for leaders seeking to enhance the value of their cyber-physical systems through emerging technologies. It includes detailed examples of AI implementation across various industrial sectors, alongside patterns and practices for successful adoption that address the specific needs and constraints of industrial systems development and operations.
Clear guidance for applying AI within safety-critical and regulated industrial environments.
Practical approach for making AI a collaborative team member in industrial settings.
Strategies for maintaining safety and reliability while leveraging AI capabilities.
Real-world examples from manufacturing, energy, automotive, and other industrial sectors.
Debbie Brey is the director of complex systems innovation practice at Project & Team. In this role, she provides consulting and coaching for companies and organizations looking to innovate when dealing with the complexity of their solution and organizations. Debbie retired from Boeing as a technical fellow. She introduced and advanced Boeing’s ways of working using a combination of Agile, Lean, and the Scaled Agile Framework (SAFe). Brey founded the Boeing Enterprise Agile Center of Excellence, where she focused on growing an internal Agile coaching capability and increasing the overall outcomes of business agility at Boeing. She achieved recognition for her continued pursuit of improving outcomes by simplifying and clarifying guidance around Lean and Agile ways of working for anyonemat Boeing, specifically how they could be embraced for cyber-physical systems. Brey is a SAFe Program Consultant Trainer (SPCT) and SAFe Fellow.
Jennifer is a semi-retired empathetic Lean and Agile leader, practitioner, coach, speaker, and consultant. A SAFe Fellow, she contributed to and helped develop SAFe content and courseware. Her passion has been in delivering value in the workplace and by understanding the science of social communities, communication, and culture. Other areas of focus included product management, product ownership, and compassionate leadership. She has provided dedicated service in these areas to enterprises for over forty years.
Dr. Suzette Johnson is an award-winning author who has spent most of her career in the aerospace defense industry working for Northrop Grumman Corporation. Suzette was the enterprise Lean/Agile transformation lead. In this role, she launched the Northrop Grumman Agile Community of Practice and the Lean/Agile Center of Excellence. She has supported over a hundred enterprise, government, and DoD transitions to and the maturation of Lean-Agile principles and engineering development practices. She has also trained and coached over four thousand individuals on Lean/Agile principles and practices and delivered more than one hundred presentations on Lean/Agile at conferences both nationally and abroad. Her current role is as Northrop Grumman Fellow and Technical Fellow Emeritus, where she continues to actively drive the adoption of Lean/Agile principles with leadership at the portfolio levels and within cyber-physical solutions, specifically within the space sector. As a mentor, coach, and leader, she launched the Women in Computing, Johns Hopkins University Chapter; the Women in Leadership Development program; the Northrop Grumman Lean-Agile Center of Excellence; and the NDIA ADAPT (Agile Delivery for Agencies, Programs, and Teams) working group. She received a Doctorate of Management at the University of Maryland with a dissertation focused on investigating the impact of leadership styles on software project outcomes in traditional and Agile engineering environments. She am also a Certified Agile Enterprise Coach and Scaled Agile Program Consultant/SPCT
Robin Yeman is an award-winning author who has spent twenty-six years working at Lockheed Martin in various roles leading up to senior technical fellow building large systems including everything from submarines to satellites. She led the Agile community of practice supporting a workforce of 120,000 people. Her initial experience with Lean practices began in the late ’90s. In 2002, she had the opportunity to lead my first Agile program with multiple Scrum teams. After just a couple months of experience, she was hooked and never turned back. She both led and supported Agile transformations for intelligence, federal, and Department of Defense organizations over the next two decades, and each one was more exciting and challenging than the last. In 2012, She had the opportunity to extend our Agile practices into DevOps, which added extensive automation and tightened our feedback loops, providing even larger results. Currently, she is the Carnegie Mellon Space Domain Lead at the Software Engineering Institute at Carnegie Mellon. She is also currently pursuing a PhD in Systems Engineering at Colorado State University, where she is working on my contribution to demonstrate empirical data of the benefits of implementing Agile and DevOps for safety-critical cyber-physical systems.
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