(04:11) Brought to you by Jellyfish
AI tools alone won’t transform your engineering org. Jellyfish provides insights into AI tool adoption, cost, and delivery impact – so you can make better investment decisions and build teams that use AI effectively. See for yourself at jellyfish.co/platform/ai-impact.
Are you managing your team the same way you did five years ago? With AI agents now part of the workforce, the old playbook no longer applies.
In this episode, Jurgen Appelo, author of “Human Robot Agent” and creator of Management 3.0 and unFIX, challenges conventional thinking about management, organizational design, and the future of work in the AI era. He explains why rigid frameworks like Scrum are becoming bottlenecks to AI speed and why he believes we need to completely rethink how organizations operate.
The conversation dives into the concept of creating “fast tracks” for AI agents while maintaining “slow tracks” for human collaboration. Jurgen also breaks down why team sizes are shrinking and why professionals must move beyond T-shaped skills to become M-shaped, multidisciplinary workers to remain relevant. He also shares his controversial take on why Scrum is “done” and why he trusts AI more than the average human when solving complex problems.
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Jurgen Appelo’s Bio
Jurgen Appelo is an author, speaker, and entrepreneur who helps leaders rewire their organizations for AI-driven leadership and autonomous digital agents. Recognized by Inc.com as a Top 50 Leadership Expert and Top 100 Leadership Speaker, he bridges opposing worldviews: human ingenuity and AI, leadership versus governance, stability with innovation, and individual growth fueling collective success. As founder of The unFIX Company (and previously founder of Management 3.0 and co-founder of Agile Lean Europe), Jurgen pioneers the future of work through stories, games, tools, and practices that challenge conventional thinking.
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(04:00) Brought to you by Unleash
Unleash is a private, flexible, and scalable feature flag system that lets teams decouple deployments from releases. It reduces the risk of shipping new features and gives organizations real-time control over what reaches production. And as AI accelerates development, Unleash helps engineering teams move fast and stay stable with safe rollouts and instant kill switches. Start a free trial of Unleash at getunleash.io/pricing.
Why do so many software projects still fail despite modern tools? The answer often lies in the psychology of the team, not the technology stack.
Software development is often viewed purely as a technical challenge, yet many projects fail due to human factors and cognitive bottlenecks. In this episode, Adam Tornhill, CTO and Founder of CodeScene, shares his unique journey combining software engineering with psychology to solve these persistent industry problems. He explains the concept of “Your Code as a Crime Scene,” a method for using behavioral analysis to identify high-risk areas in a codebase that static analysis tools often miss.
Adam covers the tangible business impact of code health, specifically how it drives predictability and development speed. He explains why 1-2% of our codebase accounts for up to 70% of our development work, and how focusing on these hotspots can make our team 2x faster and 10x more predictable. Adam also provides a critical reality check on the rise of AI in coding, exploring whether it will help reduce technical debt or accelerate it, and offers strategies for maintaining quality in an AI-assisted future.
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Adam Tornhill’s Bio
Adam Tornhill is the founder and CTO of CodeScene and the best-selling author of Your Code as a Crime Scene. Combining degrees in engineering and psychology, Adam helps companies optimize software quality using AI-driven methodologies. He is an international keynote speaker and researcher who enjoys retro computing and martial arts in his spare time.
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(06:03) Brought to you by Unleash
Unleash is a private, flexible, and scalable feature flag system that lets teams decouple deployments from releases. It reduces the risk of shipping new features and gives organizations real-time control over what reaches production. And as AI accelerates development, Unleash helps engineering teams move fast and stay stable with safe rollouts and instant kill switches. Start a free trial of Unleash at getunleash.io/pricing.
Are you making critical decisions without consulting AI? Greg argues it’s now irresponsible for any leader to make high-stakes decisions without talking to AI first.
In this episode, Greg Shove, CEO of Section and a multi-time founder with 30 years of entrepreneurial experience, shares how AI is fundamentally different from any previous technology wave. Unlike traditional software that makes us more productive within our existing boundaries, AI allows us to jump capability boundaries – enabling individuals and organizations to do things they simply couldn’t do before.
Greg explains why most enterprise AI rollouts are failing (hint: they’re treating AI like software when it’s actually co-intelligence), how to cultivate resilience through multiple startup failures, and the practical strategies for getting teams to adopt AI (from simple hacks like putting a post-it note on your monitor to creating an entire AI-dedicated screen).
This conversation goes beyond the hype to explore both the superpowers and limitations of AI, the real organizational outcomes you can expect (spoiler: it’s not just about layoffs), and why moving from efficiency to creation is the key to unlocking AI’s true potential in your organization.
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Greg Shove’s Bio
Greg Shove is a seven-time CEO, all in on AI. After first using ChatGPT in February 2023, he pivoted his company Section to be AI-powered. Now he helps enterprise organizations move from AI-anxious to AI-proficient with a proven playbook, delivered through keynote speaking and executive workshops.
Greg is also the founder of Machine & Partners, an AI lab building custom enterprise AI applications, and co-author of Personal Math, a weekly newsletter sharing business insights for early-career leaders and founders.
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(06:06) Brought to you by Jellyfish
AI tools alone won’t transform your engineering org. Jellyfish provides insights into AI tool adoption, cost, and delivery impact – so you can make better investment decisions and build teams that use AI effectively. See for yourself at jellyfish.co/platform/ai-impact.
Why do organizations constantly complain about having too much technical debt? Because they’re solving the wrong problem.
In this episode, Dr. Andrew Brown, author of “Taming Your Dragon: Addressing Your Technical Debt,” reveals a profound insight: technical debt isn’t fundamentally a technical problem. It’s a trade-off problem rooted in human bias, organizational systems, and economic incentives. Through his innovative “Technical Debt Onion Model,” Andrew shows how decisions about code quality happen across five interconnected layers, from individual cognitive biases to wicked problem dynamics.
Andrew explains why the financial debt analogy is dangerously misleading and, more importantly, how others can rack up debt you’ll eventually pay for. Drawing from behavioral economics, systems thinking, and organizational theory, he reveals why our emotions, not logic, drive most technical decisions, and how to work with this reality rather than against it.
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Andrew Brown’s Bio
Andrew Richard Brown has worked in software since 1999, starting as an SAP programmer fixing Y2K bugs. He realized the biggest problems in software development were human, not technical, and has since helped teams improve performance by addressing these issues.
Andrew coaches organizations on software development and quality engineering, focusing on technical debt, risk in complex systems, and project underestimation. He investigates how cognitive biases drive software problems and applies behavioral science techniques to solve them. His research has produced counterintuitive insights and fresh approaches. He regularly speaks at international conferences and runs a growing YouTube channel on these topics.
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Why does an AI that brilliantly generates code suddenly fail at basic math? The answer explains why your LLM will fail when you least expect it.
In this episode, Emmanuel Maggiori, author of “Smart Until It’s Dumb” and “The AI Pocket Book,” cuts through the AI hype to reveal what LLMs actually do and, more importantly, what they can’t. Drawing from his experience building AI systems and witnessing multiple AI booms and busts, Emmanuel explains why machine learning works brilliantly until it makes mistakes no human would ever make.
He shares why businesses repeatedly fail at AI adoption, how hallucinations are baked into the technology, and what developers need to know about building reliable AI products.
Whether you’re implementing AI at work or concerned about your career, this conversation offers a grounded perspective on navigating the current AI wave without getting swept away by unrealistic promises.
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Emmanuel Maggiori’s Bio
Emmanuel Maggiori, PhD, is a software engineer and 10-year AI industry insider. He has developed AI for a variety of applications, from processing satellite images to packaging deals for holiday travelers. He is the author of the books Smart Until It’s Dumb, Siliconned, and The AI Pocket Book.
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Can decades-old management philosophy actually help us tackle AI’s biggest challenges?
In this episode, John Willis, a foundational figure in the DevOps movement and co-author of the DevOps Handbook, takes us through Dr. W. Edwards Deming’s System of Profound Knowledge and its surprising relevance to today’s most pressing challenges. John reveals how Deming’s four-lens framework—theory of knowledge, understanding variation, psychology, and systems thinking—provides a practical approach to managing complexity.
The conversation moves beyond theoretical management principles into real-world applications, including incident management mistakes that have killed people, the polymorphic nature of AI agents, and why most organizations are getting AI adoption dangerously wrong.
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John Willis’ Bio
John Willis is a prolific author and a foundational figure in the DevOps movement, co-authoring the seminal The DevOps Handbook. With over 45 years of experience in IT, his work has been central to shaping modern IT operations and strategy. He is also the author of Deming’s Journey to Profound Knowledge and Rebels of Reason, which explores the history leading to modern AI.
John is a passionate mentor, a self-described “maniacal learner”, and a deep researcher into systems thinking, management theory, and the philosophical implications of new technologies like AI and quantum computing. He actively shares his insights through his “Dear CIO” newsletter (aicio.ai) and newsletters on LinkedIn covering Deming, AI, and Quantum.
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In this episode, Honey Mittal, CEO and co-founder of Locofy.ai, explores one of the most exciting transformations in software development: the convergence of design and engineering through AI-powered automation.
Honey shares the fascinating journey of building Locofy, a tool that converts Figma designs into production-ready front-end code. But this isn’t just another AI hype story. It’s a deep dive into why Large Language Models (LLMs) fundamentally can’t solve design-to-code problems, and why his team spent four years building specialized “Large Design Models” from scratch.
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Whether you’re a front-end engineer tired of translating design pixel-by-pixel, a designer curious about coding, or a technical leader evaluating AI development tools, this episode offers practical insights into the future of software development.
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Honey Mittal’s Bio
Honey Mittal is the CEO and co-founder of Locofy.ai, a platform that automates front-end development by converting designs into production-ready code. Originally an engineer who built some of the first mobile apps in Singapore, Honey transitioned into product leadership after realizing his natural strength lay in identifying high-impact problems. He set a goal to become a CPO by 30 and achieved it, leading product transformations at major Southeast Asian scale-ups like Wego, FinAccel, and Homage.
Driven by a decade of experience and the “grunt work” he and his co-founder faced, he started Locofy to solve the costly friction between design and engineering. Honey is passionate about the future of AI in development, the rise of the “Design Engineer”, and proving that globally competitive, deep-tech companies can be built from Southeast Asia.
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Can you navigate AI disruption without understanding your landscape? Discover how to gain true situational awareness.
The rise of AI has exposed a fundamental problem in how organizations make decisions. Most leaders operate using stories and graphs, not actual maps of their landscape. This leaves them vulnerable to disruption and unable to make informed choices about where to apply new technologies. The result is chaos, waste, and strategic mistakes that could have been avoided.
In this episode, Simon Wardley, creator of Wardley Mapping, explains how to build true situational awareness in your organization. He shares why most business “maps” aren’t really maps at all, how to understand the landscape before making decisions, and what leaders need to know about AI adoption beyond the current hype.
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Simon Wardley’s Bio
Simon Wardley is a researcher, former CEO, and the creator of Wardley Mapping, a powerful method for visualizing and developing business strategy. His journey began accidentally after a bookseller recommended Sun Tzu’s The Art of War, which sparked a fascination with understanding the competitive “landscape.”
As the former CEO of an online photo service acquired by Canon, he felt like a “fake CEO,” leading with stories while lacking true situational awareness. This led him to discover that almost all business “maps” were merely graphs, prompting him to develop his own mapping technique. Today, his work is used by organizations like NASA and taught at multiple MBA programs, helping leaders to “look before they leap” and navigate complex technological and market shifts, including the current disruption caused by AI.
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How much of your code exists only to prevent failures? Discover a new paradigm for building reliable applications.
In this episode, Preeti Somal, SVP at Temporal, explores a paradigm shift that can dramatically boost productivity and give developers peace of mind. Drawing on her experience leading massive infrastructure at Yahoo and HashiCorp, she explains Temporal’s concept of durable execution that helps developers focus on business logic and remove reliability concerns. Preeti also discusses key findings from Temporal’s first State of Development Report.
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Preeti Somal’s Bio
Preeti is Senior Vice President of Engineering at Temporal. Preeti is passionate about building great products, growing world class organizations and solving complex problems. Prior to Temporal, Preeti led the Platform, Security and IT engineering organizations at HashiCorp. Her extensive career includes engineering leadership roles at Yahoo!, VMware and Oracle. While at Yahoo! Preeti was VP of Cloud Services in the Platform organization delivering highly scalable services used by engineers across Yahoo to build and operate applications with improved agility, reliability and security. These services power Yahoo!’s consumer and advertising business.
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“Engineering leaders are stuck between the expectations put out by sensational headlines and the reality of what they’re seeing in their organization. There’s a big disappointment gap.”
Is your AI investment paying off? Many leaders struggle to see real ROI beyond the hype.
In this episode, Laura Tacho, CTO of DX, shares DX’s new research on measuring AI adoption success across 38,000+ engineers. Our conversation reveals why acceptance rates are misleading metrics and introduces DX’s new AI Measurement Framework™ with its three critical dimensions: utilization, impact, and cost. Learn why treating AI as an organizational problem closes the “disappointment gap” between hype and reality.
Note: This episode was recorded in July 2025. The AI adoption rate mentioned has since risen to nearly 80%.
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Laura Tacho’s Bio
Laura Tacho is CTO at DX, a developer intelligence platform, co-author of the Core 4 developer productivity metrics framework, and an executive coach. She’s an experienced technology leader and engineering leadership coach with a strong background in developer tools and distributed systems.
Her career includes leadership roles at organizations such as CloudBees, Aula Education, and Nova Credit, where she specialized in building high-performing engineering teams and delivering impactful products. Laura has worked with thousands of engineering leaders as they work to improve their engineering practices with data.
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“Architecture is something that has to emerge naturally from the code. If it doesn’t make the code better, more elegant, and more flexible, then you should not be doing it.”
Why do so many developers have a love-hate relationship with ORM? The creator of Hibernate reveals the real reasons behind the controversy and what’s being done to fix the fundamental issues.
In this episode, Gavin King, the creator of Hibernate, shares the story behind its creation, from a debate with his boss to its rise as a popular open-source. He dives deep into why developers often dislike ORM, pinpointing the “magic” of the stateful persistence context as a major pain point.
Gavin explains how modern specifications are fixing these historical issues with an emphasis on type safety and more explicit, stateless operations, giving developers greater control.
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Gavin King’s Bio
Gavin King is the creator of Hibernate, the revolutionary framework that redefined data persistence for millions of Java developers. A key figure in the evolution of enterprise Java, he has led the development of major industry standards like the Java Persistence API (JPA) and CDI. After a decade designing the Ceylon programming language, he has returned to his roots to advance the next generation of data persistence with Jakarta EE.
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Are long code review cycles killing your engineering team’s velocity? Learn how top engineering teams are shipping code faster without sacrificing quality.
In this episode, Greg Foster, CTO and co-founder of Graphite, discusses the evolution of code review practices, from the fundamentals of pull requests to the future of AI in code review workflows. He shares the secrets behind how the Graphite team became one of the most productive engineering teams by leveraging techniques like small code changes and stacked PRs (pull requests).
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Greg Foster’s Bio
Greg Foster is the CTO and co-founder of Graphite, an a16z and Anthropic-backed company helping teams like Snowflake, Figma, and Perplexity ship faster and scale AI-generated code with confidence. Prior to Graphite, Greg was a dev tools engineer at Airbnb. There, he experienced the impact of robust internal tooling on developer velocity and co-founded Graphite to bring powerful, AI-powered code review to every team. Greg holds a BS in Computer Science from Harvard University.
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Struggling with technical debt and code quality? Learn how a technical coach can help your team level up.
In this episode, Emily Bache, a Samman technical coach, shares her proven method for building better engineering teams through structured learning and collaborative coding. We explore ensemble programming, learning hours, and why AI makes fundamental engineering practices more important than ever.
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Emily Bache’s Bio
Emily Bache is an independent consultant, YouTuber and Technical Coach. She works with developers, training and coaching effective agile practices like Refactoring and Test-Driven Development.
Emily has worked with software development for 25 years, written two books and teaches courses on platforms including Pluralsight and O’Reilly. A frequent conference speaker, Emily has been invited to keynote at prestigious developer events including EuroPython, Craft and ACCU. Emily founded the Samman Technical Coaching Society in order to promote technical excellence and support coaches everywhere.
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Why do engineering teams slow down as they scale? It’s not the technology—it’s the management systems.
In this episode, Michi Kono, CTO at Garner Health and former engineering leader at Meta, Capital One, and Stripe, shares his battle-tested approach to building scalable engineering organizations. We explore why most teams slow down as they scale and how to build systems that accelerate growth. Our conversation covers everything from designing effective org charts to creating accountability without killing psychological safety. You’ll learn practical strategies for nurturing engineering culture while maintaining high-performance standards.
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Michi Kono’s Bio
Michi Kono is the Chief Technology Officer (CTO) at Garner Health, a company on a mission to help people get better healthcare. With a unique and extensive career spanning multiple industries, Michi has navigated the entire spectrum of the tech world. He began his journey in startups, one of which was acquired, leading him to a role at Capital One. From there, he gained invaluable experience at tech giants like Meta and financial-tech leader Stripe before taking the helm at Garner Health. Michi is passionate about the art and science of scaling engineering teams, building resilient cultures, and designing effective management systems to drive success in high-growth environments. He believes deeply in empowering engineers, fostering accountability, and the critical importance of clear communication for any leader.
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How do you build a high-performing engineering team in the AI era? And will AI make fundamental engineering skills obsolete?
In this episode, Mohan Krishnan, Head of Engineering at Grab, shares lessons from leading multiple transformational engineering teams. Drawing from his experience at Grab, Bukalapak, BBM Emtek, and Pivotal Labs, Mohan explains why core engineering fundamentals still matter, even in the age of AI, and will become even more valuable than ever. He discusses building disciplined, high-performing engineering teams and the importance of hands-on leadership. We also explore the unique challenges and vast potential of the tech landscape in Southeast Asia.
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Mohan Krishnan’s Bio
Mohan Krishnan, based in Singapore, is currently a Head of Engineering at Grab. Mohan Krishnan brings experience from previous roles at Google, Bukalapak, BBM and Pt. Kreatif Media Karya. Mohan Krishnan holds a 1998 - 2002 Bachelor of Engineering in Multimedia, Electronics at Multimedia University. With a robust skill set that includes Ruby on Rails, Multithreading, Web Services, HTML, Services and more.
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How has Infrastructure as Code changed in the last five years? Explore the key shifts and how to align your infrastructure to real business value.
In this episode, Kief Morris, a Distinguished Infrastructure Engineer at Thoughtworks, returns to discuss the third edition of his book “Infrastructure as Code.” He shares fresh insights on designing and delivering dynamic systems for today’s cloud-driven world. Kief explores the evolution of IaC, practical methods for modern teams, the next generation of tools, and lessons learned from the recent years. Learn how to align infrastructure with business needs and manage today’s growing infrastructure complexities.
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Kief Morris’s Bio
Kief Morris is the author of the O’Reilly book Infrastructure as Code, and is a Distinguished Infrastructure Engineer at Thoughtworks, based in London. He works with clients and project teams around the world to explore, shape, and share better ways of working with cloud and infrastructure architecture.
Kief started out as a developer and systems administrator in the dot-com boom days, then worked with a series of digital scaleups applying infrastructure automation before DevOps was a thing. He joined Thoughtworks in 2010 as the wider industry was discovering Infrastructure as Code, DevOps, and Cloud, which gave him the opportunity to bring what he had learned in the previous fifteen years to enterprise clients in many industries and many countries.
He wrote the book Infrastructure as Code (now on the third edition) to share these ideas with a wider audience, which has given him a platform to meet and learn from an ever-growing variety of people and organizations.
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Ever wondered how AI is being applied in the world of clinical trials where human lives are at stake?
In this episode, Patrick Leung, CTO of Faro Health and former Google Duplex Engineering Lead, reveals how AI is transforming the clinical trial process — a process that can cost up to $2 billion per drug and take over 10 years to complete. Patrick reveals how Faro Health’s AI systems generate complex clinical documentation in minutes instead of months in which hallucinations aren’t acceptable, while navigating the strict regulatory requirements of the healthcare industry.
Patrick also reflects on the evolution of AI technologies, the realities of large language models, and offers practical advice on how to thrive in the rapidly changing AI-driven era.
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Patrick Leung’s Bio
Patrick Leung is a Chief Technology Officer at Faro Health, a company at the forefront of optimizing clinical trial development through the use of artificial intelligence.
In his role, he is instrumental in applying large language models and other AI technologies to enhance protocol design and outcomes for clinical trials. A native of New Zealand, Mr. Leung holds degrees in Computer Science and Finance.
His career includes being a foundational member of an early e-commerce software company, where he played a key role in guiding the company from its initial stages to a successful initial public offering.
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Is your engineering team running like the wild, wild west? What does engineering excellence look like in practice?
In this episode, Ganesh Datta, co-founder and CTO of Cortex, explores what it takes to achieve engineering excellence. Ganesh shares lessons from his own journey, from early bug-fixing to building a company focused on engineering excellence.
We discuss how platform engineering and internal developer platforms (IDPs) can help teams scale, improve reliability, and align with business outcomes. Ganesh also explains why culture, leadership, and clear metrics matter more than any single tool.
If you’re looking to make your engineering team a true business driver, this conversation is for you.
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Ganesh Datta’s Bio
Ganesh Datta is a Co-Founder & CTO of Cortex. Before co-founding Cortex, he was a Principal Software Engineer at Mission Lane where he was responsible for driving the development of real-time underwriting infrastructure. At LendUp, Ganesh was a Senior Software Engineer leading the development and optimization of the company’s decisioning infrastructure and financial account management system. Ganesh holds a bachelor of science in computer science from the University of California San Diego.
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Is your software development process stuck on a conveyor belt? Discover how to break free from outdated manufacturing mindsets and build truly high-performing, agile teams that “Move Fast and Break Silos.”
In this episode, experienced CPTO, Klaus Breyer, introduces a revolutionary approach to software development. He explains why treating software engineering like a factory assembly line leads to inefficiency, micromanagement, and disempowered teams. Learn how to slice work effectively—from objectives down to delivery—and align small, empowered teams to solve real customer problems and ship value faster.
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Klaus Breyer’s Bio
Klaus Breyer is an experienced B2B SaaS CPTO who specializes in bridging the gap between technical delivery and agile product strategy, driven by a passion for breaking down silos. His career includes founding and leading the startups Buddybrand (a digital agency) and BuzzBird (a B2B marketplace), as well as building corporate startups and business units for major companies like Voith and edding in the IoT and B2B SaaS sectors.
Based in Berlin, he has extensive experience working with diverse and primarily remote teams. In addition to his leadership roles, he sometimes invests in and advises leadership teams on building effective interdisciplinary teams themselves. He is also a speaker, blogger, and book author who champions the philosophy of “Move Fast And Break Silos!”
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Is AI taking over the craft of coding? Many engineers now face an identity crisis.
In the episode, Distinguished Engineer Annie Vella discusses her research on AI’s impact on software development. She explores the “software engineering identity crisis” as the craft of coding becomes automated. Annie warns that the seductive speed of AI tools can lead to lower quality and delivery stability, a trend supported by reports from DORA and GitClear. She also cautions that over-reliance on AI prevents engineers from gaining the hands-on experience needed for deep skill acquisition.
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Annie Vella’s Bio
Annie Vella is a Distinguished Engineer at Westpac NZ with two decades of experience in software engineering and technical leadership across various industries and countries.
Vella has returned to an engineering role after a period in management and is also a part-time Master’s student at the University of Auckland, researching the impact of AI on software engineering. She believes that technologies like Generative AI, LLMs, and Agentic AI will revolutionize the field and problem-solving in general.
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