Scrum Master Toolbox Podcast: Agile storytelling from the trenches

Every week day, Certified Scrum Master, Agile Coach and Business Consultant Vasco Duarte interviews Scrum Masters and Agile Coaches from all over the world to get you actionable advice, new tips and tricks, improve your craft as a Scrum Master with daily doses of inspiring conversations with Scrum Masters from the all over the world. Stay tuned for BONUS episodes when we interview Agile gurus and other thought leaders in the business space to bring you the Agile Business perspective you need to succeed as a Scrum Master. Some of the topics we discuss include: Agile Business, Agile Strategy, Retrospectives, Team motivation, Sprint Planning, Daily Scrum, Sprint Review, Backlog Refinement, Scaling Scrum, Lean Startup, Test Driven Development (TDD), Behavior Driven Development (BDD), Paper Prototyping, QA in Scrum, the role of agile managers, servant leadership, agile coaching, and more!

Coaching Product Owners to Be the Voice of the Customer | Steve Martin 01/02/2026

Coaching Product Owners to Be the Voice of the Customer | Steve Martin Steve Martin: Coaching Product Owners to Be the Voice of the Customer In this episode, we refer to video and . The Great Product Owner: Rob Gard's Customer Obsession Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "The role of the PO really is to help the team empathize with the user, the customer of the product, because that's how they can develop great solutions." - Steve Martin Rob Gard worked at a fintech firm and is now CPO of a major fintech company. Steve describes him as having a brilliant mind and being a real agileist—someone Steve learned a huge amount about Agile from. Rob's defining characteristic was his absolute obsession with the user. Everything focused on customer pain points. Working with engineering teams serving military customers, Rob held regular workshops with those customers to understand their pain firsthand. He was literally the voice of the customer, not theoretically but practically. Rob pushed and challenged teams to be more innovative, always looking for better ways of providing better software. His gift was communication—specifically, briefing the team on the problem rather than just reading out stories in refinement sessions. This is the anti-pattern many Product Owners fall into: going through the motions, reading requirements without context. Real product ownership, as Rob demonstrated, is telling a story that helps the team empathize and understand the pain. When teams can internalize customer problems, they develop better solutions. Rob's ability to communicate the problem into the minds of teams enabled them to serve customers more effectively. This is the essence of great Product Ownership: not being a proxy for management, not juggling multiple teams, but being deeply connected to customer pain and translating that pain into context the team can work with. Self-reflection Question: Do your refinement sessions tell stories that help the team empathize with customer pain, or do you just read out requirements? The Bad Product Owner: Proxies for Management Instead of Customer Advocates Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "They weren't a team, they were a group of individuals working on multiple different projects." - Vasco Duarte Steve emphasizes that Product Owners often have great intentions but struggle due to lack of training and coaching. The anti-patterns are systemic: commercial managers "dressed up" as Product Owners without understanding the role. Project managers transitioning to PO roles—though Steve notes PMs can make really good POs with proper support. The most damaging pattern is Product Owners spread across multiple teams, having very little time to focus on any single team or their customers. These POs become proxies—representing the voice of senior management rather than the voice of the customer. They cascade requirements downward instead of bringing customer insights upward. The solution isn't to criticize these struggling Product Owners but to help them understand their role and see what good looks like. Steve recommends video—15 minutes, 15 years old, still profoundly relevant. He also points to and formal training like CSPO or IC Agile Product Ownership courses. The fundamental issue is meeting Product Owners where they are, providing coaching and support to transform them from management proxies into customer advocates. When POs understand their role as empathy builders between customers and teams, everything changes. Self-reflection Question: Is your Product Owner the voice of senior management or the voice of the customer? [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Steve Martin You can link with . Steve is an Agile Coach, mentor, and founder of The Agile Master Academy. After over 14 years leading Agile transformation programmes, he's on a mission to elevate Scrum Masters—building high-performing teams, measurable impact, and influence—and raising industry standards of Agile mastery through practical, evidence-led coaching. You can also find Steve's insights on his . /episode/index/show/scrummastertoolbox/id/39440915

Making Scrum Master Success Visible with OKRs That Actually Work | Steve Martin 01/01/2026

Making Scrum Master Success Visible with OKRs That Actually Work | Steve Martin Steve Martin: Making Scrum Master Success Visible with OKRs That Actually Work Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "It is not the retrospective that is the success of the retrospective. It is the ownership and accountability where you take improvements after the session." - Steve Martin The biggest problem for Scrum Masters isn't just defining success—it's being able to shout it from the rooftops with tangible evidence. Steve champions OKRs as an amazing way to define and measure success, but with a critical caveat: they've historically been poorly written and implemented in dark rooms by executives, then cascaded down to teams who never bought in. Steve's approach is radically different. Create OKRs collectively with the team, stakeholders, and end users. Start by focusing on the pain—what problems or pain points do customers, users, and stakeholders actually experience? Make the objective the goal to solve that problem, then define how to measure progress with key results. When everyone is bought in—Scrum Master, engineers, Product Owner, stakeholders, leaders—all pulling in the same direction, magic happens. Make progress visible on the wall like a speedometer, showing exactly where you are at any moment. For an e-commerce checkout, the problem might be too many steps. The objective: reduce pain for users checking out quickly. The baseline: 15 steps today. The target: 5 clicks in three months. Everyone can see the dial moving. Everything should focus on the customer as the endpoint. The challenge is distinguishing between targets imposed from above ("increase sales by 10%") and objectives created collaboratively based on factors the team can actually control. Find what you can control first, work with customers to understand their pain, and start from there. Self-reflection Question: Can you articulate your team's success with specific, measurable outcomes that everyone—from developers to executives—understands and owns? Featured Retrospective Format for the Week: Post-Retro Actions and Ownership The success of a retrospective isn't the retrospective itself—it's what happens after. Steve emphasizes that ownership and accountability matter more than the format of the session. Take improvements from the retrospective and bring them into the sprint as user stories with clear structure: this is the problem, how we'll solve it, and how we'll measure impact. Assign collective ownership—not just a single person, but the whole team owns the improvement. Then bring improvements into the demo so the team showcases what changed. This creates cultural transformation: the team themselves want to bring improvements, not just because the Scrum Master pushed them. For ongoing impediments, conduct root cause analysis. Create a system to escalate issues beyond the team's control—make these visible on another board or with the leadership team. Find peers in pain: teams with the same problems can work together collectively. The retrospective format matters less than this system of ownership, action, measurement, and visibility. Stop retrospective theatre—going through the motions without taking action. Make improvements real by treating them like any other work: visible, measured, owned, and demonstrated. [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Steve Martin You can link with . Steve is an Agile Coach, mentor, and founder of The Agile Master Academy. After over 14 years leading Agile transformation programmes, he's on a mission to elevate Scrum Masters—building high-performing teams, measurable impact, and influence—and raising industry standards of Agile mastery through practical, evidence-led coaching. You can also find Steve's insights on his . /episode/index/show/scrummastertoolbox/id/39441100

Why Agile Fatigue Means We Need to Change Our Approach | Steve Martin 12/31/2025

Why Agile Fatigue Means We Need to Change Our Approach | Steve Martin Steve Martin: Why Agile Fatigue Means We Need to Change Our Approach Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "We teach transformation, we support transformation, we help change, but we don't really understand what they're changing from." - Steve Martin Steve believes Agile as a whole is on the back foot, possibly regressing. There's palpable fatigue in the industry, and transformation in its current form hasn't been the success we hoped. Organizations still need to work in a state of agility—making rapid decisions, aligning teams, delivering value at pace—but they're exhausted by how we've implemented Agile. As Agile professionals, Steve argues, we have a responsibility to take stock and reflect on what's not working. The problem isn't that organizations don't need agility; it's that we've been force-feeding them frameworks without understanding their context. Steve invokes an ancient principle: "When the student is ready, the teacher will appear." But we haven't waited for readiness—we've barged in with Big Bang transformations, bringing 10, 15, or 20 Agile coaches to "save the world." The solution requires meeting people where they are, understanding what they're changing from, not just what they're changing to. Steve's coaching conversation centers on a radical idea: stop trying to help teams that don't want to be helped. Focus on teams already interested in incremental, adaptable delivery. Run small pilots, learn what works, then scale when ready. The age of prescriptive transformation is over. We need to adapt to the reality of the moment, experiment with what works, and have the courage to change the plan when our approach isn't working. Self-reflection Question: Are you forcing Agile on teams that aren't ready, or are you working with those who genuinely want to improve their delivery approach? [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Steve Martin You can link with . Steve is an Agile Coach, mentor, and founder of The Agile Master Academy. After over 14 years leading Agile transformation programmes, he's on a mission to elevate Scrum Masters—building high-performing teams, measurable impact, and influence—and raising industry standards of Agile mastery through practical, evidence-led coaching. You can also find Steve's insights on his . /episode/index/show/scrummastertoolbox/id/39441310

When a Distributed Team's Energy Vanishes into the Virtual Void | Steve Martin 12/30/2025

When a Distributed Team's Energy Vanishes into the Virtual Void | Steve Martin Steve Martin: When a Distributed Team's Energy Vanishes into the Virtual Void Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "They weren't a team, they were a group of individuals working on multiple different projects." - Vasco Duarte (describing Steve's team situation) The infrastructure team looked promising on paper: Product Owner in Italy, hardware engineers in Budapest, software engineers in Bucharest, designers in the UK. The team started with energy and enthusiasm, but within a month, something shifted. People stopped showing up for daily stand-ups. Cameras went dark during meetings. Engagement in retrospectives withered. This wasn't just about being distributed—plenty of teams work across time zones successfully. The problem ran deeper. The Scrum Master had a conflict of interest, serving dual roles as both facilitator and engineer. Team members were simultaneously juggling three or four other projects, treating this work as just another item on an impossibly long list. Steve spent a couple of months watching the deterioration before recognizing the root cause: there was no leadership sponsorship or buy-in. Stakeholders weren't invested. The team wasn't actually a team—they were individuals happening to work on the same project. Steve considers this a failure because he couldn't solve it. Sometimes, the absence of organizational support creates an unsolvable puzzle. Without leadership commitment, even the most skilled Scrum Master can't manufacture the conditions for team success. In this episode, we refer to , a book about organizational culture disguised as a DevOps novel. Self-reflection Question: Is your team truly dedicated to one mission, or are they a collection of individuals spread across competing priorities? Featured Book of the Week: The Phoenix Project by Gene Kim "There's a lot of good lightning bulb moments that go off." - Steve Martin Steve describes as a book about culture, not just DevOps. Written like a novel following a mock company, it creates continuous light bulb moments for readers. The book resonated deeply with Steve because it exposed patterns he'd experienced firsthand—particularly the anti-pattern of single points of failure. Steve had worked with an engineer who would spend entire weekends doing releases, holding everything in his head, then burning out and taking three days off to recover. This engineer was the bottleneck, the single point of failure that put the entire system at risk. The Phoenix Project illuminates how knowledge hoarding and dependency on individuals creates organizational fragility. The solution isn't just technical—it's cultural. Teams need to share knowledge and understanding, deliberately de-risking the concentration of expertise in one person's mind. Steve recommends this book for anyone trying to understand why organizational transformation requires more than process changes—it demands a fundamental shift in how teams think about knowledge, risk, and collaboration. [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Steve Martin You can link with . Steve is an Agile Coach, mentor, and founder of The Agile Master Academy. After over 14 years leading Agile transformation programmes, he's on a mission to elevate Scrum Masters—building high-performing teams, measurable impact, and influence—and raising industry standards of Agile mastery through practical, evidence-led coaching. You can also find Steve's insights on his . /episode/index/show/scrummastertoolbox/id/39441535

When the Gospel of Agile Becomes a Barrier to Change | Steve Martin 12/29/2025

When the Gospel of Agile Becomes a Barrier to Change | Steve Martin Steve Martin: When the Gospel of Agile Becomes a Barrier to Change Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "It took me a while to realize that that's what I was doing. I felt the reason wasn't working was them, it wasn't me." - Steve Martin Steve carried the Scrum Guide like a Bible in his early days as an Agile coach. He was a purist—convinced he had an army of Agile practitioners behind him, ready to transform every team he encountered. When teams questioned his approach, he would shut down the conversation: "Don't challenge me on this, because this is how it's supposed to be." But pushing against the tide and spreading the gospel created something unexpected: resistance. The more Steve insisted on his purist view, the more teams pushed back. It took him a couple of years to recognize the pattern. The problem wasn't the teams refusing to change—it was his approach. Steve's breakthrough came when he started teaching and realized he needed to meet people where they are, not force them to come to him. Like understanding a customer's needs, he learned to build empathy with teams, Product Owners, and leaders. He discovered the power of creating personas for the people he was coaching, understanding their context before prescribing solutions. The hardest part wasn't learning this lesson—it was being honest about his failures and admitting that his righteous certainty had been the real impediment to transformation. Self-reflection Question: Are you meeting your teams where they are, or are you pushing them toward where you think they should be? [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Steve Martin You can link with . Steve is an Agile Coach, mentor, and founder of The Agile Master Academy. After over 14 years leading Agile transformation programmes, he's on a mission to elevate Scrum Masters—building high-performing teams, measurable impact, and influence—and raising industry standards of Agile mastery through practical, evidence-led coaching. You can also find Steve's insights on his . /episode/index/show/scrummastertoolbox/id/39441600

BONUS The Operating System for Software-Native Organizations - The Five Core Principles With Vasco Duarte 12/26/2025

BONUS The Operating System for Software-Native Organizations - The Five Core Principles With Vasco Duarte BONUS: The Operating System for Software-Native Organizations - The Five Core Principles In this BONUS episode, the final installment of our Special Xmas 2025 reflection on Software-native businesses, we explore the five fundamental principles that form the operating system for software-native organizations. Building on the previous four episodes, this conversation provides the blueprint for building organizations that can adapt at the speed of modern business demands, where the average company lifespan on the S&P 500 has dropped from 33 years in the 1960s to a projected 12 years by 2027. The Challenge of Adaptation "What we're observing in Ukraine is adaptation happening at a speed that would have been unthinkable in traditional military contexts - new drone capabilities emerge, countermeasures appear within days, and those get countered within weeks." The opening draws a powerful parallel between the rapid adaptation we're witnessing in drone warfare and the existential threats facing modern businesses. While our businesses aren't facing literal warfare, they are confronting dramatic disruption. Clayton Christensen documented this in "The Innovator's Dilemma," but what he observed in the 1970s and 80s is happening exponentially faster now, with software as the accelerant. If we can improve businesses' chances of survival even by 10-15%, we're talking about thousands of companies that could thrive instead of fail, millions of jobs preserved, and enormous value created. The central question becomes: how do you build an organization that can adapt at this speed? Principle 1: Constant Experimentation with Tight Feedback Loops "Everything becomes an experiment. Not in the sense of being reckless or uncommitted, but in being clear about what we're testing and what we expect to learn. I call this: work like a scientist: learning is the goal." Software developers have practiced this for decades through Test-Driven Development, but now this TDD mindset is becoming the ruling metaphor for managing products and entire businesses. The practice involves framing every initiative with three clear elements: the goal (what are we trying to achieve?), the action (what specific thing will we do?), and the learning (what will we measure to know if it worked?). When a client says "we need to improve our retrospectives," software-native organizations don't just implement a new format. Instead, they connect it to business value - improving the NPS score for users of a specific feature by running focused retrospectives that explicitly target user pain points and tracking both the improvements implemented and the actual NPS impact. After two weeks, you know whether it worked. The experiment mindset means you're always learning, never stuck. This is TDD applied to organizational change, and it's powerful because every process change connects directly to customer outcomes. Principle 2: Clear Connection to Business Value "Software-native organizations don't measure success by tasks completed, story points delivered, or features shipped. Or even cycle time or throughput. They measure success by business outcomes achieved." While this seems obvious, most organizations still optimize for output, not outcomes. The practice uses Impact Mapping or similar outcome-focused frameworks where every initiative answers three questions: What business behavior are we trying to change? How will we measure that change? What's the minimum software needed to create that change? A financial services client wanted to "modernize their reporting system" - a 12-month initiative with dozens of features in project terms. Reframed through a business value lens, the goal became reducing time analysts spend preparing monthly reports from 80 hours to 20 hours, measured by tracking actual analyst time, starting with automating just the three most time-consuming report components. The first delivery reduced time to 50 hours - not perfect, but 30 hours saved, with clear learning about which parts of reporting actually mattered. The organization wasn't trying to fulfill requirements; they were laser focused on the business value that actually mattered. When you're connected to business value, you can adapt. When you're committed to a feature list, you're stuck. Principle 3: Software as Value Amplifier "Software isn't just 'something we do' or a support function. Software is an amplifier of your business model. If your business model generates $X of value per customer through manual processes, software should help you generate $10X or more." Before investing in software, ask whether this can amplify your business model by 10x or more - not 10% improvement, but 10x. That's the threshold where software's unique properties (zero marginal cost, infinite scale, instant distribution) actually matter, and where the cost/value curve starts to invert. Remember: software is still the slowest and most expensive way to check if a feature would deliver value, so you better have a 10x or more expectation of return. Stripe exemplifies this principle perfectly. Before Stripe, accepting payments online required a merchant account (weeks to set up), integration with payment gateways (months of development), and PCI compliance (expensive and complex). Stripe reduced that to adding seven lines of code - not 10% easier, but 100x easier. This enabled an entire generation of internet businesses that couldn't have existed otherwise: subscription services, marketplaces, on-demand platforms. That's software as amplifier. It didn't optimize the old model; it made new models possible. If your software initiatives are about 5-10% improvements, ask yourself: is software the right medium for this problem, or should you focus where software can create genuine amplification? Principle 4: Software as Strategic Advantage "Software-native organizations use software for strategic advantage and competitive differentiation, not just optimization, automation, or cost reduction. This means treating software development as part of your very strategy, not a way to implement a strategy that is separate from the software." means that instead of creating a strategy every few years and deploying it like a project, strategy and execution are continuously intertwined when it comes to software delivery. The practice involves organizing around competitive capabilities that software uniquely enables by asking: How can software 10x the value we generate right now? What can we do with software that competitors can't easily replicate? Where does software create a defensible advantage? How does our software create compounding value over time? Amazon Web Services didn't start as a product strategy but emerged from Amazon building internal capabilities to run their e-commerce platform at scale. They realized they'd built infrastructure that was extremely hard to replicate and asked: "What if we offered it to others?" AWS became Amazon's most profitable business - not because they optimized their existing retail business, but because they turned an internal capability into a strategic platform. The software wasn't supporting the strategy - the software became the strategy. Compare this to companies that use software just for cost reduction or process optimization - they're playing defense. Software-native companies use software to play offense, creating capabilities that change the competitive landscape. Continuous strategy means your software capabilities and your business strategy evolve together, in real-time, not in annual planning cycles. Principle 5: Real-Time Observability and Adaptive Systems "Software-native organizations use telemetry and real-time analytics not just to understand their software, but to understand their entire business and adapt dynamically. Observability practices from DevOps are actually ways of managing software delivery itself. We're bootstrapping our own operating system for software businesses." This principle connects back to Principle 1 but takes it to the organizational level. The practice involves building systems that constantly sense what's happening and can adapt in real-time: deploy with feature flags so you can turn capabilities on/off instantly, use A/B testing not just for UI tweaks but for business model experiments, instrument everything so you know how users actually behave, and build feedback loops that let the system respond automatically. Social media companies and algorithmic trading firms already operate this way. Instagram doesn't deploy a new feed algorithm and wait six months to see if it works - they're constantly testing variations, measuring engagement in real-time, adapting the algorithm continuously. The system is sensing and responding every second. High-frequency trading firms make thousands of micro-adjustments per day based on market signals. Imagine applying this to all businesses: a retail company that adjusts pricing, inventory, and promotions in real-time based on demand signals; a healthcare system that dynamically reallocates resources based on patient flow patterns; a logistics company whose routing algorithms adapt to traffic, weather, and delivery success rates continuously. This is the future of software-native organizations - not just fast decision-making, but systems that sense and adapt at software speed, with humans setting goals and constraints but software executing continuous optimization. We're moving from "make a decision, deploy it, wait to see results" to "deploy multiple variants, measure continuously, let the system learn." This closes the loop back to Principle 1 - everything is an experiment, but now the experiments run automatically at scale with near real-time signal collection and decision making. It’s Experiments All The Way Down "We established that software has become societal infrastructure. That software is different - it's not a construction project with a fixed endpoint; it's a living capability that evolves with the business." This five-episode series has built a complete picture: Episode 1 established that software is societal infrastructure and fundamentally different from traditional construction. Episode 2 diagnosed the problem - project management thinking treats software like building a bridge, creating cascade failures throughout organizations. Episode 3 showed that solutions already exist, with organizations like Spotify, Amazon, and Etsy practicing software-native development successfully. Episode 4 exposed the organizational immune system - the four barriers preventing transformation: the project mindset, funding models, business/IT separation, and risk management theater. Today's episode provides the blueprint - the five principles forming the operating system for software-native organizations. This isn't theory. This is how software-native organizations already operate. The question isn't whether this works - we know it does. The question is: how do you get started? The Next Step In Building A Software-Native Organization "This is how transformation starts - not with grand pronouncements or massive reorganizations, but with conversations and small experiments that compound over time. Software is too important to society to keep managing it wrong." Start this week by doing two things. First, start a conversation: pick one of these five principles - whichever resonates most with your current challenges - and share it with your team or leadership. Don't present it as "here's what we should do" but as "here's an interesting idea - what would this mean for us?" That conversation will reveal where you are, what's blocking you, and what might be possible. Second, run one small experiment: take something you're currently doing and frame it as an experiment with a clear goal, action, and learning measure. Make it small, make it fast - one week maximum, 24 hours if you can - then stop and learn. You now have the blueprint. You understand the barriers. You've seen the alternatives. The transformation is possible, and it starts with you. Recommended Further Reading The book by Christensen, Clayton: The book by Gojko Adzic: About Vasco Duarte Vasco Duarte is a thought leader in the Agile space, co-founder of Agile Finland, and host of the Scrum Master Toolbox Podcast, which has over 10 million downloads. Author of NoEstimates: How To Measure Project Progress Without Estimating, Vasco is a sought-after speaker and consultant helping organizations embrace Agile practices to achieve business success. You can link with . /episode/index/show/scrummastertoolbox/id/39411805

BONUS Breaking Through The Organizational Immune System | Vasco Duarte 12/25/2025

BONUS Breaking Through The Organizational Immune System | Vasco Duarte BONUS: Breaking Through The Organizational Immune System - Why Software-Native Organizations Are Still Rare With Vasco Duarte In this BONUS episode, we explore the organizational barriers that prevent companies from becoming truly software-native. Despite having proof that agile, iterative approaches work at scale—from Spotify to Amazon to Etsy—most organizations still struggle to adopt these practices. We reveal the root cause behind this resistance and expose four critical barriers that form what we call "The Organizational Immune System." This isn't about resistance to change; it's about embedded structures, incentives, and mental models that actively reject beneficial transformation. The Root Cause: Project Management as an Incompatible Mindset "Project management as a mental model is fundamentally incompatible with software development. And will continue to be, because 'project management' as an art needs to support industries that are not software-native." The fundamental problem isn't about tools or practices—it's about how we think about work itself. Project management operates on assumptions that simply don't hold true for software development. It assumes you can know the scope upfront, plan everything in advance, and execute according to that plan. But software is fundamentally different. A significant portion of the work only becomes visible once you start building. You discover that the "simple" feature requires refactoring three other systems. You learn that users actually need something different than what they asked for. This isn't poor planning—it's the nature of software. Project management treats discovery as failure ("we missed requirements"), while software-native thinking treats discovery as progress ("we learned something critical"). As Vasco points out in his NoEstimates work, what project management calls "scope creep" should really be labeled "value discovery" in software—because we're discovering more value to add. Discovery vs. Execution: Why Software Needs Different Success Metrics "Software hypotheses need to be tested in hours or days, not weeks, and certainly not months. You can't wait until the end of a 12-month project to find out your core assumption was wrong." The timing mismatch between project management and software development creates fundamental problems. Project management optimizes for plan execution with feedback loops that are months or years long, with clear distinctions between teams doing requirements, design, building, and testing. But software needs to probe and validate assumptions in hours or days. Questions like "Will users actually use this feature?" or "Does this architecture handle the load?" can't wait for the end of a 12-month project. When we finally discover our core assumption was wrong, we need to fully replan—not just "change the plan." Software-native organizations optimize for learning speed, while project management optimizes for plan adherence. These are opposing and mutually exclusive definitions of success. The Language Gap: Why Software Needs Its Own Vocabulary "When you force software into project management language, you lose the ability to manage what actually matters. You end up tracking task completion while missing that you're building the wrong thing." The vocabulary we use shapes how we think about problems and solutions. Project management talks about tasks, milestones, percent complete, resource allocation, and critical path. Software needs to talk about user value, technical debt, architectural runway, learning velocity, deployment frequency, and lead time. These aren't just different words—they represent fundamentally different ways of thinking about work. When organizations force software teams to speak in project management terms, they lose the ability to discuss and manage what actually creates value in software development. The Scholarship Crisis: An Industry-Wide Knowledge Gap "Agile software development represents the first worldwide trend in scholarship around software delivery. But most organizational investment still goes into project management scholarship and training." There's extensive scholarship in IT, but almost none about delivery processes until recently. The agile movement represents the first major wave of people studying what actually works for building software, rather than adapting thinking from manufacturing or construction. Yet most organizational investment continues to flow into project management certifications like PMI and Prince2, and traditional MBA programs—all teaching an approach with fundamental problems when applied to software. This creates an industry-wide challenge: when CFOs, executives, and business partners all think in project management terms, they literally cannot understand why software needs to work differently. The mental model mismatch isn't just a team problem—it's affecting everyone in the organization and the broader industry. Budget Cycles: The Project Funding Trap "You commit to a scope at the start, when you know the least about what you need to build. The budget runs out exactly when you're starting to understand what users actually need." Project thinking drives project funding: organizations approve a fixed budget (say $2M over 9 months) to deliver specific features. This seems rational and gives finance predictability, but it's completely misaligned with how software creates value. Teams commit to scope when they know the least about what needs building. The budget expires just when they're starting to understand what users actually need. When the "project" ends, the team disbands, taking all their accumulated knowledge with them. Next year, the cycle starts over with a new project, new team, and zero retained context. Meanwhile, the software itself needs continuous evolution, but the funding structure treats it as a series of temporary initiatives with hard stops. The Alternative: Incremental Funding and Real-Time Signals "Instead of approving $2M for 9 months, approve smaller increments—maybe $200K for 6 weeks. Then decide whether to continue based on what you've learned." Software-native organizations fund teams working on products, not projects. This means incremental funding decisions based on learning rather than upfront commitments. Instead of detailed estimates that pretend to predict the future, they use lightweight signals from the NoEstimates approach to detect problems early: Are we delivering value regularly? Are we learning? Are users responding positively? These signals provide more useful information than any Gantt chart. Portfolio managers shift from being "task police" asking "are you on schedule?" to investment curators asking "are we seeing the value we expected? Should we invest more, pivot, or stop?" This mirrors how venture capital works—and software is inherently more like VC than construction. Amazon exemplifies this approach, giving teams continuous funding as long as they're delivering value and learning, with no arbitrary end date to the investment. The Business/IT Separation: A Structural Disaster "'The business' doesn't understand software—and often doesn't want to. They think in terms of features and deadlines, not capabilities and evolution." Project thinking reinforces organizational separation: "the business" defines requirements, "IT" implements them, and project managers coordinate the handoff. This seems logical with clear specialization and defined responsibilities. But it creates a disaster. The business writes requirements documents without understanding what's technically possible or what users actually need. IT receives them, estimates, and builds—but the requirements are usually wrong. By the time IT delivers, the business need has changed, or the software works but doesn't solve the real problem. Sometimes worst of all, it works exactly as specified but nobody wants it. This isn't a communication problem—it's a structural problem created by project thinking. Product Thinking: Starting with Behavior Change "Instead of 'build a new reporting dashboard,' the goal is 'reduce time finance team spends preparing monthly reports from 40 hours to 4 hours.'" Software-native organizations eliminate the business/IT separation by creating product teams focused on outcomes. Using approaches like Impact Mapping, they start with behavior change instead of features. The goal becomes a measurable change in business behavior or performance, not a list of requirements. Teams measure business outcomes, not task completion—tracking whether finance actually spends less time on reports. If the first version doesn't achieve that outcome, they iterate. The "requirement" isn't sacred; the outcome is. "Business" and "IT" collaborate on goals rather than handing off requirements. They're on the same team, working toward the same measurable outcome with no walls to throw things over. Spotify's squad model popularized this approach, with each squad including product managers, designers, and engineers all focused on the same part of the product, all owning the outcome together. Risk Management Theater: The Appearance of Control "Here's the real risk in software: delivering software that nobody wants, and having to maintain it forever." Project thinking creates elaborate risk management processes—steering committees, gate reviews, sign-offs, extensive documentation, and governance frameworks. These create the appearance of managing risk and make everyone feel professional and in control. But paradoxically, the very practices meant to manage risk end up increasing the risk of catastrophic failure. This mirrors Chesterton's Fence paradox. The real risk in software isn't about following the plan—it's delivering software nobody wants and having to maintain it forever. Every line of code becomes a maintenance burden. If it's not delivering value, you're paying the cost forever or paying additional cost to remove it later. Traditional risk management theater doesn't protect against this at all. Gates and approvals just slow you down without validating whether users will actually use what you're building or whether the software creates business value. Agile as Risk Management: Fast Learning Loops "Software-native organizations don't see 'governance' and 'agility' as a tradeoff. Agility IS governance. Fast learning loops ARE how you manage risk." Software-native organizations recognize that agile and product thinking ARE risk management. The fastest way to reduce risk is delivering quickly—getting software in front of real users in production with real data solving real problems, not in demos or staging environments. Teams validate expected value by measuring whether software achieves intended outcomes. Did finance really reduce their reporting time? Did users actually engage with the feature? When something isn't working, teams change it quickly. When it is working, they double down. Either way, they're managing risk through rapid learning. Eric Ries's Lean Startup methodology isn't just for startups—it's fundamentally a software-native management practice. Build-Measure-Learn isn't a nice-to-have; it's how you avoid the catastrophic risk of building the wrong thing. The Risk Management Contrast: Theater vs. Reality "Which approach actually manages risk? The second one validates assumptions quickly and cheaply. The first one maximizes your exposure to building the wrong thing." The contrast between approaches is stark. Risk management theater involves six months of requirements gathering and design, multiple approval gates that claim to prevent risk but actually accumulate it, comprehensive test plans, and a big-bang launch after 12 months. Teams then discover users don't want it—and now they're maintaining unwanted software forever. The agile risk management approach takes two weeks to build a minimal viable feature, ships to a subset of users, measures actual behavior, learns it's not quite right, iterates in another two weeks, validates value before scaling, and only maintains software that's proven valuable. The second approach validates assumptions quickly and cheaply. The first maximizes exposure to building the wrong thing. The Immune System in Action: How Barriers Reinforce Each Other "When you try to 'implement agile' without addressing these structural barriers, the organization's immune system rejects it. Teams might adopt standups and sprints, but nothing fundamental changes." These barriers work together as an immune system defending the status quo. It starts with the project management mindset—the fundamental belief that software is like construction, that we can plan it all upfront, that "done" is a meaningful state. That mindset creates funding models that allocate budgets to temporary projects instead of continuous products, organizational structures that separate "business" from "IT" and treat software as a cost center, and risk management theater that optimizes for appearing in control rather than actually learning. Each barrier reinforces the others. The funding model makes it hard to keep stable product teams. The business/IT separation makes it hard to validate value quickly. The risk theater slows down learning loops. The whole system resists change—even beneficial change—because each part depends on the others. This is why so many "agile transformations" fail: they treat the symptoms (team practices) without addressing the disease (organizational structures built on project thinking). Breaking Free: Seeing the System Clearly "Once you see the system clearly, you can transform it. You now know the root cause, how it manifests, and what the alternatives look like." Understanding these barriers is empowering. It's not that people are stupid or resistant to change—organizations have structural barriers built on a fundamental mental model mismatch. But once you see the system clearly, transformation becomes possible. You now understand the root cause (project management mindset), how it manifests in your organization (funding models, business/IT separation, risk theater), and what the alternatives look like through real examples from companies successfully operating as software-native organizations. The path forward requires addressing the disease, not just the symptoms—transforming the fundamental structures and mental models that shape how your organization approaches software. Recommended Further Reading About Vasco Duarte Vasco Duarte is a thought leader in the Agile space, co-founder of Agile Finland, and host of the Scrum Master Toolbox Podcast, which has over 10 million downloads. Author of NoEstimates: How To Measure Project Progress Without Estimating, Vasco is a sought-after speaker and consultant helping organizations embrace Agile practices to achieve business success. You can . /episode/index/show/scrummastertoolbox/id/39411675

BONUS: Recovering the Essence of Agile - What's Already Working With Vasco Duarte 12/24/2025

BONUS: Recovering the Essence of Agile - What's Already Working With Vasco Duarte Xmas Special: Recovering the Essence of Agile - What's Already Working in Software-Native Organizations In this BONUS Xmas Special episode, we explore what happens when we strip away the certifications and branded frameworks to recover the essential practices that make software development work. Building on Episode 2's exploration of the Project Management Trap, Vasco reveals how the core insights that sparked the Agile revolution remain valid - and how real organizations like Spotify, Amazon, and Etsy embody these principles to thrive in today's software-driven world. The answer isn't to invent something new; it's to amplify what's already working. Agile as an Idea, Not a Brand "The script (sold as the solution) will eventually kill the possibility of the conversation ever happening with any quality." We establish a parallel between good conversations and good software development. Just as creating "The Certified Conversational Method™" with prescribed frameworks and certification levels would miss the point of genuine dialogue, the commodification of agile into Agile™ has obscured its essential truth. The core idea was simple and powerful: build software in small increments, get it in front of real users quickly, learn from their actual behavior, adapt based on what you learn, and repeat continuously. This wasn't revolutionary - it was finally recognizing how software actually works. You can't know if your hypothesis about user needs is correct until users interact with it, so optimize for learning speed, not planning precision. But when the need to certify and validate "doing Agile right" took over, the idea got packaged, and often the package became more important than the principle. Four Fundamental Practices That Enable Living Software "Every deployment was a chance to see how users actually responded." Software-native organizations distinguish themselves through core practices that align with software as a living capability. In this episode, we review four critical ones: First, iterative delivery means shipping the smallest valuable increment possible and building on it - exemplifies this approach, where each small change serves as a learning opportunity. Second, tight feedback loops get software in front of real users as fast as possible, whether through paper prototypes or production deployments. Third, continuous improvement of the process itself creates meta-feedback loops, as demonstrated by principle introduced by , where development teams running their own services in production learn rapidly to write more resilient code. Fourth, product thinking over project thinking organizes teams around long-lived products rather than temporary projects, allowing teams to develop deep expertise and become living capabilities themselves, accumulating knowledge and improving over time. Spotify's Evolutionary Approach "The Spotify model has nothing to do with Spotify really. It was just a snapshot of how that one company worked at the time." Spotify's journey reveals a critical insight often missed in discussions of their famous organizational model. Starting with standard Scrum methodology pre-2012, with autonomous teams organized into tribes, documented (direct PDF link). But post-2016, internal staff and agile coaches noted that the "Spotify model" had become mythology, and the company had moved on from original concepts to address new challenges. the model has taken on a life of its own, much like Lean's relationship to Toyota. The key insight isn't the specific structure - it's that Spotify treated their own organizational design as a living capability, continuously adapting based on what worked and what didn't rather than implementing "the model" and declaring victory. That's software-native thinking applied to organization design itself. Amazon's Two-Pizza Teams and Massive Scale "Amazon deploys code every 11.7 seconds on average. That's over 7,000 deployments per day across the organization." () goes far deeper than team size. Teams small enough to be fed with two pizzas (roughly 6-10 people) gain crucial autonomy and ownership: each team owns specific services and APIs, makes their own technical decisions, runs their services in production, and manages inter-team dependencies through APIs rather than meetings. This structure enabled Amazon to scale massively while maintaining speed, as teams could iterate independently without coordinating with dozens of other teams. The staggering deployment frequency - over 7,000 times per day as of 2021 - is only possible with a software-native structure for the company itself, demonstrating that this isn't just about managing software delivery but touches everything, including how teams are organized. Why These Practices Work "These practices work because they align with what software actually is: a living, evolvable capability." The effectiveness of software-native approaches stems from their alignment with software's true nature. Traditional project approaches assume we can know requirements upfront, estimate accurately, build it right the first time, and reach a meaningful "done" state. Software-native approaches recognize that requirements emerge through interaction with users, estimation is less important than rapid learning, "right" is discovered iteratively rather than designed upfront, and "done" only happens when we stop evolving the software. When Etsy ships 50 times per day, they're optimizing for learning where each deployment is a hypothesis test. When Amazon's teams own services end-to-end, they're creating tight feedback loops where teams feel the pain of their own decisions directly. When Spotify continuously evolves their organizational model, they're treating their own structure as software that should adapt to changing needs. The Incomplete Picture and the Question of Universal Adoption "If these approaches work, why aren't they universal?" We’re not trying to paint a unrealistically rosy picture - these organizations aren't perfect. , Amazon's culture has been criticized as demanding and sometimes brutal, and Etsy has gone through multiple strategic shifts. But what matters is that they're practicing software-native development at scale, and it's working well enough that they can compete and thrive. They're not following a playbook perfectly but embodying principles and adapting continuously. This raises the critical question that will be explored in the next episode: if these approaches work, why do so many organizations still operate in project mode, and why do "agile transformations" so often fail to deliver real change? Understanding the resistance - what we call The Organizational Immune System - is essential to overcoming it. References for Further Reading A book on the shift from “projects” to “products”: About Vasco Duarte Vasco Duarte is a thought leader in the Agile space, co-founder of Agile Finland, and host of the Scrum Master Toolbox Podcast, which has over 10 million downloads. Author of NoEstimates: How To Measure Project Progress Without Estimating, Vasco is a sought-after speaker and consultant helping organizations embrace Agile practices to achieve business success. /episode/index/show/scrummastertoolbox/id/39411615

Xmas Special: Why project management tools fail software development - and what works instead! 12/23/2025

Xmas Special: Why project management tools fail software development - and what works instead! Xmas Special: Why project management tools fail software development - and what works instead! In this BONUS episode, we dive deep into The Project Management Trap, continuing our exploration from Episode 1 where we established that software is societal infrastructure being managed with tools from the 1800s. We examine why project management frameworks - designed for building railroads and ships - are fundamentally misaligned with software development, and what happens when we treat living capabilities like construction projects with defined endpoints. The Origin Story - Where Project Management Came From "The problem isn't that project management is bad. The problem is that software isn't building a railroad or a building, or setting up a process that will run forever (like a factory)." Project management emerged from industries with hard physical constraints - building the , coordinating factory machinery, managing finite and expensive materials. invented in the 1910s for factory scheduling, worked brilliantly for coordinating massive undertakings with calculable physics, irreversible decisions, and clear completion points. When the rails met, you were done. When the bridge was built, the project ended. These tools gave us remarkable precision for building ships, bridges, factories, and highways. But software operates in a completely different reality - one where the raw materials are time and brainpower, not minerals and hardware, and where the transformation happens in unique creative moments rather than repeated mechanical movements. The Seductive Clarity Of Project Management Artifacts "In software, we almost never know either of those things with certainty." Project management is tempting for software leaders because it offers comforting certainty. Gantt charts show every task laid out, milestones mark clear progress, "percent complete" gives us a number, and a defined "done" promises relief. The typical software project kickoff breaks down into neat phases: requirements gathering (6 weeks), design (4 weeks), development (16 weeks), testing (4 weeks), deployment (2 weeks) - total 32 weeks, done by Q3. Leadership loves this. Finance can budget it. Everyone can plan around it. But this is false precision. Software isn't pouring concrete where you measure twice and pour once. Every line of code is a hypothesis about what users need and how the system should behave. That 32-week plan assumes we know exactly what to build and exactly how long each piece takes - assumptions that are almost never true in software development. The Completion Illusion "Software products succeed by evolving. Projects end; products adapt." "Done" is the wrong goal for living software. We expand on the Slack story from Episode 1 to illustrate this point. If Slack's team had thought in project terms in 2013, they might have built a functional tool with channels, direct messages, file sharing, and search - shipped on time and on budget by Q2 2014, project complete. But that wasn't the end; it was the beginning. Through continuous user feedback and evolution, Slack added threaded conversations (2017), audio/video calls (2016), workflow automation (2019), and Canvas for knowledge management (2023). Each wasn't maintenance or bug fixing - these were fundamental enhancements. Glass's research shows that 60% of maintenance costs are enhancements, not fixes. By 2021, when Salesforce acquired Slack for $27.7 billion, it bore little resemblance to the 2014 version. The value wasn't in that initial "project" - it was in the continuous evolution. If they'd thought "build it, ship it, done," Slack would have died competing against HipChat and Campfire. When Projects Succeed (Well, Some Do, Anyway) But Software Fails "They tried to succeed at project management. They ended up failing at both software delivery AND project management!" examining five distinct cases from five different countries that represent what's wrong with project thinking for software. These projects tried hard to do everything right by project management standards: detailed requirements (thousands of pages), milestone tracking, contractor coordination, hitting fixed deadlines, and proper auditing. What they didn't have was iterative delivery to test with real users early, feedback loops to discover problems incrementally, adaptability to change based on learning, or a "living capability" mindset. Project thinking demanded: get all requirements right upfront (otherwise no funding), build it all, test at the end, launch on deadline. Software thinking demands: launch something minimal early, get real user feedback, iterate rapidly, evolve the capability. These projects succeeded at following project management rules but failed at delivering valuable software. What Software-Native Delivery Management Looks Like "Software is unpredictable not because we're bad at planning - it's unpredictable because we're creating novel solutions to complex problems, and in a completely different economic system." If not projects, then what? Vasco has been exploring this question for years, since publishing The answer starts with thinking in products and capabilities, not projects - recognizing that products have ongoing evolution, capabilities are cultivated and improved rather than "delivered" and done, and value is measured in outcomes rather than task completion. Instead of comprehensive planning, we need iteration and constant decision-making based on validated hypotheses: start with "We believe users need X," run experiments by building small and testing with real users, then learn and adapt. Instead of fixed scope, define the problem (not the solution), allow the solution to evolve as you learn, and optimize for learning speed rather than task completion. The contrast is clear: project thinking says "We will build features A, B, C, D, and E by Q3, then we're done." Software-native thinking says "We're solving problem X for users. We'll start with the riskiest hypothesis, build a minimal version, ship it to 100 users next week, and learn whether we're on the right track." The appropriate response to software's inherent unpredictability isn't better planning - it's faster learning. References for Further Reading Vasco Duarte's Glass, Robert L. - Fact 42: "Enhancement is responsible for roughly 60 percent of software maintenance costs. Error correction is roughly 17 percent. Therefore, software maintenance is largely about adding new capability to old software, not fixing it." - Slack’s answer to the knowledge management problem. About Vasco Duarte Vasco Duarte is a thought leader in the Agile space, co-founder of Agile Finland, and host of the Scrum Master Toolbox Podcast, which has over 10 million downloads. Author of NoEstimates: How To Measure Project Progress Without Estimating, Vasco is a sought-after speaker and consultant helping organizations embrace Agile practices to achieve business success. /episode/index/show/scrummastertoolbox/id/39411535

Xmas Special: Software Industry Transformation - Why Software Development Must Mature With Vasco Duarte 12/22/2025

Xmas Special: Software Industry Transformation - Why Software Development Must Mature With Vasco Duarte Xmas Special: Software Industry Transformation - Why Software Development Must Mature - a five-episode deep dive into how software as an industry needs to transform. In this opening episode, we explore the fundamental disconnect between how we manage software and what software actually is. From small businesses to global infrastructure, software has become the backbone of modern society, yet we continue to manage it with tools designed for building ships in the 1800s. This episode sets the stage for understanding why software development must evolve into a mature discipline. Software Runs Everything Now "Without any single piece, I couldn't operate - and I'm tiny. Scale this reality up: software isn't just in tech companies anymore." Even the smallest businesses today run entirely on software infrastructure. A small consulting and media business depends on WordPress for websites, Kajabi for courses, Stripe for payments, Quaderno for accounting, plus email, calendar, CRM systems, and AI assistants for content creation. The challenge? We're managing this critical infrastructure with tools designed for building physical structures with fixed requirements - an approach that fundamentally misunderstands what software is and how it evolves. This disconnect has to change. The Oscillation Between Technology and Process "AI amplifies our ability to create software, but doesn't solve the fundamental process problems of maintaining, evolving, and enhancing that software over its lifetime." Software improvement follows a predictable pattern: technology leaps forward, then processes must adapt to manage the new complexity. In the 1960s-70s, we moved from machine code to COBOL and Fortran, which was revolutionary but led to the "software crisis" when we couldn't manage the resulting complexity. This eventually drove us toward structured programming and object-oriented programming as process responses, which, in turn, resulted in technology changes! Today, AI tools like GitHub Copilot, ChatGPT, and Claude make writing code absurdly easy - but writing code was never the hard part. Robert Glass documents in "Facts and Fallacies of Software Engineering" that maintenance typically consumes between 40 and 80 percent of software costs, making “maintenance” probably the most important life cycle phase. We're overdue for a process evolution that addresses the real challenge: maintaining, evolving, and enhancing software over its lifetime. Software Creates An Expanding Possibility Space "If they'd treated it like a construction project ('ship v1.0 and we're done'), it would never have reached that value." Traditional project management assumes fixed scope, known solutions, and a definable "done" state. The Sydney Opera House exemplifies this: designed in 1957, completed in 1973, ten times over budget, with the architect resigning - but once built, it stands with “minimal” (compared to initial cost) maintenance. Software operates fundamentally differently. Slack started as an internal tool for a failed gaming company called Glitch in 2013. When the game failed, they noticed their communication tool was special and pivoted entirely. After launching in 2014, Slack continuously evolved based on user feedback: adding threads in 2017, calls in 2016, workflow builder in 2019, and Canvas in 2023. Each addition changed what was possible in organizational communication. precisely because it kept evolving with user needs. The key difference is that software creates possibility space that didn't exist before, and that space keeps expanding through continuous evolution. Software Is Societal Infrastructure "This wasn't a cyber attack - it was a software update gone wrong." Software has become essential societal infrastructure, not optional and not just for tech companies. In July 2024, a faulty software update from cybersecurity firm CrowdStrike crashed 8.5 million Windows computers globally. Airlines grounded flights, hospitals canceled surgeries, banks couldn't process transactions, and 911 services went down. The global cost exceeded $10 billion. This wasn't an attack - it was a routine update that failed catastrophically. AWS outages in 2021 and 2023 took down major portions of the internet, stopping Netflix, Disney+, Robinhood, and Ring doorbells from working. CloudFlare outages similarly cascaded across daily-use services. When software fails, society fails. We cannot keep managing something this critical with tools designed for building physical things with fixed requirements. Project management was brilliant for its era, but that era isn't this one. The Path Ahead: Four Critical Challenges "The software industry doesn't just need better tools - it needs to become a mature discipline." This five-episode series will address how we mature as an industry by facing four critical challenges: Episode 2: The Project Management Trap - Why we think in terms of projects, dates, scope, and "done" when software is never done, and how this mindset prevents us from treating software as a living capability Episode 3: What's Already Working - The better approaches we've already discovered, including iterative delivery, feedback loops, and continuous improvement, with real examples of companies doing this well Episode 4: The Organizational Immune System - Why better approaches aren't universal, how organizations unconsciously resist what would help them, and the hidden forces preventing adoption Episode 5: Software-Native Organizations - What it means to truly be a software-native organization, transforming how the business thinks, not just using agile on teams Software is too important to our society to keep getting it wrong. We have much of the knowledge we need - the challenge is adoption and evolution. Over the next four episodes, we'll build this case together, starting with understanding why we keep falling into the same trap. References For Further Reading Glass, Robert L. "" - Fact 41, page 115 CrowdStrike incident: AWS outages: , , and incidents CloudFlare outages: , and major incident Slack history and Salesforce acquisition: Sydney Opera House: About Vasco Duarte Vasco Duarte is a thought leader in the Agile space, co-founder of Agile Finland, and host of the Scrum Master Toolbox Podcast, which has over 10 million downloads. Author of NoEstimates: How To Measure Project Progress Without Estimating, Vasco is a sought-after speaker and consultant helping organizations embrace Agile practices to achieve business success. . /episode/index/show/scrummastertoolbox/id/39411470

From Spreadsheets to Discovery—Helping POs Make the Transition | Natalia Curusi 12/19/2025

From Spreadsheets to Discovery—Helping POs Make the Transition | Natalia Curusi Natalia Curusi: From Spreadsheets to Discovery—Helping POs Make the Transition The Great Product Owner: Taking Ownership and Coaching the Team Forward Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "That person was not just a great product owner, but a great coach—he had excellent communication and stakeholder management skills, and he coached myself as a Scrum Master, showing me how product ownership should look like." - Natalia Curusi Natalia worked with a Product Owner who embodied everything the role should be. He didn't come from a technical background, but he possessed exceptional domain knowledge, outstanding communication skills, and stakeholder management expertise you rarely find in one person. What made him truly remarkable was that he coached everyone around him, including Natalia as the Scrum Master. He demonstrated full empowerment and ownership—making decisions himself rather than constantly escalating to higher management. When risks needed to be taken, he took them with courage and conviction. The team trusted him completely because he balanced business needs with team capacity, always understanding what they could realistically achieve. Over the past five years, this person has been promoted multiple times and now serves as a global director of product, still with the same company. When Natalia thinks about what great product ownership looks like, she thinks of him—someone who combined technical understanding with coaching ability, took genuine ownership of outcomes, and empowered the team through clear vision and decisive leadership. These are exactly the skills that are hardest to find in the market, yet when you find them, the impact is transformative for the entire organization. Self-reflection Question: Does your Product Owner take ownership and make decisions, or do they constantly escalate to higher management, preventing the team from moving forward with confidence? The Bad Product Owner: Assigned Without Training, Support, or Willingness "She was a great subject matter expert with deep domain knowledge, but the organization assigned her the product owner role without her willingness, without training, and while she was already 80% loaded with other responsibilities." - Natalia Curusi Natalia encountered a Product Owner anti-pattern that reveals a systemic organizational failure. The person was an exceptional subject matter expert with incredible domain knowledge, but when the organization decided to adopt Agile, they assigned her the PO role like sticking a label on a box—no training, no consent, no preparation. She was already working at 80% capacity on other responsibilities and had no understanding of what product ownership meant. Frustrated and overwhelmed, she approached the role from a command-and-control mindset. At the project start, she brought a massive spreadsheet of requirements, expecting the team to implement them sequentially. The team tried a different approach, wanting to understand problems before discussing solutions, but the PO surprised everyone by re-introducing the spreadsheet in a later meeting—a clear sign of misalignment and broken trust. Natalia, recognizing this was a battle she couldn't win without organizational support, chose to manage the relationship rather than create open conflict. She worked to mediate between the PO's spreadsheet approach and the team's need for discovery and iterative development. The real anti-pattern wasn't the individual—it was the organization assigning critical roles without providing training, time, or psychological safety. This situation illustrates why product ownership fails: not from bad people, but from bad systems that set people up to fail. Self-reflection Question: When you see a struggling Product Owner, are you addressing the individual's behavior or the systemic conditions that set them up to fail in the first place? [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Natalia Curusi With over 20 years in software delivery, Natalia Curusi is an expert in Agile Transformations, Delivery Optimisation, and Systems Thinking. As an Agile Coach at Endava, she leads Asia Pacific initiatives, driving business agility and continuous improvement while mentoring teams to build customer-centric, high-performing, and collaborative cultures. You can link with . You can also follow Natalia on . /episode/index/show/scrummastertoolbox/id/39411420

Measuring What Matters Beyond Velocity and Story Points | Natalia Curusi 12/18/2025

Measuring What Matters Beyond Velocity and Story Points | Natalia Curusi Natalia Curusi: Measuring What Matters Beyond Velocity and Story Points Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "We as Scrum Masters need to put a scope for ourselves—we need to aim to leave the place where we work a little bit better than it was, and to make sure that this place could improve itself without us." - Natalia Curusi Natalia defines success for Scrum Masters with crystal clarity: leave the organization better than you found it, and ensure it can continue improving when you're gone. This means fostering independence and ownership in teams so they can perform whether you're on vacation, in another meeting, or have moved to coaching other teams. The opposite pattern—where everything falls apart when the Scrum Master isn't present—reveals someone who hasn't truly succeeded in the role. Natalia also emphasizes the importance of establishing metrics early, but not the traditional ones. Using velocity as a metric is an anti-pattern that focuses teams on the wrong outcomes. Instead, she recommends metrics like predictability, team morale, psychological safety measured through 360 feedback, and the quality of conversations both within teams and with stakeholders. But metrics alone don't tell the story. Natalia champions the concept of —going to see what's actually happening, talking to people, observing the reality rather than just reviewing dashboard numbers. Some metrics are easily gamed, others provide only narrow perspectives on reality. The most important practice is using metrics to trigger reflection and adaptation, not as fixed targets. Natalia believes strongly that the quality of conversations—how teams discuss options, make decisions together, and adapt when facing pressure—reveals more about a Scrum Master's success than any velocity chart ever could. The ultimate question: can your team succeed without you? Self-reflection Question: If you disappeared from your team tomorrow, would they continue improving, or would progress stop until someone replaced you? Featured Retrospective Format for the Week: Spotify Squad Health Check "This is a multidimensional retro that I run with teams every 2 to 3 months—you need around 30 minutes for it, and I often get insights and new ideas from this retrospective that help me as a Scrum Master." - Natalia Curusi The is Natalia's favorite retrospective format because it provides a comprehensive view of team health across multiple dimensions. Unlike traditional retrospectives that might focus on a single sprint or specific issue, this format examines the team's overall state across areas like teamwork, support, mission clarity, and technical quality. Teams rate themselves on various health indicators, creating a visual representation that reveals patterns over time. What makes this particularly valuable is that it works whether you know the team well or are just starting with them—either way, you gain insights and "aha moments" about where the team truly stands. The multidimensional nature prevents teams from optimizing just one aspect while neglecting others, and the regular cadence (every 2-3 months) allows you to track trends and celebrate improvements. For Natalia, this format consistently surfaces the hidden challenges that teams might not raise in regular retrospectives, making it an essential tool in her Scrum Master toolkit. [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Natalia Curusi With over 20 years in software delivery, Natalia Curusi is an expert in Agile Transformations, Delivery Optimisation, and Systems Thinking. As an Agile Coach at Endava, she leads Asia Pacific initiatives, driving business agility and continuous improvement while mentoring teams to build customer-centric, high-performing, and collaborative cultures. You can link with . /episode/index/show/scrummastertoolbox/id/39411350

Demonstrating Your Value When the Market Questions Agile Roles | Natalia Curusi 12/17/2025

Demonstrating Your Value When the Market Questions Agile Roles | Natalia Curusi Natalia Curusi: Demonstrating Your Value When the Market Questions Agile Roles Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "My challenging topic is about the demand of agility in the market—how do we fit ourselves as scrum masters in that AI era? How can we demonstrate our competence and contribution when there's a perception that agile roles bring little value?" - Natalia Curusi Natalia faces the challenge every Scrum Master in 2025 grapples with: how to demonstrate value in an era when business perceives agile roles as optional overhead. The market has contracted, companies are optimizing budgets, and Scrum Masters often appear first on the chopping block. There's talk of "" where developers are expected to absorb Scrum Master responsibilities, and questions about how AI might replace the human facilitation work that coaches provide. But Natalia believes the answer lies in understanding something fundamental: the Scrum Master is a deeply situational and contextual role that adapts to what the team needs each day. Some teams need help with communication spaces, others need work structure like Kanban boards, still others need translation between technical realities and stakeholder expectations. The challenge is that this situational nature makes it incredibly hard to explain to business leaders who think in fixed job descriptions and measurable outputs. Natalia's approach involves bringing metrics—not velocity, which focuses on the wrong things, but metrics around team independence, continuous improvement, and organizational capability. She suggests concepts like —going to see what's actually happening rather than relying only on numbers. The real question Natalia poses is this: the biggest value we can bring to an organization is to leave it better than we found it, but how do we make that visible and tangible to business stakeholders who need justification for our roles? Self-reflection Question: If you had to demonstrate your value as a Scrum Master using only observable evidence from the past month, what would you show your leadership? [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Natalia Curusi With over 20 years in software delivery, Natalia Curusi is an expert in Agile Transformations, Delivery Optimisation, and Systems Thinking. As an Agile Coach at Endava, she leads Asia Pacific initiatives, driving business agility and continuous improvement while mentoring teams to build customer-centric, high-performing, and collaborative cultures. You can link with . /episode/index/show/scrummastertoolbox/id/39411265

The Dark Side of High-Performing Dream Teams | Natalia Curusi 12/16/2025

The Dark Side of High-Performing Dream Teams | Natalia Curusi Natalia Curusi: The Dark Side of High-Performing Dream Teams Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "I was proud of this team—I helped form them from the start, we traveled to the client together, they were mature and independent, they even jelled outside the workplace. This was my dream team." - Natalia Curusi Natalia had built something special. The team was technically strong, emotionally connected, and highly productive. They socialized outside work, traveled together to client sites, and operated with remarkable independence. But when a new junior developer joined, everything started to unravel. The existing team members were like heroes—fast, skilled, confident. The newcomer couldn't keep pace, and slowly Natalia noticed something disturbing: the team started making fun of the new member during retrospectives and stand-ups. The person became an outlier, a black swan ignored by the group. Natalia conducted one-on-one meetings with both the new member and the team, but the situation only worsened. The new person insisted they were fine and didn't need help. The team members claimed they were just joking around. Meanwhile, the team structure and morale deteriorated. Natalia realized she was watching her dream team self-destruct through a form of bullying—something she hadn't even recognized at the time. Finally, she understood she couldn't handle this alone and escalated to the head of discipline and the organizational psychologist. Together, they decided to rotate the person to another team where they felt more comfortable. Natalia learned a painful lesson: as Scrum Masters, we don't need to solve everything ourselves, and sometimes the best solution is recognizing when to use the support structure around us rather than treating it as a personal failure. In this episode, we refer to and . Self-reflection Question: When have you witnessed subtle forms of exclusion in your team, and did you recognize them early enough to intervene effectively? Featured Book of the Week: Coaching Agile Teams by Lyssa Adkins "This was the first book about agile coaching that I read, and it's how I understood that I was already playing the scrum master role without even knowing it—I understood that I was already acting like a glue for the team." - Natalia Curusi Natalia discovered at a pivotal moment in her career. The book revealed something profound: if you're irreplaceable, there's a problem. A great Scrum Master or coach makes themselves obsolete by growing team members who can replace them. The team should be able to perform independently when you're on vacation or move to another assignment. Lyssa Adkins showed Natalia that she needed to let go of over-control and over-responsibility, focusing instead on growing the team's capabilities. The book remains one of Natalia's top recommendations for every junior Scrum Master wanting to embrace the role, alongside , which teaches facilitators how to run interactive workshops where people learn from each other rather than just listening to slides. [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Natalia Curusi With over 20 years in software delivery, Natalia Curusi is an expert in Agile Transformations, Delivery Optimisation, and Systems Thinking. As an Agile Coach at Endava, she leads Asia Pacific initiatives, driving business agility and continuous improvement while mentoring teams to build customer-centric, high-performing, and collaborative cultures. You can link with . /episode/index/show/scrummastertoolbox/id/39411205

When Your Technical Expertise Becomes Your Biggest Scrum Master Weakness | Natalia Curusi 12/15/2025

When Your Technical Expertise Becomes Your Biggest Scrum Master Weakness | Natalia Curusi Natalia Curusi: When Your Technical Expertise Becomes Your Biggest Scrum Master Weakness Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "I thought my technical background was my biggest strength, but I understood that this was my biggest weakness—I was coming into stand-ups saying 'I know how we need to fix that issue,' and I was a Scrum Master." - Natalia Curusi Natalia stepped into her first as team leader and Scrum Master full of confidence. With years of programming experience behind her, she believed she could guide her team through any technical challenge. But during morning stand-ups, she found herself suggesting solutions, directing technical approaches, and sharing her expertise freely. The team listened—after all, she was their former leader. They implemented her suggestions, but when those solutions failed, the team didn't have the thinking process to adapt them to their context. Natalia realized she was preventing the team's learning and ownership by taking control away from them. The turning point came when she made a deliberate choice: she selected the most technical person on the team to become the technical authority and committed to never stepping on his feet again. From that moment forward, she focused purely on the Scrum Master role—asking questions, fostering collaboration, and shutting up to listen actively. Years later, that technical lead followed her to another job, and they remain friends to this day. Natalia learned that her contribution wasn't about giving solutions—it was about keeping the team from losing ownership of their work. Self-reflection Question: When you attend your team's daily stand-up, are you contributing to collaboration, or is your contribution keeping the team from owning their work? [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Natalia Curusi With over 20 years in software delivery, Natalia Curusi is an expert in Agile Transformations, Delivery Optimisation, and Systems Thinking. As an Agile Coach at Endava, she leads Asia Pacific initiatives, driving business agility and continuous improvement while mentoring teams to build customer-centric, high-performing, and collaborative cultures. You can link with . /episode/index/show/scrummastertoolbox/id/39411160

Swimming in Tech Debt — Practical Techniques to Keep Your Team from Drowning in Its Codebase | Lou Franco 12/13/2025

Swimming in Tech Debt — Practical Techniques to Keep Your Team from Drowning in Its Codebase | Lou Franco BONUS: Swimming in Tech Debt — Practical Techniques to Keep Your Team from Drowning in Its Codebase In this fascinating conversation, veteran software engineer and author Lou Franco shares hard-won lessons from decades at startups, Trello, and Atlassian. We explore diving deep into the 8 Questions framework for evaluating tech debt decisions, personal practices that compound over time, team-level strategies for systematic improvement, and leadership approaches that balance velocity with sustainability. Lou reveals why tech debt is often the result of success, how to navigate the spectrum between ignoring debt and rewriting too much, and practical techniques individuals, teams, and leaders can use starting today. The Exit Interview That Changed Everything "We didn't go slower by paying tech debt. We went actually faster, because we were constantly in that code, and now we didn't have to run into problems." — Lou Franco Lou's understanding of tech debt crystallized during an exit interview at Atalasoft, a small startup where he'd spent years. An engineer leaving the company confronted him: "You guys don't care about tech debt." Lou had been focused on shipping features, believing that paying tech debt would slow them down. But this engineer told a different story — when they finally fixed their terrible build and installation system, they actually sped up. They were constantly touching that code, and removing the friction made everything easier. This moment revealed a fundamental truth: tech debt isn't just about code quality or engineering pride. It's about velocity, momentum, and the ability to move fast sustainably. Lou carried this lesson through his career at Trello (where he learned the dangers of rewriting too much) and Atlassian (where he saw enterprise-scale tech debt management). These experiences became the foundation for "Swimming in Tech Debt." Tech Debt Is the Result of Success "Tech debt is often the result of success. Unsuccessful projects don't have tech debt." — Lou Franco This reframes the entire conversation about tech debt. Failed products don't accumulate debt — they disappear before it matters. Tech debt emerges when your code survives long enough to outlive its original assumptions, when your user base grows beyond initial expectations, when your team scales faster than your architecture anticipated. At Atalasoft, they built for 10 users and got 100. At Trello, mobile usage exploded beyond their web-first assumptions. Success creates tech debt by changing the context in which code operates. This means tech debt conversations should happen at different intensities depending on where you are in the product lifecycle. Early startups pursuing product-market fit should minimize tech debt investments — move fast, learn, potentially throw away the code. Growth-stage companies need balanced approaches. Mature products benefit significantly from tech debt investments because operational efficiency compounds over years. Understanding this lifecycle perspective helps teams make appropriate decisions rather than applying one-size-fits-all rules. The 8 Questions Framework for Tech Debt Decisions "Those 8 questions guide you to what you should do. If it's risky, has regressions, and you don't even know if it's gonna work, this is when you're gonna do a project spike." — Lou Franco Lou introduces a systematic framework for evaluating whether to pay tech debt, inspired by Bob Moesta's push-pull forces from product management. The 8 questions create a complete picture: Visibility — Will people outside the team understand what we're doing? Alignment — Does this match our engineering values and target architecture? Resistance — How hard is this code to work with right now? Volatility — How often do we touch this code? Regression Risk — What's the chance we'll introduce new problems? Project Size — How big is this to fix? Estimate Risk — How uncertain are we about the effort required? Outcome Uncertainty — How confident are we the fix will actually improve things? High volatility and high resistance with low regression risk? Pay the debt now. High regression risk with no tests? Write tests first, then reassess. Uncertain outcomes on a big project? Do a spike or proof of concept. The framework prevents both extremes — ignoring costly debt and undertaking risky rewrites without proper preparation. Personal Practices That Compound Daily "When I sit down at my desk, the first thing I do is I pay a little tech debt. I'm looking at code, I'm about to change it, do I even understand it? Am I having some kind of resistance to it? Put in a little helpful comment, maybe a little refactoring." — Lou Franco Lou shares personal habits that create compounding improvements over time. Start each coding session by paying a small amount of tech debt in the area you're about to work — add a clarifying comment, extract a confusing variable, improve a function name. This warms you up, reduces friction for your actual work, and leaves the code slightly better than you found it. The clean-as-you-go philosophy means tech debt never accumulates faster than you can manage it. But Lou's most powerful practice comes at the end of each session: mutation testing by hand. Before finishing for the day, deliberately break something — change a plus to minus, a less-than to less-than-or-equal. See if tests catch it. Often they don't, revealing gaps in test coverage. The key insight: don't fix it immediately. Leave that failing test as the bridge to tomorrow's coding session. It connects today's momentum to tomorrow's work, ensuring you always start with context and purpose rather than cold-starting each day. Mutation Testing: Breaking Things on Purpose "Before I'm done working on a coding session, I break something on purpose. I'll change a plus to a minus, a less than to a less than equals, and see if tests break. A lot of times tests don't break. Now you've found a problem in your test." — Lou Franco Manual mutation testing — deliberately breaking code to verify tests catch the break — reveals a critical gap in most test suites. You can have 100% code coverage and still have untested behavior. A line of code that's executed during tests isn't necessarily tested — the test might not actually verify what that line does. By changing operators, flipping booleans, or altering constants, you discover whether your tests protect against actual logic errors or just exercise code paths. Lou recommends doing this manually as part of your daily practice, but automated tools exist for systematic discovery: and can mutate your entire codebase and report which mutations survive uncaught. This isn't just about test quality — it's about understanding what your code actually does and building confidence that changes won't introduce subtle bugs. Team-Level Practices: Budgets, Backlogs, and Target Architecture "Create a target architecture document — where would we be if we started over today? Every PR is an opportunity to move slightly toward that target." — Lou Franco At the team level, Lou advocates for three interconnected practices. First, create a target architecture document that describes where you'd be if starting fresh today — not a detailed design, but architectural patterns, technology choices, and structural principles that represent current best practices. This isn't a rewrite plan; it's a North Star. Every pull request becomes an opportunity to move incrementally toward that target when touching relevant code. Second, establish a budget split between PM-led feature work and engineering-led tech debt work — perhaps 80/20 or whatever ratio fits your product lifecycle stage. This creates predictable capacity for tech debt without requiring constant negotiation. Third, hold quarterly tech debt backlog meetings separate from sprint planning. Treat this backlog like PMs treat product discovery — explore options, estimate impacts, prioritize based on the 8 Questions framework. Some items fit in sprints; others require dedicated engineers for a quarter or two. This systematic approach prevents tech debt from being perpetually deprioritized while avoiding the opposite extreme of engineers disappearing into six-month "improvement" projects with no visible progress. The Atlassian Five-Alarm Fire "The Atlassian CTO's 'five-alarm fire' — stopping all feature development to focus on reliability. I reduced sync errors by 75% during that initiative." — Lou Franco Lou shares a powerful example of leadership-driven tech debt management at scale. The Atlassian CTO called a "five-alarm fire" — halting all feature development across the company to focus exclusively on reliability and tech debt. This wasn't panic; it was strategic recognition that accumulated debt threatened the business. Lou worked on reducing sync errors, achieving a 75% reduction during this focused period. The initiative demonstrated several leadership principles: willingness to make hard calls that stop revenue-generating feature work, clear communication of why reliability matters strategically, trust that teams will use the time wisely, and commitment to see it through despite pressure to resume features. This level of intervention is rare and shouldn't be frequent, but it shows what's possible when leadership truly prioritizes tech debt. More commonly, leaders should express product lifecycle constraints (startup urgency vs. mature product stability), give teams autonomy to find appropriate projects within those constraints, and require accountability through visible metrics and dashboards that show progress. The Rewrite Trap: Why Big Rewrites Usually Fail "A system that took 10 years to write has implicit knowledge that can't be replicated in 6 months. I'm mostly gonna advocate for piecemeal migrations along the way, reducing the size of the problem over time." — Lou Franco Lou lived through Trello's iOS navigation rewrite — a classic example of throwing away working code to start fresh, only to discover all the edge cases, implicit behaviors, and user expectations baked into the "old" system. A codebase that evolved over several years contains implicit knowledge — user workflows, edge case handling, performance optimizations, and subtle behaviors that users rely on even if they never explicitly requested them. Attempting to rewrite this in six months inevitably misses critical details. Lou strongly advocates for piecemeal migrations instead. The Trello "Decaffeinate Project" exemplifies this approach — migrating from CoffeeScript to TypeScript incrementally, with public dashboards showing the percentage remaining, interoperable technologies allowing gradual transition, and the ability to pause or reverse if needed. Keep both systems running in parallel during migrations. Use runtime observability to verify new code behaves identically to old code. Reduce the problem size steadily over months rather than attempting big-bang replacements. The only exception: sometimes keeping parallel systems requires scaffolding that creates its own complexity, so evaluate whether piecemeal migration is actually simpler or if you're better off living with the current system. Making Tech Debt Visible Through Dashboards "Put up a dashboard, showing it happen. Make invisible internal improvements visible through metrics engineering leadership understands." — Lou Franco One of tech debt's biggest challenges is invisibility — non-technical stakeholders can't see the improvement from refactoring or test coverage. Lou learned to make tech debt work visible through dashboards and metrics. The Decaffeinate Project tracked percentage of CoffeeScript files remaining, providing a clear progress indicator anyone could understand. When reducing sync errors, Lou created dashboards showing error rates declining over time. These visualizations serve multiple purposes: they demonstrate value to leadership, create accountability for engineering teams, build momentum as progress becomes visible, and help teams celebrate wins that would otherwise go unnoticed. The key is choosing metrics that matter to the business — error rates, page load times, deployment frequency, mean time to recovery — rather than pure code quality metrics like cyclomatic complexity that don't translate outside engineering. Connect tech debt work to customer experience, reliability, or developer productivity in ways leadership can see and value. Onboarding as a Tech Debt Opportunity "Unit testing is a really great way to learn a system. It's like an executable specification that's helping you prove that you understand the system." — Lou Franco Lou identifies onboarding as an underutilized opportunity for tech debt reduction. When new engineers join, they need to learn the codebase. Rather than just reading code or shadowing, Lou suggests having them write unit tests in areas they're learning. This serves dual purposes: tests are executable specifications that prove understanding of system behavior, and they create safety nets in areas that likely lack coverage (otherwise, why would new engineers be confused by the code?). The new engineer gets hands-on learning, the team gets better test coverage, and everyone wins. This practice also surfaces confusing code — if new engineers struggle to understand what to test, that's a signal the code needs clarifying comments, better naming, or refactoring. Make onboarding a systematic tech debt reduction opportunity rather than passive knowledge transfer. Leadership's Role: Constraints, Autonomy, and Accountability "Leadership needs to express the constraints. Tell the team what you're feeling about tech debt at a high level, and what you think generally is the appropriate amount of time to be spent on it. Then give them autonomy." — Lou Franco Lou distills leadership's role in tech debt management to three elements. First, express constraints — communicate where you believe the product is in its lifecycle (early startup, rapid growth, mature cash cow) and what that means for tech debt tolerance. Are we pursuing product-market fit where code might be thrown away? Are we scaling a proven product where reliability matters? Are we maintaining a stable system where operational efficiency pays dividends? These constraints help teams make appropriate trade-offs. Second, give autonomy — once constraints are clear, trust teams to identify specific tech debt projects that fit those constraints. Engineers understand the codebase's pain points better than leaders do. Third, require accountability — teams must make their work visible through dashboards, metrics, and regular updates. Autonomy without accountability becomes invisible engineering projects that might not deliver value. Accountability without autonomy becomes micromanagement that wastes engineering judgment. The balance creates space for teams to make smart decisions while keeping leadership informed and confident in the investment. AI and the Future of Tech Debt "I really do AI-assisted software engineering. And by that, I mean I 100% review every single line of that code. I write the tests, and all the code is as I would have written it, it's just a lot faster. Developers are still responsible for it. Read the code." — Lou Franco Lou has a chapter about AI in his book, addressing the elephant in the room: will AI-generated code create massive tech debt? His answer is nuanced. AI can accelerate development tremendously if used correctly — Lou uses it extensively but reviews every single line, writes all tests himself, and ensures the code matches what he would have written manually. The problem emerges with "vibe coders" — non-developers using AI to generate code they don't understand, creating unmaintainable messes that become someone else's problem. Developers remain responsible for all code, regardless of how it's generated. This means you must read and understand AI-generated code, not blindly accept it. Lou also raises supply chain security concerns — dependencies can contain malicious code, and AI might introduce vulnerabilities developers miss. His recommendation: stay six months behind on dependency updates, let others discover the problems first, and consider separate sandboxed development machines to limit security exposure. AI is a powerful tool, but it doesn't eliminate the need for engineering judgment, testing discipline, or code review practices. The Style Guide Beyond Formatting "Have a style guide that goes beyond formatting to include target architecture. This is the kind of code we want to write going forward." — Lou Franco Lou advocates for style guides that extend beyond tabs-versus-spaces formatting rules to include architectural guidance. Document patterns you want to move toward: how should components be structured, what state management approaches do we prefer, how should we handle errors, what testing patterns should we follow? This creates a shared understanding of the target architecture without requiring a massive design document. When reviewing pull requests, teams can reference the style guide to explain why certain approaches align with where the codebase is headed versus perpetuating old patterns. This makes tech debt conversations less personal and more objective — it's not about criticizing someone's code, it's about aligning with team standards and strategic direction. The style guide becomes a living document that evolves as the team learns and technology changes, capturing collective wisdom about what good code looks like in your specific context. Recommended Resources Some of the resources mentioned in this episode include: . And Geoffrey Moore’s , and . About Lou Franco Lou Franco is a veteran software engineer and author of Swimming in Tech Debt. With decades of experience at startups, as well as Trello, and Atlassian, he's seen both sides of debt—as coder and leader. Today, he advises teams on engineering practices, helping them turn messy codebases into momentum. You can link with and learn more at . /episode/index/show/scrummastertoolbox/id/39312635

The Agile Organization as a Learning System With Tom Gilb and Simon Holzapfel 12/12/2025

The Agile Organization as a Learning System With Tom Gilb and Simon Holzapfel BONUS: The Agile Organization as a Learning System Think Like a Farmer, Not a Factory Manager "Go slow to go fast. If you want to go somewhere, go together as a team. Take a farmer's mentality." Simon contrasts monoculture industrial thinking with the permaculture approach of Joel Salatin. Industrial approaches optimize for short-term efficiency but create fragile systems. Farmer thinking recognizes that healthy ecosystems require patience, diversity, and nurturing conditions for growth. The nervous system that's constantly stressed never builds much over time—think of the body, trust the body, let the body be a body. Value Masters, Not Scrum Masters "We need value masters, not Scrum Masters. Agile is a useful tool for delivering value, but value itself is primary. Everything else is secondary—Agile included." Tom makes his most provocative point: if you asked a top manager whether they'd prefer an agile person or value delivery, the answer is obvious. Agile is one tactic among many for delivering value—not even a necessary one. The shift required is from process mastery to value mastery, from Scrum Masters to people who understand and can deliver on critical stakeholder values. The DOVE Manifesto "I wrote a paper called DOVE—Deliver Optimum Values Efficiently. It's the manifesto focusing on delivering value, delivering value, delivering value." Tom offers his alternative to the Agile Manifesto: a set of principles laser-focused on value delivery. The document includes 10 principles on a single page that can guide any organization toward genuine impact. Everything else—processes, frameworks, methodologies—are secondary tools in service of this primary goal. . Building the Glue Between Social and Physical Technology "Value is created in interactions. That's where the social and physical technology meet—that joyous boundary where stuff gets done." Simon describes seeing the world through two lenses: physical technology (visible tools and systems) and social technology (culture, relationships, the air we breathe). Eric Beinhoeker's insight is that progress happens at the intersection. The Gilbian learning loops provide the structure; trust and human connection provide the fuel. Together, they create organizations that can actually learn and adapt. Further Reading To Support Your Learning Journey Resources & Further Reading Explore these curated resources to deepen your understanding of strategic planning, value-based management, and transformative organizational change. 📚 Essential Reading Tom Gilb's seminal book on requirements engineering and value-based development approaches. A critical analysis of the popular OKR framework and its limitations in measuring real value. Detailed exploration of the DOVE (Design Of Value Engineering) methodology for quantifying and optimizing stakeholder value. 🎓 Learning Materials A comprehensive collection of strategic planning principles and practical frameworks. Watch Tom Gilb discuss key strategic concepts and answer questions from the community. An in-depth look at value-driven design processes and their practical application. Exploring how organizational conversations shape thinking, decision-making, and change. 🧭 Frameworks & Models The Observe-Orient-Decide-Act decision cycle for rapid strategic thinking and adaptation. 🎯 Practical Tips Measurement of Increased Value Focus on tracking actual value delivery rather than activity completion. Establish baseline measurements and regularly assess improvements in stakeholder-defined value dimensions. Quantify Critical Values Identify the 3-5 most important value attributes for your stakeholders. Make these concrete and measurable, avoiding vague qualities in favor of specific, quantifiable metrics. Measurement vs Testing Process Understand the distinction: measurement tells you how much value exists, while testing validates whether something works. Use both strategically—test hypotheses early, then measure outcomes continuously. 🔗 Related Profiles Educational leadership and innovative approaches to value-based learning environments. About Tom Gilb and Simon Holzapfel Tom Gilb, born in the US, lived in London, and then moved to Norway in 1958. An independent teacher, consultant, and writer, he has worked in software engineering, corporate top management, and large-scale systems engineering. As the saying goes, Tom was writing about Agile before Agile was named. In 1976, Tom introduced the term "evolutionary" in his book Software Metrics, advocating for development in small, measurable steps. Today, we talk about Evo, the name Tom uses to describe his approach. Tom has worked with Dr. Deming and holds a certificate personally signed by him. . You can link with Simon Holzapfel is an educator, coach, and learning innovator who helps teams work with greater clarity, speed, and purpose. He specializes in separating strategy from tactics, enabling short-cycle decision-making and higher-value workflows. Simon has spent his career coaching individuals and teams to achieve performance with deeper meaning and joy. Simon is also the author of the . And you can listen to . You can link with . /episode/index/show/scrummastertoolbox/id/39312265

Quality 5.0—Quantifying the "Unmeasurable" With Tom Gilb and Simon Holzapfel 12/11/2025

Quality 5.0—Quantifying the "Unmeasurable" With Tom Gilb and Simon Holzapfel BONUS: Quality 5.0—Quantifying the "Unmeasurable" With Tom Gilb and Simon Holzapfel Clarification Before Quantification "Quantification is not the main idea. The key idea is clarification—so that the executive team understands each other." Tom emphasizes that measurement is a means to an end. The real goal is shared understanding. But quantification is a powerful clarification tactic because it forces precision. When someone says they want a "very fast car," asking "can we define a scale of measure?" immediately surfaces the vagueness. Miles per hour? Acceleration time? Top speed? Each choice defines what you're actually optimizing for. The Scale-Meter-Target Framework "First, define a scale of measure. Second, define the meter—the device for measuring. Third, set numbers: where are we now, what's the minimum to survive, and what does success look like?" Tom's framework makes the abstract concrete: Scale of measure: What dimension are you measuring? (e.g., time to complete task) Meter: How will you measure it? (e.g., user testing with stopwatch) Past/Status: Where are you now? (e.g., currently takes 47 seconds) Tolerable: What's the minimum acceptable? (e.g., must be under 30 seconds to survive) Target/Goal: What does success look like? (e.g., 15 seconds or less) Many important concepts like "usability" decompose into 10+ different scales of measure—you're not looking for one magic number but a set of relevant metrics. Trust as the Organizational Hormone "Change moves at the speed of trust. Once there's trust, information flows. Once information flows, the system comes to life and can learn. Until there's trust, you have the Soviet problem." Simon introduces trust as the "human growth hormone" of organizational change—it's fast, doesn't require a user's manual, and enables everything else. Low-trust environments hoard information, guaranteeing poor outcomes. The practical advice? Make your work visible to your manager, alignment-check first, do something, show results. Living the learning cycle yourself builds trust incrementally. And as Tom adds: if you deliver increased critical value every week, you will build trust. About Tom Gilb and Simon Holzapfel Tom Gilb, born in the US, lived in London, and then moved to Norway in 1958. An independent teacher, consultant, and writer, he has worked in software engineering, corporate top management, and large-scale systems engineering. As the saying goes, Tom was writing about Agile before Agile was named. In 1976, Tom introduced the term "evolutionary" in his book Software Metrics, advocating for development in small, measurable steps. Today, we talk about Evo, the name Tom uses to describe his approach. Tom has worked with Dr. Deming and holds a certificate personally signed by him. . You can link with Simon Holzapfel is an educator, coach, and learning innovator who helps teams work with greater clarity, speed, and purpose. He specializes in separating strategy from tactics, enabling short-cycle decision-making and higher-value workflows. Simon has spent his career coaching individuals and teams to achieve performance with deeper meaning and joy. Simon is also the author of the . And you can listen to . You can link with . /episode/index/show/scrummastertoolbox/id/39312230

Testing as Measurement—Why Bug-Hunting Misses the Point With Tom Gilb and Simon Holzapfel 12/10/2025

Testing as Measurement—Why Bug-Hunting Misses the Point With Tom Gilb and Simon Holzapfel BONUS: Testing as Measurement—Why Bug-Hunting Misses the Point With Tom Gilb and Simon Holzapfel The Revelation That Almost Caused a Car Crash "Tom said like 10 sentences in a row, kind of like a geometric proof, that just so blew my mind I almost drove off the road. I realized I had wasted hundreds of hours in boardrooms arguing about errors of which we were aware of perhaps 10%." Simon shares the moment Tom's framework clicked for him. The insight? Traditional testing—finding bugs and defects—is the wrong focus entirely. It's a programmer's view of the world. Managers don't care about bugs; they care about results, about improvements in their business. Tom calls this shift moving from "testing" to "measurement of enhanced or increased value at every cycle." The American Toast Problem "How do we make toast in America? We burn the toast, and then we pay someone to scrape off the black bits off the bread." Vasco invokes to describe traditional software testing. The entire testing-at-the-end approach is fundamentally wasteful. Instead, Tom advocates for continuous measurement against quantified values. If you expected 3% progress toward your goals this week and didn't get it, you've learned something critical: your strategy needs to change. If you did get it, keep going with confidence. Four Questions at Every Checkpoint "Where are we going? Where are we now? Where should we have been at this point? And why is there a gap?" Drawing from fighter pilot doctrine, these four questions should be asked at every micro-cycle—not just at quarterly reviews. Fighter pilots ask these questions every minute during critical missions, with clear abort criteria if answers are unacceptable. Most organizations have no abort criteria for their strategies at all, guaranteeing they'll discover failures far too late. About Tom Gilb and Simon Holzapfel Tom Gilb, born in the US, lived in London, and then moved to Norway in 1958. An independent teacher, consultant, and writer, he has worked in software engineering, corporate top management, and large-scale systems engineering. As the saying goes, Tom was writing about Agile before Agile was named. In 1976, Tom introduced the term "evolutionary" in his book Software Metrics, advocating for development in small, measurable steps. Today, we talk about Evo, the name Tom uses to describe his approach. Tom has worked with Dr. Deming and holds a certificate personally signed by him. . You can link with Simon Holzapfel is an educator, coach, and learning innovator who helps teams work with greater clarity, speed, and purpose. He specializes in separating strategy from tactics, enabling short-cycle decision-making and higher-value workflows. Simon has spent his career coaching individuals and teams to achieve performance with deeper meaning and joy. Simon is also the author of the . And you can listen to . You can link with . /episode/index/show/scrummastertoolbox/id/39312205

Continuous Strategy Engineering—Beyond Waterfall Planning With Tom Gilb and Simon Holzapfel 12/09/2025

Continuous Strategy Engineering—Beyond Waterfall Planning With Tom Gilb and Simon Holzapfel BONUS: Continuous Strategy Engineering—Beyond Waterfall Planning With Tom Gilb and Simon Holzapfel Strategy Professors Are Decades Behind "The professors of strategy have no clue as to what Evo is. They are locked in decades ago, waterfall mode." Tom's analysis is stark: the people teaching strategy in business schools haven't undergone the same agile transformation that software development experienced. They still think in terms of 5-year plans that get tested at the end—a guaranteed recipe for discovering failure too late. The alternative? Decompose any large strategy into weekly value delivery steps. And if you think that's impossible, ask any AI to do it for you—it will produce 52 reasonable weekly increments in about a minute. Why OKRs Aren't Enough for Complex Systems "If you're doing small-scale stuff that OKRs were designed for, like planning your personal work 14 days hence, OKRs are wonderful. If you're designing the air traffic control system for Europe, they're just too simple." Tom distinguishes between tools appropriate for personal productivity and those needed for complex organizational strategy. OKRs force some thinking, which is good, but they weren't designed for—and have never been adapted to—large-scale systems engineering. His paper "What is Wrong with OKRs?" documents roughly 100 gaps between simple OKRs and what robust value requirements actually require. . The Missing Alignment Layer "We have no mental model for most of leadership about how you actually align people around clear vision." Simon introduces the concept of a “sprinkler” system—imagine strategic clarity flowing from the top and misting over everyone's desk as alignment. Most organizations lack anything resembling this. They have Moses descending from expensive consultant retreats with tablets, but no continuous two-way flow of strategic information. The result? Teams work hard on things that don't matter while critical values go unaddressed. About Tom Gilb and Simon Holzapfel Tom Gilb, born in the US, lived in London, and then moved to Norway in 1958. An independent teacher, consultant, and writer, he has worked in software engineering, corporate top management, and large-scale systems engineering. As the saying goes, Tom was writing about Agile before Agile was named. In 1976, Tom introduced the term "evolutionary" in his book Software Metrics, advocating for development in small, measurable steps. Today, we talk about Evo, the name Tom uses to describe his approach. Tom has worked with Dr. Deming and holds a certificate personally signed by him. . You can link with Simon Holzapfel is an educator, coach, and learning innovator who helps teams work with greater clarity, speed, and purpose. He specializes in separating strategy from tactics, enabling short-cycle decision-making and higher-value workflows. Simon has spent his career coaching individuals and teams to achieve performance with deeper meaning and joy. Simon is also the author of the . And you can listen to . You can link with . /episode/index/show/scrummastertoolbox/id/39312145

Impact Engineering, Finding Agile's Lost North Star |Tom Gilb and Simon Holzapfel 12/08/2025

Impact Engineering, Finding Agile's Lost North Star |Tom Gilb and Simon Holzapfel BONUS: Impact Engineering—Finding Agile's Lost North Star With Tom Gilb and Simon Holzapfel The Clarity Problem: Why Organizations Start with "Fuzzy B*S*!" "Everybody seems to start from a position of fuzzy b*s*. Nice-sounding words. Management does it, professors do it, politicians do it. And they don't even feel very guilty about it." Tom Gilb doesn't mince words when describing how most organizations define their objectives. The fundamental problem isn't a lack of ambition—it's a lack of clarity. When leaders are asked about their critical values like "extremely high security" or "employee happiness," they typically respond with circular definitions that provide no actionable direction. Tom's approach starts by exposing this gap and then demonstrating that any value—no matter how "soft" or intangible it seems—can be quantified. Using AI tools, he's shown clients over 1,400 different ways to measure human happiness alone. Why Agile Lost Its North Star "Agile's lost its North Star because the economic problems it was trying to solve within the organization are now mismatched with the digital world." Simon Holzapfel offers a structural analysis: Agile developed primarily to allay the concerns of pre-digital capital—investors who needed reassurance that their money wouldn't disappear into failed projects. But today's digital economy operates differently. Capital now moves like a service (SaaS model), and innovation is fundamentally stochastic—you can't predict when breakthroughs will happen. Organizations using flow-focused tools when the real problem is value creation are applying yesterday's solutions to today's challenges. The First Step: Quantify Your Critical Values "If you ask AI to quantify employee happiness a hundred different ways, it will do it in one minute for free. So you can no longer be in denial." The path forward starts with brutal honesty about what your organization actually cares about. Tom's approach involves: Identifying the top 10 critical stakeholder values Defining clear scales of measure for each Establishing where you are now (status) Setting where you need to be to survive (tolerable level) Defining what success looks like (target/goal level) This isn't about adding bureaucracy—it's about creating shared clarity that enables everyone to row in the same direction. About Tom Gilb and Simon Holzapfel Tom Gilb, born in the US, lived in London, and then moved to Norway in 1958. An independent teacher, consultant, and writer, he has worked in software engineering, corporate top management, and large-scale systems engineering. As the saying goes, Tom was writing about Agile before Agile was named. In 1976, Tom introduced the term "evolutionary" in his book Software Metrics, advocating for development in small, measurable steps. Today, we talk about Evo, the name Tom uses to describe his approach. Tom has worked with Dr. Deming and holds a certificate personally signed by him. . You can link with Simon Holzapfel is an educator, coach, and learning innovator who helps teams work with greater clarity, speed, and purpose. He specializes in separating strategy from tactics, enabling short-cycle decision-making and higher-value workflows. Simon has spent his career coaching individuals and teams to achieve performance with deeper meaning and joy. Simon is also the author of the . And you can listen to . You can link with . /episode/index/show/scrummastertoolbox/id/39312125

Empathy and Availability Define Excellent Product Ownership | Scott Smith 12/05/2025

Empathy and Availability Define Excellent Product Ownership | Scott Smith Scott Smith: Empathy and Availability Define Excellent Product Ownership Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . The Great Product Owner: Always Present, Always Available, Always Curious "They are always present. They always make themselves available for team members that need them." - Scott Smith Scott is currently working with a Product Owner who exemplifies what great PO collaboration looks like. This person is always present—not just physically but mentally engaged with the team's work and challenges. They make themselves available for team members who need them, responding actively on the team chat and interacting consistently. What makes this PO stand out is their empathy and curiosity. Instead of being defensive when questions arise or challenges emerge, they lean into helping the team understand and solve problems. They show genuine curiosity about what the team is experiencing, asking questions and exploring solutions together rather than dictating answers. This PO understands that their role isn't to be the smartest person in the room but to be the most available, most collaborative, and most curious. The result is a team that feels supported and empowered, with clear direction and someone who genuinely helps them answer the hard questions. Scott's experience with this PO demonstrates that presence, availability, empathy, and curiosity are the foundations of great Product Owner work. Self-reflection Question: How present and available are you to your team, and do you approach their questions with curiosity or defensiveness? The Bad Product Owner: Never There When the Team Needs Direction "The PO was never present. The team had lack of clarity, and vision, and had no direction or someone who would help answer those questions." - Scott Smith Scott has also experienced the opposite extreme—a Product Owner who was never present. This absence created a cascade of problems for the team. Without regular access to the PO, the team lacked clarity about priorities, vision, and direction. They had questions that went unanswered and decisions that couldn't be made. The result was frustration and a team that couldn't move forward effectively. An absent PO creates a vacuum where uncertainty thrives. Teams end up making assumptions, second-guessing decisions, and feeling disconnected from the purpose of their work. The lack of someone who can help answer strategic questions or provide guidance means the team operates in the dark, building things without confidence that they're building the right things. Scott's experience highlights a fundamental truth about Product Ownership: presence isn't optional. Teams need a PO who shows up, engages, and stays connected to the work. Without that presence, even the most skilled team will struggle to deliver value because they can't align their efforts with the product vision and customer needs. Self-reflection Question: If your team were asked whether you're present and available as a Product Owner or Scrum Master, what would they say? [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Scott Smith Scott Smith is a 53-year-old professional based in Perth, Australia. He balances a successful career with a strong focus on health and fitness, currently preparing for bodybuilding competitions in 2026. With a background in leadership and coaching, Scott values growth, discipline, and staying relevant in a rapidly changing world. You can link with . /episode/index/show/scrummastertoolbox/id/39137510

Using MIRO to Build a Living Archive of Learning | Scott Smith 12/04/2025

Using MIRO to Build a Living Archive of Learning | Scott Smith Scott Smith: Using MIRO to Build a Living Archive of Learning Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "We're in a servant leadership role. So, ask: is the team thriving? That's a huge indication of success." - Scott Smith For Scott, success as a Scrum Master isn't measured by velocity charts or burn-down graphs—it's measured by whether the people are thriving. This includes everyone: the development team and the Product Owner. As a servant leader, Scott's focus is on creating conditions where teams can flourish, and he has practical ways to gauge that health. Scott does a light touch check on a regular basis and a deeper assessment quarterly. Mid-sprint, he conducts what he calls a "vibe" check—a quick pulse to understand how people are feeling and what they need. During quarterly planning, the team retrospects and celebrates achievements from the past quarter, keeping and tracking actions to ensure continuous improvement isn't just talked about but lived. Scott's approach recognizes that success is both about the work being done and the people doing it. When teams feel supported, heard, and valued, the work naturally flows better. This people-first perspective defines what great servant leadership looks like in practice. Self-reflection Question: How often do you check in on whether your team is truly thriving, and what specific indicators tell you they are? Featured Retrospective Format for the Week: MIRO as a Living History Museum "Use the multiple retros in the MIRO board as a shared history museum for the team." - Scott Smith Scott leverages not just as a tool for running retrospectives but as a living archive of team learning and growth. He uses templates to bring diversity to retrospective conversations, exploring the vast library of pre-built formats that offer themed and structured approaches to reflection. The magic happens when Scott treats each retrospective board not as a disposable artifact but as part of the team's shared history museum. Over time, the accumulation of retrospective boards tells the story of the team's journey—what they struggled with, what they celebrated, what actions they took, and how they evolved. This approach transforms retrospectives from isolated events into a continuous narrative of improvement. Teams can look back at previous retros to see patterns, track whether actions were completed, and recognize how far they've come. MIRO becomes both the canvas for current reflection and the archive of collective learning, making improvement visible and tangible across time. [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Scott Smith Scott Smith is a 53-year-old professional based in Perth, Australia. He balances a successful career with a strong focus on health and fitness, currently preparing for bodybuilding competitions in 2026. With a background in leadership and coaching, Scott values growth, discipline, and staying relevant in a rapidly changing world. You can link with . /episode/index/show/scrummastertoolbox/id/39137525

Building a Coaching Service Where Survey Scores Become Living Improvement | Scott Smith 12/03/2025

Building a Coaching Service Where Survey Scores Become Living Improvement | Scott Smith Scott Smith: Building a Coaching Service Where Survey Scores Become Living Improvement Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "Success is about feedback from coaching clients." - Scott Smith Scott is tackling one of the most challenging aspects of organizational transformation: turning annual survey results into continuous improvement. Working with a domain of about 30 people, Scott is exploring how to create a coaching service that doesn't just react to once-a-year data but actively drives ongoing growth. The typical pattern in many organizations is familiar—conduct an annual survey, review the scores, maybe have a few discussions, and then wait another year. Scott is experimenting with a different approach. He's setting up a coaching service that focuses on real-time feedback from the people being coached, making improvement a living practice rather than an annual event. The strategy starts with a pilot, testing the concept before scaling across the entire domain. Scott's measure of success is pragmatic and human-centered: feedback from coaching clients. Not abstract metrics or theoretical frameworks, but whether the people receiving coaching find value in what's being offered. This approach reflects a fundamental principle of Agile coaching—start small, experiment, gather feedback, and iterate based on what actually works for the people involved. Scott is building improvement infrastructure that puts continuous learning at the center, transforming how organizations think about growth from an annual checkbox into an ongoing conversation. Self-reflection Question: If you were to implement a coaching service in your organization, how would you measure its success beyond traditional survey scores? [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Scott Smith Scott Smith is a 53-year-old professional based in Perth, Australia. He balances a successful career with a strong focus on health and fitness, currently preparing for bodybuilding competitions in 2026. With a background in leadership and coaching, Scott values growth, discipline, and staying relevant in a rapidly changing world. You can link with . /episode/index/show/scrummastertoolbox/id/39137550

Why Great Scrum Masters Create Space for Breaks | Scott Smith 12/02/2025

Why Great Scrum Masters Create Space for Breaks | Scott Smith Scott Smith: Why Great Scrum Masters Create Space for Breaks Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "Think of the people involved. Put yourself in the shoes of the other." - Scott Smith Scott found himself in the middle of rising tension as voices escalated between the Product Owner and the development team. The PO was harsh, emotions were running high, and the conflict was intensifying with each exchange. In that moment, Scott knew he had to act. He stepped in with a simple but powerful reminder: "We're on the same team." That pause—that momentary break—allowed everyone to step back and reset. Both the PO and the team members later thanked Scott for his intervention, acknowledging they needed that space to cool down and refocus on their shared outcome. Scott's approach centers on empathy and perspective-taking. He emphasizes thinking about the people involved and putting yourself in their shoes. When tensions rise, sometimes the most valuable contribution a Scrum Master can make is creating space for a break, reminding everyone of the shared goal, and helping teams focus on the outcome rather than the conflict. It's not about taking sides—it's about serving the team by being the calm presence that brings everyone back to what matters most. Self-reflection Question: When you witness conflict between team members or between the team and Product Owner, do you tend to jump in immediately or create space for the parties to find common ground themselves? Featured Book of the Week: An Ex-Manager Who Believed "It was about having someone who believed in me." - Scott Smith Scott's most influential "book" isn't printed on pages—it's a person. After spending 10 years as a Business Analyst, Scott decided to take the Professional Scrum Master I (PSM I) course and look for a Scrum Master position. That transition wasn't just about skills or certification; it was about having an ex-manager who inspired him to chase his goals and truly believed in him. This person gave Scott the confidence to make a significant career pivot, demonstrating that sometimes the most powerful catalyst for growth is someone who sees your potential before you fully recognize it yourself. Scott's story reminds us that great leadership isn't just about managing tasks—it's about inspiring people to reach for goals they might not have pursued alone. The belief and encouragement of a single person can change the trajectory of someone's entire career. [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Scott Smith Scott Smith is a 53-year-old professional based in Perth, Australia. He balances a successful career with a strong focus on health and fitness, currently preparing for bodybuilding competitions in 2026. With a background in leadership and coaching, Scott values growth, discipline, and staying relevant in a rapidly changing world. You can link with . /episode/index/show/scrummastertoolbox/id/39137560

The Spotlight Failure That Taught a Silent Lesson About Recognition | Scott Smith 12/01/2025

The Spotlight Failure That Taught a Silent Lesson About Recognition | Scott Smith Scott Smith: The Spotlight Failure That Taught a Silent Lesson About Recognition Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: . "Not everybody enjoys the limelight and being called out, even for great work." - Scott Smith Scott was facilitating a multi-squad showcase with over 100 participants, and everything seemed to be going perfectly. Each squad had their five-minute slot to share achievements from the sprint, and Scott was coordinating the entire event. When one particular team member delivered what Scott considered fantastic work, he couldn't help but publicly recognize them during the introduction. It seemed like the perfect moment to celebrate excellence in front of the entire organization. But then his phone rang. The individual he had praised was unhappy—really unhappy. What Scott learned in that moment transformed his approach to recognition forever. The person was quiet, introverted, and conservative by nature. Being called out without prior notice or permission in front of 100+ people wasn't a reward—it was uncomfortable and unwelcome. Scott discovered that even positive recognition requires consent and awareness of individual preferences. Some people thrive in the spotlight, while others prefer their contributions to be acknowledged privately. The relationship continued well afterward, but the lesson stuck: check in with individuals before publicly recognizing them, understanding that great coaching means respecting how people want to be celebrated, not just that they should be celebrated. Self-reflection Question: How do you currently recognize team members' achievements, and have you asked each person how they prefer to be acknowledged for their contributions? [The Scrum Master Toolbox Podcast Recommends] 🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥 Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people. 🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue. [The Scrum Master Toolbox Podcast Recommends] About Scott Smith Scott Smith is a 53-year-old professional based in Perth, Australia. He balances a successful career with a strong focus on health and fitness, currently preparing for bodybuilding competitions in 2026. With a background in leadership and coaching, Scott values growth, discipline, and staying relevant in a rapidly changing world. You can link with . /episode/index/show/scrummastertoolbox/id/39137580

BONUS: When AI Knows Your Emotional Triggers Better Than You Do — Navigating Mindfulness in the AI Age | Mo Edjlali 11/29/2025

BONUS: When AI Knows Your Emotional Triggers Better Than You Do — Navigating Mindfulness in the AI Age | Mo Edjlali BONUS: When AI Knows Your Emotional Triggers Better Than You Do — Navigating Mindfulness in the AI Age In this thought-provoking conversation, former computer engineer and mindfulness leader explores how AI is reshaping human meaning, attention, and decision-making. We examine the critical question: what happens when AI knows your emotional triggers better than you know yourself? Mo shares insights on remaining sovereign over our attention, avoiding dependency in both mindfulness and technology, and preparing for a world where AI may outperform us in nearly every domain. From Technology Pioneer to Mindfulness Leader "I've been very heavily influenced by technology, computer engineering, software development. I introduced DevOps to the federal government. But I have never seen anything change the way in which human beings work together like Agile." — Mo Edjlali Mo's journey began in the tech world — graduating in 1998, he was on the front line of the internet explosion. He remembers the days before the internet, watched online multiplayer games emerge in 1994, and worked on some of the most complicated tech projects in federal government. Technology felt almost like magic, advancing at a logarithmic rate faster than anything else. But when Mo discovered mindfulness practices 12-15 years ago, he found something equally transformative: actual exercises to develop emotional intelligence and soft skills that the tech world talked about but never taught. Mindfulness provided logical, practical methods that didn't require "woo-woo" beliefs — just practice that fundamentally changed his relationship with his mind. This dual perspective — tech innovator and mindfulness teacher — gives Mo a unique lens for understanding where we're headed. The Shift from Liberation to Dependency "I was fortunate enough, the teachers I was exposed to, the mentality was very much: you're gonna learn how to meditate on your own, in silence. There is no guru. There is no cult of personality." — Mo Edjlali Mo identifies a dangerous drift in the mindfulness movement: from teaching independence to creating dependency. His early training, particularly a Vipassana retreat led by , modeled true liberation — you show up for 10 days, pay nothing, receive food and lodging, learn to meditate, then donate what you can at the end. Critically, you leave being able to meditate on your own without worshiping a teacher or subscribing to guided meditations. But today's commercialized mindfulness often creates the opposite: powerful figures leading fiefdoms, consumers taught to listen to guided meditations rather than meditate independently. This dependency model mirrors exactly what's happening with AI — systems designed to make us rely on them rather than empower our own capabilities. Recognizing this parallel is essential for navigating both fields wisely. AI as a New Human Age, Not Just Another Tool "With AI, this is different. This isn't like mobile computing, this isn't like the internet. We're entering a new age. We had the Bronze Age, the Iron Age, the Industrial Age. When you enter a new age, it's almost like knocking the chess board over, flipping the pieces upside down. We're playing a new game." — Mo Edjlali Mo frames AI not as another technology upgrade but as the beginning of an entirely new human age. In a new age, everything shifts: currency, economies, government, technology, even religions. The documentary about the Bronze Age collapse taught him that when ages turn over, the old rules no longer apply. This perspective explains why AI feels fundamentally different from previous innovations. ChatGPT 2.0 was interesting; ChatGPT 3 blew Mo's mind and made him realize we're witnessing something unprecedented. While he's optimistic about the potential for sustainable abundance and extraordinary breakthroughs, he's also aware we're entering both the most exciting and most frightening time to be alive. Everything we learned in high school might be proven wrong as AI rewrites human knowledge, translates animal languages, extends longevity, and achieves things we can't even imagine. The Mental Health Tsunami and Loss of Purpose "If we do enter the age of abundance, where AI could do anything that human beings could do and do it better, suddenly the system we have set up — where our purpose is often tied to our income and our job — suddenly, we don't need to work. So what is our purpose?" — Mo Edjlali Mo offers a provocative vision of the future: a world where people might pay for jobs rather than get paid to work. It sounds crazy until you realize it's already happening — people pay $100,000-$200,000 for college just to get a job, politicians spend millions to get elected. If AI handles most work and we enter an age of abundance, jobs won't be about survival or income — they'll be about meaning, identity, and social connection. This creates three major crises Mo sees accelerating: attacks on our focus and attention (technology hijacking our awareness), polarization (forcing black-and-white thinking), and isolation (pushing us toward solo experiences). The mental health tsunami is coming as people struggle to find purpose in a world where AI outperforms them in domain after domain. The jobs will change, the value systems will shift, and those without tools for navigating this transformation will suffer most. When AI Reads Your Mind "Researchers at Duke University had hooked up fMRI brain scanning technology and took that data and fed it into GPT 2. They were able to translate brain signals into written narrative. So the implications are that we could read people's minds using AI." — Mo Edjlali The future Mo describes isn't science fiction — it's already beginning. Three years ago, researchers used early GPT to translate brain signals into written text by scanning people's minds with fMRI and training AI on the patterns. Today, AI knows a lot about heavy users like Mo through chat conversations. Tomorrow, AI will have video input of everything we see, sensory input from our biometrics (pulse, heart rate, health indicators), and potentially direct connection to our minds. This symbiotic relationship is coming whether we're ready or not. Mo demonstrates this with a personal experiment: he asked his AI to tell him about himself, describe his personality, identify his strengths, and most powerfully — reveal his blind spots. The AI's response was outstanding, better than what any human (even his therapist or himself) could have articulated. This is the reality we're moving toward: AI that knows our emotional triggers, blind spots, and patterns better than we do ourselves. Using AI as a Mirror for Self-Discovery "I asked my AI, 'What are my blind spots?' Human beings usually won't always tell you what your blind spots are, they might not see them. A therapist might not exactly see them. But the AI has... I've had the most intimate kind of conversations about everything. And the response was outstanding." — Mo Edjlali Mo's approach to AI is both pragmatic and experimental. He uses it extensively — at the level of teenagers and early college students who are on it all the time. But rather than just using AI as a tool, he treats it as a mirror for understanding himself. Asking AI to identify your blind spots is a powerful exercise because AI has observed all your conversations, patterns, and tendencies without the human limitations of forgetfulness or social politeness. Vasco shares a similar experience using AI as a therapy companion — not replacing his human therapist, but preparing for sessions and processing afterward. This reveals an essential truth: most of us don't understand ourselves that well. We're blind navigators using an increasingly powerful tool. The question isn't whether AI will know us better than we know ourselves — that's already happening. The question is how we use that knowledge wisely. The Danger of AI Hijacking Our Agency "There's this real danger. I saw that South Park episode about ChatGPT where his wife is like, 'Come on, put the AI down, talk to me,' and he's got this crazy business idea, and the AI keeps encouraging him along. It's a point where he's relying way too heavily on the AI and making really poor decisions." — Mo Edjlali Not all AI use is beneficial. Mo candidly admits his own mistakes — sometimes leaning into AI feedback over his actual users' feedback for his Meditate Together app because "I like what the AI is saying." , where the character's AI encourages increasingly poor decisions while his relationships suffer. Social media demonstrates this danger at scale: AI algorithms tuned to steal our attention and hijack our agency, preventing us from thinking about what truly matters — relationships and human connection. Mo shares a disturbing story about Zoom bombers disrupting Meditate Together sessions, filming it, posting it on YouTube where it got 90,000 views, with comments thanking the disruptors for "making my day better." Technology created a cannibalistic dynamic where teenagers watched videos of their mothers, aunts, and grandmothers being harassed during meditation. When Mo tried to contact Google, the company's incentive structure prioritized views and revenue over human decency. Technology combined with capitalism creates these dangerous momentum toward monetizing attention at any cost. Remaining Sovereign Over Your Attention "Traditionally, mindfulness does an extraordinary job, if you practice right, to help you regain your agency of your focus and concentration. It takes practice. But reading is now becoming a concentration practice. It's an actual practice." — Mo Edjlali Mo identifies three major symptoms affecting us: attacks on focus/attention, polarization into black-and-white thinking, and isolation. Mindfulness practices directly counter all three — but only if practiced correctly. Training attention, focus, and concentration requires actual practice, not just listening to guided meditations. Mo offers practical strategies: reading as concentration practice (asking "does anyone read anymore?" recognizing that sustained reading now requires deliberate effort), turning off AirPods while jogging or driving to find silence, spending time alone with your thoughts, and recognizing that we were given extraordinary power (smartphones) with zero training on how to be aware of it. Older generations remember having to rewind VHS tapes — forced moments of patience and stillness that no longer exist. We need to deliberately recreate those spaces where we're not constantly consuming entertainment and input. Dialectic Thinking: Beyond Polarization "I saw someone the other day wear a shirt that said, 'I'm perfect the way I am.' That's one-dimensional thinking. Two-dimensional thinking is: you're perfect the way that you are, and you could be a little better." — Mo Edjlali Mo's book OpenMBSR specifically addresses polarization by introducing dialectic thinking — the ability to hold paradoxes and seeming contradictions simultaneously. Social media and algorithms push us toward one-dimensional, black-and-white thinking: good/bad, right/wrong, with me/against me. But reality is far more nuanced. The ability to think "I'm perfect as I am AND I can improve" or "AI is extraordinary AND dangerous" is essential for navigating complexity. This mirrors the tech world's embrace of continuous improvement in Agile — accepting where you are while always pushing for better. Chess players learned this years ago when AI defeated humans — they didn't freak out, they accepted it and adapted. Now AI in chess doesn't just give answers; it helps humans understand how it arrived at those answers. This partnership model, where AI coaches us through complexity rather than simply replacing us, represents the healthiest path forward. Building Community, Not Dependency "When people think to meditate, unfortunately, they think, I have to do this by myself and listen to guided meditation. I'm saying no. Do it in silence. If you listen to guided meditation, listen to guided meditation that teaches you how to meditate in silence. And do it with other people, with intentional community." — Mo Edjlali Mo's OpenMBSR initiative explicitly borrows from the Agile movement's success: grassroots, community-centric, open source, transparent. Rather than creating fiefdoms around cult personalities, he wants mindfulness to spread organically through communities helping communities. This directly counters the isolation trend that technology accelerates. Meditate Together exists specifically to create spaces where people meditate with other human beings around the world, with volunteer hosts holding sessions. The model isn't about dependency on a teacher or platform — it's about building connection and shared practice. This aligns perfectly with how the tech world revolutionized collaborative work through Agile and Scrum: transparent, iterative, valuing individuals and interactions. The question for both mindfulness and AI adoption is whether we'll create systems that empower independence and community, or ones that foster dependency and isolation. Preparing for a World Where AI Outperforms Humans "AI is going to need to kind of coach us and ease us into it, right? There's some really dark, ugly things about ourselves that could be jarring without it being properly shared, exposed, and explained." — Mo Edjlali Looking at his children, Mo wonders what tools they'll need in a world where AI may outperform humans in nearly every domain. The answer isn't trying to compete with AI in calculation, memory, or analysis — that battle is already lost. Instead, the essential human skills become self-awareness, emotional intelligence, dialectic thinking, community building, and maintaining agency over attention and decision-making. AI will need to become a coach, helping humans understand not just answers but how it arrived at those answers. This requires AI development that prioritizes human growth over profit maximization. It also requires humans willing to do the hard work of understanding themselves — confronting blind spots, managing emotional triggers, practicing concentration, and building genuine relationships. The mental health tsunami Mo predicts isn't inevitable if we prepare now by teaching these skills widely, building community-centric systems, and designing AI that empowers rather than replaces human wisdom and connection. About Mo Edjlali Mo Edjlali is a former computer engineer, and also the founder and CEO of Mindful Leader, the world's largest provider of Mindfulness-Based Stress Reduction training. Mo's new book Open MBSR: Reimagining the Future of Mindfulness explores how ancient practices can help us navigate the AI revolution with awareness and resilience. You can learn more about Mo and his work at , check out , and read his articles on and . /episode/index/show/scrummastertoolbox/id/39095805

AI Assisted Coding: Building Reliable Software with Unreliable AI Tools With Lada Kesseler 11/28/2025

AI Assisted Coding: Building Reliable Software with Unreliable AI Tools With Lada Kesseler AI Assisted Coding: Building Reliable Software with Unreliable AI Tools In this special episode, Lada Kesseler shares her journey from AI skeptic to pioneer in AI-assisted development. She explores the spectrum from careful, test-driven development to quick AI-driven experimentation, revealing practical patterns, anti-patterns, and the critical role of judgment in modern software engineering. From Skeptic to Pioneer: Lada's AI Coding Journey "I got a new skill for free!" Lada's transformation began when she discovered Anthropic’s Claude Projects. Despite being skeptical about AI tools throughout 2023, she found herself learning Angular frontend development with AI—a technology she had no prior experience with. This breakthrough moment revealed something profound: AI could serve as an extension of her existing development skills, enabling her to acquire new capabilities without the traditional learning curve. The journey evolved through and , each tool expanding her understanding of what's possible when developers collaborate with AI. Understanding Vibecoding vs. AI-Assisted Development "AI assisted coding requires judgment, and it's never been as important to exercise judgment as now." Lada introduces the concept of "vibecoding" as one extreme on a new dimension in software development—the spectrum from careful, test-driven development to quick, AI-driven experimentation. The key insight isn't that one approach is superior, but that developers must exercise judgment about which approach fits their context. She warns against careless AI coding for production systems: "You just talk to a computer, you say, do this, do that. You don't really care about code... For some systems, that's fine. When the problem arises is when you put the stuff to production and you really care about your customers. Please, please don't do that." This wisdom highlights that with great power comes great responsibility—AI accelerates both good and bad practices. The Answer Injection Anti-Pattern When Working With AI "You're limiting yourself without knowing, you're limiting yourself just by how you formulate your questions. And it's so hard to detect." One of Lada's most important discoveries is the "answer injection" anti-pattern—when developers unconsciously constrain AI's responses by how they frame their questions. She experienced this firsthand when she asked an AI about implementing a feature using a specific approach, only to realize later that she had prevented the AI from suggesting better alternatives. The solution? Learning to ask questions more openly and reformulating problems to avoid self-imposed limitations. As she puts it, "Learn to ask the right way. This is one of the powers this year that's been kind of super cool." This skill of question formulation has become as critical as any technical capability. Answer injection is when we—sometimes, unknowingly—ask a leading question that also injects a possible answer. It’s an anti-pattern because LLM’s have access to far more information than we do. Lada’s advice: “just ask for anything you need”, the LLM might have a possible answer for you. Never Trust a Single LLM: Multi-Agent Collaboration "Never trust the output of a single LLM. When you ask it to develop a feature, and then you ask the same thing to look at that feature, understand the code, find the issues with it—it suddenly finds improvements." Lada shares her experiments with —using multiple AI instances that collaborate and cross-check each other's work. She created specialized agents (architect, developer, tester) and even built systems using and to make different AI instances communicate with each other. This approach revealed a powerful pattern: AI reviewing AI often catches issues that a single instance would miss. The practical takeaway is simple but profound—always have one AI instance review another's work, treating AI output with the same healthy skepticism you'd apply to any code review. Code Quality Matters MORE with AI "This thing is a monkey, and if you put it in a good codebase, like any developer, it's gonna replicate what it sees. So it behaves much better in the better codebase, so refactor!" Lada emphasizes that code quality becomes even more critical when working with AI. Her systems "work silently" and "don't make a lot of noise, because they don't break"—a result of maintaining high standards even when AI makes rapid development tempting. She uses a memorable metaphor: AI is like a monkey that replicates what it sees. Put it in a clean, well-structured codebase, and it produces clean code. Put it in a mess, and it amplifies that mess. This insight transforms refactoring from a nice-to-have into a strategic necessity—good architecture and clean code directly improve AI's ability to contribute effectively. Managing Complexity: The Open Question "If I just let it do things, it'll just run itself to the wall at crazy speeds, because it's really good at running. So I have to be there managing complexity for it." One of the most honest insights Lada shares is the current limitation of AI: complexity management. While AI excels at implementing features quickly, it struggles to manage the growing complexity of systems over time. Lada finds herself acting as the complexity manager, making architectural decisions and keeping the system maintainable while AI handles implementation details. She poses a critical question for the future: "Can it manage complexity? Can we teach it to manage complexity? I don't know the answer to that." This honest assessment reminds us that fundamental software engineering skills—architecture, refactoring, testing—remain as vital as ever. Context is Everything: Highway vs. Parking Lot "You need to be attuned to the environment. You can go faster or slow, and sometimes going slow is bad, because if you're on a highway, you're gonna get hurt." Lada introduces a powerful metaphor for choosing development speed: highway versus parking lot. When learning or experimenting with non-critical systems, you can go fast, don't worry about perfection, and leverage AI's speed fully. But when building production systems where reliability matters, different rules apply. The key is matching your development approach to the risk level and context. She emphasizes safety nets: "In one project, we used AI, and we didn't pay attention to the code, as it wasn't important, because at any point, we could actually step back and refactor. We were not unsafe." This perspective helps developers make better judgment calls about when to accelerate and when to slow down. The Era of Discovery: We've Only Just Begun "We haven't even touched the possibilities of what is there out there right now. We're in the era of gentleman scientists—newbies can make big discoveries right now, because nobody knows what AI really is capable of." Perhaps most exciting is Lada's perspective on where we stand in the AI-assisted development journey: we're at the very beginning. Even the creators of these tools are figuring things out as they go. This creates unprecedented opportunities for practitioners at all levels to experiment, discover patterns, and share learnings with the community. Lada has documented her discoveries in an interactive patterns and anti-patterns website, a presentation, and her Substack blog—contributing to the collective knowledge base that's being built in real-time. Resources For Further Study Video of Lada's talk: Lada’s Patterns and Anti-patterns website: Lada’s Substack AI Assisted Coding episode with Dawid Dahl About Lada Kesseler Lada Kesseler is a passionate software developer specializing in the design of scalable, robust software systems. With a focus on best development practices, she builds applications that are easy to maintain, adapt, and support. Lada combines technical expertise with a keen eye for clean architecture and sustainable code, driving innovation in modern software engineering. Currently exploring how these values translate to AI-assisted development and figuring out what it takes to build reliable software with unreliable tools. You can link with . /episode/index/show/scrummastertoolbox/id/39080275

AI Assisted Coding: Transactional AI Development - Commit, Validate, and Rollback With Sergey Sergyenko 11/27/2025

AI Assisted Coding: Transactional AI Development - Commit, Validate, and Rollback With Sergey Sergyenko AI Assisted Coding: Treating AI Like a Junior Engineer - Onboarding Practices for AI Collaboration In this special episode, Sergey Sergyenko, CEO of , shares his practical framework for AI-assisted development built on transactional models, Git workflows, and architectural conventions. He explains why treating AI like a junior engineer, keeping commits atomic, and maintaining rollback strategies creates production-ready code rather than just prototypes. Vibecoding: An Automation Design Instrument "I would define as an automation design instrument. It's not a tool that can deliver end-to-end solution, but it's like a perfect set of helping hands for a person who knows what they need to do." Sergey positions vibecoding clearly: it's not magic, it's an automation design tool. The person using it must know what they need to accomplish—AI provides the helping hands to execute that vision faster. This framing sets expectations appropriately: AI speeds up development significantly, but it's not a silver bullet that works without guidance. The more you practice vibecoding, the better you understand its boundaries. Sergey's definition places vibecoding in the evolution of development tools: from scaffolding to co-pilots to agentic coding to vibecoding. Each step increases automation, but the human architect remains essential for providing direction, context, and validation. Pair Programming with the Machine "If you treat AI as a junior engineer, it's very easy to adopt it. Ah, okay, maybe we just use the old traditions, how we onboard juniors to the team, and let AI follow this step." One of Sergey's most practical insights is treating AI like a junior engineer joining your team. This mental model immediately clarifies roles and expectations. You wouldn't let a junior architect your system or write all your tests—so why let AI? Instead, apply existing onboarding practices: pair programming, code reviews, test-driven development, architectural guidance. This approach leverages Extreme Programming practices that have worked for decades. The junior engineer analogy helps teams understand that AI needs mentorship, clear requirements, and frequent validation. Just as you'd provide a junior with frameworks and conventions to follow, you constrain AI with established architectural patterns and framework conventions like Ruby on Rails. The Transactional Model: Atomic Commits and Rollback "When you're working with AI, the more atomic commits it delivers, more easy for you to kind of guide and navigate it through the process of development." Sergey's transactional approach transforms how developers work with AI. Instead of iterating endlessly when something goes wrong, commit frequently with atomic changes, then rollback and restart if validation fails. Each commit should be small, independent, and complete—like a feature flag you can toggle. The commit message includes the prompt sequence used to generate the code and rollback instructions. This approach makes the Git repository the context manager, not just the AI's memory. When you need to guide AI, you can reference specific commits and their context. This mirrors trunk-based development practices where teams commit directly to master with small, verified changes. The cost of rollback stays minimal because changes are atomic, making this strategy far more efficient than trying to fix broken implementations through iteration. Context Management: The Weak Point and the Solution "Managing context and keeping context is one of the weak points of today's coding agents, therefore we need to be very mindful in how we manage that context for the agent." Context management challenges current AI coding tools—they forget, lose thread, or misinterpret requirements over long sessions. Sergey's solution is embedding context within the commit history itself. Each commit links back to the specific reasoning behind that code: why it was accepted, what iterations it took, and how to undo it if needed. This creates a persistent context trail that survives beyond individual AI sessions. When starting new features, developers can reference previous commits and their context to guide the AI. The transactional model doesn't just provide rollback capability—it creates institutional memory that makes AI progressively more effective as the codebase grows. TDD 2.0: Humans Write Tests, AI Writes Code "I would never allow AI to write the test. I would do it by myself. Still, it can write the code." Sergey is adamant about roles: humans write tests, AI writes implementation code. This inverts traditional TDD slightly—instead of developers writing tests then code, they write tests and AI writes the code to pass them. Tests become executable requirements and prompts. This provides essential guardrails: AI can iterate on implementation until tests pass, but it can't redefine what "passing" means. The tests represent domain knowledge, business requirements, and validation criteria that only humans should control. Sergey envisions multi-agent systems where one agent writes code while another validates with tests, but critically, humans author the original test suite. () creates a verification mechanism that prevents the biggest anti-pattern: coding without proper validation. The Two Cardinal Rules: Architecture and Verification "I would never allow AI to invent architecture. Writing AI agentic coding, Vibecoding, whatever coding—without proper verification and properly setting expectations of what you want to get as a result—that's the main mistake." Sergey identifies two non-negotiables. First, never let AI invent architecture. Use framework conventions (Rails, etc.) to constrain AI's choices. Leverage existing code generators and scaffolding. Provide explicit architectural guidelines in planning steps. Store iteration-specific instructions where AI can reference them. The framework becomes the guardrails that prevent AI from making structural decisions it's not equipped to make. Second, always verify AI output. Even if you don't want to look at code, you must validate that it meets requirements. This might be through tests, manual review, or automated checks—but skipping verification is the fundamental mistake. These two rules—human-defined architecture and mandatory verification—separate successful AI-assisted development from technical debt generation. Prototype vs. Production: Two Different Workflows "When you pair as an architect or a really senior engineer who can implement it by himself, but just wants to save time, you do the pair programming with AI, and the AI kind of ships a draft, and rapid prototype." Sergey distinguishes clearly between prototype and production development. For MVPs and rapid prototypes, a senior architect pairs with AI to create drafts quickly—this is where speed matters most. For production code, teams add more iterative testing and polishing after AI generates initial implementation. The key is being explicit about which mode you're in. The biggest anti-pattern is treating prototype code as production-ready without the necessary validation and hardening steps. When building production systems, Sergey applies the full transactional model: atomic commits, comprehensive tests, architectural constraints, and rollback strategies. For prototypes, speed takes priority, but the architectural knowledge still comes from humans, not AI. The Future: AI Literacy as Mandatory "Being a software engineer and trying to get a new job, it's gonna be a mandatory requirement for you to understand how to use AI for coding. So it's not enough to just be a good engineer." Sergey sees AI-assisted coding literacy becoming as fundamental as Git proficiency. Future engineering jobs will require demonstrating effective AI collaboration, not just traditional coding skills. We're reaching good performance levels with AI models—now the challenge is learning to use them efficiently. This means frameworks and standardized patterns for AI-assisted development will emerge and consolidate. Approaches like , , and others represent early attempts to create these patterns. Sergey expects architectural patterns for AI-assisted development to standardize, similar to how design patterns emerged in object-oriented programming. The human remains the bottleneck—for domain knowledge, business requirements, and architectural guidance—but the implementation mechanics shift heavily toward AI collaboration. Resources for Practitioners "We are reaching a good performance level of AI models, and now we need to guide it to make it impactful. It's a great tool, now we need to understand how to make it impactful." Sergey recommends particularly valuable for Ruby and Rails developers but applicable broadly. He references and emphasizes practices as foundational. The tools he uses— and —support custom planning steps and context management. But more important than tools is the mindset: we have powerful AI capabilities now, and the focus must shift to efficient usage patterns. This means experimenting with workflows, documenting what works, and sharing patterns with the community. Sergey himself shares case studies on LinkedIn and travels extensively speaking about these approaches, contributing to the collective learning happening in real-time. About Sergey Sergyenko Sergey is the CEO of Cybergizer, a dynamic software development agency with offices in Vilnius, Lithuania. Specializing in MVPs with zero cash requirements, Cybergizer offers top-tier CTO services and startup teams. Their tech stack includes Ruby, Rails, Elixir, and ReactJS. Sergey was also a featured speaker at the , and you can find his talk available in your membership area. If you are not a member don't worry, You can link with . /episode/index/show/scrummastertoolbox/id/39080150

AI Assisted Coding: Augmented AI Development - Software Engineering First, AI Second With Dawid Dahl 11/26/2025

AI Assisted Coding: Augmented AI Development - Software Engineering First, AI Second With Dawid Dahl BONUS: Augmented AI Development - Software Engineering First, AI Second In this special episode, Dawid Dahl introduces —a disciplined approach where professional developers augment their capabilities with AI while maintaining full architectural control. He explains why starting with software engineering fundamentals and adding AI where appropriate is the opposite of most frameworks, and why this approach produces production-grade software rather than technical debt. The AAID Philosophy: Don't Abandon Your Brain "Two of the fundamental developer principles for AAID are: first, don't abandon your brain. And the second is incremental steps." Dawid's Augmented AI Development framework stands in stark contrast to ""—which he defines strictly as not caring about code at all, only results on screen. AAID is explicitly designed for professional developers who maintain full understanding and control of their systems. The framework is positioned on the furthest end of the spectrum from vibe coding, requiring developers to know their craft deeply. The two core principles—don't abandon your brain, work incrementally—reflect a philosophy that AI is a powerful collaborator, not a replacement for thinking. This approach recognizes that while 96% of Dawid's code is now written by AI, he remains the architect, constantly steering and verifying every step. In this segment we refer to and . Software Engineering First, AI Second: A Hill to Die On "You should start with software engineering wisdom, and then only add AI where it's actually appropriate. I think this is super, super important, and the entire foundation of this framework. This is a hill I will personally die on." What makes AAID fundamentally different from other AI-assisted development frameworks is its starting point. Most frameworks start with AI capabilities and try to add structure and best practices afterward. Dawid argues this is completely backwards. AAID begins with 50-60 years of proven software engineering wisdom—test-driven development, behavior-driven development, continuous delivery—and only then adds AI where it enhances the process. This isn't a minor philosophical difference; it's the foundation of producing maintainable, production-grade software. Dawid admits he's sometimes "manipulating developers to start using good, normal software engineering practices, but in this shiny AI box that feels very exciting and new." If the AI wrapper helps developers finally adopt and , he's fine with that. Why TDD is Non-Negotiable with AI "Every time I prompt an AI and it writes code for me, there is often at least one or two or three mistakes that will cause catastrophic mistakes down the line and make the software impossible to change." Test-driven development isn't just a nice-to-have in AAID—it's essential. Dawid has observed that AI consistently makes 2-3 mistakes per prompt that could have catastrophic consequences later. Without TDD's red-green-refactor cycle, these errors accumulate, making code increasingly difficult to change. TDD answers the question "Is my code technically correct?" while acceptance tests answer "Is the system releasable?" Both are needed for production-grade software. The refactor step is where 50-60 years of software engineering wisdom gets applied to make code maintainable. This matters because AAID isn't vibe coding—developers care deeply about code quality, not just visible results. Good software, as Dave Farley says, is software that's easy to change. Without TDD, AI-generated code becomes a maintenance nightmare. The Problem with "Prompt and Pray" Autonomous Agents "When I hear 'our AI can now code for over 30 hours straight without stopping,' I get very afraid. You fall asleep, and the next morning, the code is done. Maybe the tests are green. But what has it done in there? Imagine everything it does for 30 hours. This system will not work." Dawid sees two diverging paths for AI-assisted development's future. The first—autonomous agents working for hours or days without supervision—terrifies him. The marketing pitch sounds appealing: prompt the AI, go to sleep, wake up to completed features. But the reality is technical debt accumulation at scale. Imagine all the decisions, all the architectural choices, all the mistakes an AI makes over 30 hours of autonomous work. Dawid advocates for the stark contrast: working in extremely small increments with constant human steering, always aligned to specifications. His vision of the future isn't AI working alone—it's voice-controlled confirmations where he says "Yes, yes, no, yes" as AI proposes each tiny change. This aligns with metrics showing that high-performing teams work in small batches with fast feedback loops. Prerequisites: Product Discovery Must Come First "Without Dave Farley, this framework would be totally different. I think he does everything right, basically. With this framework, I want to stand on the shoulders of giants and work on top of what has already been done." AAID explicitly requires product discovery and specification phases before AI-assisted coding begins. This is based on Dave Farley's product journey model, which shows how products move from idea to production. AAID starts at the "executable specifications" stage—it requires input specifications from prior discovery work. This separates specification creation (which Dawid is addressing in a separate "Dream Encoder" framework) from code execution. The prerequisite isn't arbitrary; it acknowledges that AI-assisted implementation works best when the problem is well-defined. This "standing on shoulders of giants" approach means AAID doesn't try to reinvent software engineering—it leverages decades of proven practices from TDD pioneers, BDD creators, and continuous delivery experts. What's Wrong with Other AI Frameworks "When the AI decides to check the box [in task lists], that means this is the definition of done. But how is the AI taking that decision? It's totally ad hoc. It's like going back to the 1980s: 'I wrote the code, I'm done.' But what does that mean? Nobody has any idea." Dawid is critical of current AI frameworks like , pointing out fundamental flaws. They start with AI first and try to add structure later (backwards approach). They use task lists with checkboxes where AI decides when something is "done"—but without clear criteria, this becomes ad hoc decision-making reminiscent of 1980s development practices. These frameworks "vibecode the specs," not realizing there's a structured taxonomy to specifications that BDD already solved. Most concerning, some have removed testing as a "feature," treating it as optional. Dawid sees these frameworks as over-engineered, process-centric rather than developer-centric, often created by people who may not develop software themselves. AAID, in contrast, is built by a practicing developer solving real problems daily. Getting Started: Learn Fundamentals First "The first thing developers should do is learn the fundamentals. They should skip AI altogether and learn about BDD and TDD, just best practices. But when you know that, then you can look into a framework, maybe like mine." Dawid's advice for developers interested in AI-assisted coding might seem counterintuitive: start by learning fundamentals without AI. Master behavior-driven development, test-driven development, and software engineering best practices first. Only after understanding these foundations should developers explore frameworks like AAID. This isn't gatekeeping—it's recognizing that AI amplifies whatever approach developers bring. If they start with poor practices, AI will help them build unmaintainable systems faster. But if they start with solid fundamentals, AI becomes a powerful multiplier that lets them work at unprecedented speed while maintaining quality. , meeting developers wherever they are in their journey. About Dawid Dahl Dawid is the creator of Augmented AI Development (AAID), a disciplined approach where developers augment their capabilities by integrating with AI, while maintaining full architectural control. Dawid is a software engineer at Umain, a product development agency. You can link with and find . /episode/index/show/scrummastertoolbox/id/39079565

Scrum Master Toolbox Podcast: Agile storytelling from the trenches

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