Scrum Master Toolbox Podcast: Agile storytelling from the trenches

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: http://bit.ly/SMTP_ShowNotes. 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.   Buy Now on Amazon   [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 Scott Smith on LinkedIn.  

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: http://bit.ly/SMTP_ShowNotes.   "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 MIRO not just as a tool for running retrospectives but as a living archive of team learning and growth. He uses MIROVERSE 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.   Buy Now on Amazon   [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 Scott Smith on LinkedIn.

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: http://bit.ly/SMTP_ShowNotes.   "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.   Buy Now on Amazon   [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 Scott Smith on LinkedIn.

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: http://bit.ly/SMTP_ShowNotes.   "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.   Buy Now on Amazon   [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 Scott Smith on LinkedIn.

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: http://bit.ly/SMTP_ShowNotes.   "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.   Buy Now on Amazon   [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 Scott Smith on LinkedIn.  

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 Mo Edjlali 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 S.N. Goenka, 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." This mirrors the South Park episode's warning about AI dependency, 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 coun

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 WindSurf and Claude Code, 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 swarm programming—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 AppleScript and Tmux 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 Calgary Software Crafters 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: https://www.youtube.com/watch?v=_LSK2bVf0Lc&t=8654s Lada's Patterns and Anti-patterns website: https://lexler.github.io/augmented-coding-patterns/ Lada's Substack https://lexler.substack.com/ AI Assisted Coding episode with Dawid Dahl AI Assisted Coding episode with Llewellyn Falco Claude Flow - orchestration platform   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 Lada Kesseler on LinkedIn.

AI Assisted Coding: Treating AI Like a Junior Engineer - Onboarding Practices for AI Collaboration In this special episode, Sergey Sergyenko, CEO of Cybergizer, 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 Vibecoding 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. This TDD 2.0 framework (a talk Sergey gave at the Global Agile Summit) 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 AAID, SpecKit, 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 Obie Fernandez's work on "Patterns of Application Development Using AI," particularly valuable for Ruby and Rails developers but applicable broadly. He references Andrey Karpathy's original vibecoding post and emphasizes Extreme Programming practices as foundational. The tools he uses—Cursor and Claude Code—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 t

BONUS: Augmented AI Development - Software Engineering First, AI Second In this special episode, Dawid Dahl introduces Augmented AI Development (AAID)—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 "vibecoding"—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 Marcus Hammarberg's work and his book The Bungsu Story. 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 TDD and BDD, 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 DORA 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 SpecKit, 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. AAID offers both a dense technical article on dev.to and a gentler game-like onboarding in the GitHub repo, 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 Dawid Dahl on LinkedIn and find the AAID framework on GitHub.

AI Assisted Coding: Swimming in AI - Managing Tech Debt in the Age of AI-Assisted Coding In this special episode, Lou Franco, veteran software engineer and author of "Swimming in Tech Debt," shares his practical approach to AI-assisted coding that produces the same amount of tech debt as traditional development—by reading every line of code. He explains the critical difference between vibecoding and AI-assisted coding, why commit-by-commit thinking matters, and how to reinvest productivity gains into code quality. Vibecoding vs. AI-Assisted Coding: Reading Code Matters "I read all the code that it outputs, so I need smaller steps of changes."   Lou draws a clear distinction between vibecoding and his approach to AI-assisted coding. Vibecoding, in his definition, means not reading the code at all—just prompting, checking outputs, and prompting again. His method is fundamentally different: he reads every line of generated code before committing it. This isn't just about catching bugs; it's about maintaining architectural control and accountability. As Lou emphasizes, "A computer can't be held accountable, so a computer can never make decisions. A human always has to make decisions." This philosophy shapes his entire workflow—AI generates code quickly, but humans make the final call on what enters the repository. The distinction matters because it determines whether you're managing tech debt proactively or discovering it later when changes become difficult. The Moment of Shift: Staying in the Zone "It kept me in the zone. It saved so much time! Never having to look up what a function's arguments were... it just saved so much time."   Lou's AI coding journey began in late 2022 with GitHub Copilot's free trial. He bought a subscription immediately after the trial ended because of one transformative benefit: staying in the flow state. The autocomplete functionality eliminated constant context switching to documentation, Stack Overflow searches, and function signature lookups. This wasn't about replacing thinking—it was about removing friction from implementation. Lou could maintain focus on the problem he was solving rather than getting derailed by syntax details. This experience shaped his understanding that AI's value lies in removing obstacles to productivity, not in replacing the developer's judgment about architecture and design. Thinking in Commits: The Right Size for AI Work "I think of prompts commit-by-commit. That's the size of the work I'm trying to do in a prompt."   Lou's workflow centers on a simple principle: size your prompts to match what should be a single commit. This constraint provides multiple benefits. First, it keeps changes small enough to review thoroughly—if a commit is too big to review properly, the prompt was too ambitious. Second, it creates a clear commit history that tells a story about how the code evolved. Third, it enables easy rollback if something goes wrong. This commit-sized thinking mirrors good development practices that existed long before AI—small, focused changes that each accomplish one clear purpose. Lou uses inline prompting in Cursor (Command-K) for these localized changes because it keeps context tight: "Right here, don't go look at the rest of my files... Everything you need is right here. The context is right here... And it's fast." The Tech Debt Question: Same Code, Same Debt "Based on the way I've defined how I did it, it's exactly the same amount of tech debt that I would have done on my own... I'm faster and can make more code, but I invest some of that savings back into cleaning things up."   As the author of "Swimming in Tech Debt," Lou brings unique perspective to whether AI coding creates more technical debt. His answer: not if you're reading and reviewing everything. When you maintain the same quality standards—code review, architectural oversight, refactoring—you generate the same amount of debt as manual coding. The difference is speed. Lou gets productivity gains from AI, and he consciously reinvests a portion of those gains back into code quality through refactoring. This creates a virtuous cycle: faster development enables more time for cleanup, which maintains a codebase that's easier for both humans and AI to work with. The key insight is that tech debt isn't caused by AI—it's caused by skipping quality practices regardless of how code is generated. When Vibecoding Creates Debt: AI Resistance as a Symptom "When you start asking the AI to do things, and it can't do them, or it undoes other things while it's doing them... you're experiencing the tech debt a different way. You're trying to make changes that are on your roadmap, and you're getting resistance from making those changes."   Lou identifies a fascinating pattern: tech debt from vibecoding (without code review) manifests as "AI resistance"—difficulty getting AI to make the changes you want. Instead of compile errors or brittle tests signaling problems, you experience AI struggling to understand your codebase, undoing changes while making new ones, or producing code with repetition and tight coupling. These are classic tech debt symptoms, just detected differently. The debt accumulates through architecture violations, lack of separation of concerns, and code that's hard to modify. Lou's point is profound: whether you notice debt through test failures or through AI confusion, the underlying problem is the same—code that's difficult to change. The solution remains consistent: maintain quality practices including code review, even when AI makes generation fast. Can AI Fix Tech Debt? Yes, With Guidance "You should have some acceptance criteria on the code... guide the LLM as to the level of code quality you want."   Lou is optimistic but realistic about AI's ability to address existing tech debt. AI can definitely help with refactoring and adding tests—but only with human guidance on quality standards. You must specify what "good code" looks like: acceptance criteria, architectural patterns, quality thresholds. Sometimes copy/paste is faster than having AI regenerate code. Very convoluted codebases challenge both humans and AI, so some remediation should happen before bringing AI into the picture. The key is recognizing that AI amplifies your approach—if you have strong quality standards and communicate them clearly, AI accelerates improvement. If you lack quality standards, AI will generate code just as problematic as what already exists. Reinvesting Productivity Gains in Quality "I'm getting so much productivity out of it, that investing a little bit of that productivity back into refactoring is extremely good for another kind of productivity."   Lou describes a critical strategy: don't consume all productivity gains as increased feature velocity. Reinvest some acceleration back into code quality through refactoring. This mirrors the refactor step in test-driven development—after getting code working, clean it up before moving on. AI makes this more attractive because the productivity gains are substantial. If AI makes you 30% faster at implementation, using 10% of that gain on refactoring still leaves you 20% ahead while maintaining quality. Lou explicitly budgets this reinvestment, treating quality maintenance as a first-class activity rather than something that happens "when there's time." This discipline prevents the debt accumulation that makes future work progressively harder. The 100x Code Concern: Accountability Remains Human "Directionally, I think you're probably right... this thing is moving fast, we don't know. But I'm gonna always want to read it and approve it."   When discussing concerns about AI generating 100x more code (and potentially 100x more tech debt), Lou acknowledges the risk while maintaining his position: he'll always read and approve code before it enters the repository. This isn't about slowing down unnecessarily—it's about maintaining accountability. Humans must make the decisions because only humans can be held accountable for those decisions. Lou sees potential for AI to improve by training on repository evolution rather than just end-state code, learning from commit history how codebases develop. But regardless of AI improvements, the human review step remains essential. The goal isn't to eliminate human involvement; it's to shift human focus from typing to thinking, reviewing, and making architectural decisions. Practical Workflow: Inline Prompting and Small Changes "Right here, don't go look at the rest of my files... Everything you need is right here. The context is right here... And it's fast."   Lou's preferred tool is Cursor with inline prompting (Command-K), which allows him to work on specific code sections with tight context. This approach is fast because it limits what AI considers, reducing both latency and irrelevant changes. The workflow resembles pair programming: Lou knows what he wants, points AI at the specific location, AI generates the implementation, and Lou reviews before accepting. He also uses Claude Code for full codebase awareness when needed, but the inline approach dominates his daily work. The key principle is matching tool choice to context needs—use inline prompting for localized changes, full codebase tools when you need broader understanding. This thoughtful tool selection keeps development efficient while maintaining control. Resources and Community Lou recommends Steve Yegge's upcoming book on vibecoding. His website, LouFranco.com, provides additional resources.    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 Lou Franco on LinkedIn and visit his website at L

AI Assisted Coding: From Designer to Solo Developer - Building Production Apps with AI In this special episode, Elina Patjas shares her remarkable journey from designer to solo developer, building LexieLearn—an AI-powered study tool with 1,500+ users and paying customers—entirely through AI-assisted coding. She reveals the practical workflow, anti-patterns to avoid, and why the future of software might not need permanent apps at all. The Two-Week Transformation: From Idea to App Store "I did that, and I launched it to App Store, and I was like, okay, so… If I can do THIS! So, what else can I do? And this all happened within 2 weeks."   Elina's transformation happened fast. As a designer frustrated with traditional software development where maybe 10% of your original vision gets executed, she discovered Cursor and everything changed. Within two weeks, she went from her first AI-assisted experiment to launching a complete app in the App Store. The moment that shifted everything was realizing that AI had fundamentally changed the paradigm from "writing code" to "building the product." This wasn't about learning to code—it was about finally being able to execute her vision 100% the way she wanted it, with immediate feedback through testing. Building LexieLearn: Solving Real Problems for Real Users "I got this request from a girl who was studying, and she said she would really appreciate to be able to iterate the study set... and I thought: "That's a brilliant idea! And I can execute that!" And the next morning, it was 9.15, I sent her a screen capture."   Lexie emerged from Elina's frustration with ineffective study routines and gamified edtech that didn't actually help kids learn. She built an AI-powered study tool for kids aged 10-15 that turns handwritten notes into adaptive quizzes revealing knowledge gaps—private, ad-free, and subscription-based. What makes Lexie remarkable isn't just the technology, but the speed of iteration. When a user requested a feature, Elina designed and implemented it overnight, sending a screen capture by 9:15 AM the next morning. This kind of responsiveness—from customer feedback to working feature in hours—represents a fundamental shift in how software can be built. Today, Lexie has over 1,500 users with paying customers, proving that AI-assisted development isn't just for prototypes anymore. The Workflow: It's Not Just "Vibing" "I spend 30 minutes designing the whole workflow inside my head... all the UX interactions, the data flow, and the overall architectural decisions... so I spent a lot of time writing a really, really good spec. And then I gave that to Claude Code."   Elina has mixed feelings about the term "vibecoding" because it suggests carelessness. Her actual workflow is highly disciplined. She spends significant time designing the complete workflow mentally—all UX interactions, data flow, and architectural decisions—then writes detailed specifications. She often collaborates with Claude to write these specs, treating the AI as a thinking partner. Once the spec is clear, she gives it to Claude Code and enters a dialogue mode: splitting work into smaller tasks, maintaining constant checkpoints, and validating every suggestion. She reads all the code Claude generates (32,000 lines client-side, 8,000 server-side) but doesn't write code herself anymore. This isn't lazy—it's a new kind of discipline focused on design, architecture, and clear communication rather than syntax. Reading Code vs. Writing Code: A New Skill Set "AI is able to write really good code, if you just know how to read it... But I do not write any code. I haven't written a single line of code in a long time."   Elina's approach reveals an important insight: the skill shifts from writing code to reading and validating it. She treats Claude Code as a highly skilled companion that she needs to communicate with extremely well. This requires knowing "what good looks like"—her 15 years of experience as a designer gives her the judgment to evaluate what the AI produces. She maintains dialogue throughout development, using checkpoints to verify direction and clarify requirements. The fast feedback loop means when she fails to explain something clearly, she gets immediate feedback and can course-correct instantly. This is fundamentally different from traditional development where miscommunication might not surface until weeks later. The Anti-Pattern: Letting AI Run Rampant "You need to be really specific about what you want to do, and how you want to do it, and treat the AI as this highly skilled companion that you need to be able with."   The biggest mistake Elina sees is treating AI like magic—giving vague instructions and expecting it to "just figure it out." This leads to chaos. Instead, developers need to be incredibly specific about requirements and approach, treating AI as a skilled partner who needs clear communication. The advantage is that the iteration loop is so fast that when you fail to explain something properly, you get feedback immediately and can clarify. This makes the learning curve steep but short. The key is understanding that AI amplifies your skills—if you don't know what good architecture looks like, AI won't magically create it for you. Breaking the Gatekeeping: One Person, Ten Jobs "I think that I can say that I am a walking example of what you can do, if you have the proper background, and you know what good looks like. You can do several things at a time. What used to require 10 people, at least, to build before."   Elina sees herself as living proof that the gatekeeping around software development is breaking down. Someone with the right background and judgment can now do what previously required a team of ten people. She's passionate about others experiencing this same freedom—the ability to execute their vision without compromise, to respond to user feedback overnight, to build production-quality software solo. This isn't about replacing developers; it's about expanding who can build software and what's possible for small teams. For Elina, working with a traditional team would actually slow her down now—she'd spend more time explaining her vision than the team would save through parallel work. The Future: Intent-Based Software That Emerges and Disappears "The software gets built in an instance... it's going to this intent-based mode when we actually don't even need apps or software as we know them."   Elina's vision for the future is radical: software that emerges when you need it and disappears when you don't. Instead of permanent apps, you'd have intent-based systems that generate solutions in the moment. This shifts software from a product you download and learn to a service that materializes around your needs. We're not there yet, but Elina sees the trajectory clearly. The speed at which she can now build and modify Lexie—overnight feature implementations, instant bug fixes, continuous evolution—hints at a future where software becomes fluid rather than fixed. Getting Started: Just Do It "I think that the best resource is just your own frustration with some existing tools... Just open whatever tool you're using, is it Claude or ChatGPT and start interacting and discussing, getting into this mindset that you're exploring what you can do, and then just start doing."   When asked about resources, Elina's advice is refreshingly direct: don't look for tutorials, just start. Let your frustration with existing tools drive you. Open Claude or ChatGPT and start exploring, treating it as a dialogue partner. Start building something you actually need. The learning happens through doing, not through courses. Her own journey proves this—she went from experimenting with Cursor to shipping Lexie to the App Store in two weeks, not because she found the perfect tutorial, but because she just started building. The tools are good enough now that the biggest barrier isn't technical knowledge—it's having the courage to start and the judgment to evaluate what you're building.   About Elina Patjas   Elina is building Lexie, an AI-powered study tool for kids aged 10–15. Frustrated by ineffective "read for exams" routines and gamified edtech fluff, she designed Lexie to turn handwritten notes into adaptive quizzes that reveal knowledge gaps—private, ad-free, and subscription-based. Lexie is learning, simplified.   You can link with Elina Patjas on LinkedIn.

Sara Di Gregorio: Coaching Product Owners from Isolation to Collaboration 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: http://bit.ly/SMTP_ShowNotes. The Great Product Owner: Using User Story Mapping to Break Down PO Isolation "One of the key strengths is the ability to build a strong collaborative relationship with the Scrum team. We constantly exchange feedback, with the shared goal of improving both our collaborating and the way of working." - Sara Di Gregorio   Sara considers herself fortunate—she currently works with Product Owners who exemplify what great collaboration looks like. One of their key strengths is the ability to build strong collaborative relationships with the Scrum team. They don't wait for sprint reviews to exchange feedback; instead, they constantly communicate with the shared goal of improving both collaboration and ways of working.  These Product Owners involve the team early, using techniques like user story mapping after analysis phases to create open discussions around upcoming topics and help the team understand potential dependencies. They make themselves truly available—they observe daily stand-ups not as passive attendees but as engaged contributors. If the team needs five minutes to discuss something afterward, the Product Owner is ready. They attend Scrum events with genuine interest in working with the team, not just fulfilling an attendance requirement. They encourage open dialogue, even participating in retrospectives to understand how the team is working and where they can improve collaboration. What sets these Product Owners apart is their communication approach. They don't come in thinking they know everything or that they need to do everything alone. Their mindset is collaborative: "We're doing this together." They recognize that developers aren't just executors—they're users of the product, experts who can provide valuable perspectives.  When Product Owners ask "Why do you want this?" and developers respond with "If we do it this way, we can be faster, and you can try your product sooner," that's when magic happens. Great Product Owners understand that strong communication skills and collaborative relationships create better products, better teams, and better outcomes for everyone involved.   Self-reflection Question: How are your Product Owners involving the team early in discovery and analysis, and are they building collaborative relationships or just attending required events? The Bad Product Owner: The Isolated Expert Who Thinks Teams Just Execute   "Sometimes they feel very comfortable in their subject, so they assume they know everything, and the team has only to execute what they asked for." - Sara Di Gregorio   Sara has encountered Product Owners who embody the worst anti-pattern: they believe they don't need to interact with the development team because they're confident in their subject matter expertise. They assume they know everything, and the team's job is simply to execute what they ask for. These Product Owners work isolated from the development team, writing detailed user stories alone and skipping the interesting discussions with developers. They only involve the team when they think it's necessary, treating developers as order-takers rather than collaborators who could contribute valuable insights.  The impact is significant—teams lose the opportunity to understand the "why" behind features, Product Owners miss perspectives that could improve the product, and collaboration becomes transactional instead of transformational. Sara's approach to addressing this anti-pattern is patient but deliberate. She creates space for dialogue and provides training with the Product Owner to help them understand how important it is to collaborate and cooperate with the team. She shows them the impact of including the team from the beginning of feature study.  One powerful technique she uses is user story mapping workshops, bringing both the team and Product Owner together. The Product Owner explains what they want to deliver from their point of view, but then something crucial happens: the team asks lots of questions to understand "Why do you want this?"—not just "I will do it."  Through this exercise, Sara watched Product Owners have profound realizations. They understood they could change their mindset by talking with developers, who often are users of the product and can offer perspectives like "If we do it this way, we can be faster, and you can try your product sooner."  The workshop helps teams understand the big picture of what the Product Owner is asking for while helping the Product Owner reflect on what they're actually asking. It transforms the relationship from isolation to collaboration, from directive to dialogue, from assumption to shared understanding.   In this segment, we refer to the User Story Mapping blog post by Jeff Patton.   Self-reflection Question: Are your Product Owners writing user stories in isolation, or are they involving the team in discovery to create shared understanding and better solutions?   [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.   Buy Now on Amazon   [The Scrum Master Toolbox Podcast Recommends]   About Sara Di Gregorio   Sara is a people-centered Scrum Master who champions trust, collaboration, and real value over rigid frameworks. With experience introducing Agile practices, she fosters empathy, inclusion, and clarity in every team. As an Advanced Scrum Master, she helps teams grow, perform, and deliver with enthusiasm and purpose.   You can link with Sara Di Gregorio on LinkedIn.  

Sara Di Gregorio: How to Know Your Team Has Internalized Agile Values 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: http://bit.ly/SMTP_ShowNotes.   "Scrum isn't just a process to follow, it's a way of working." - Sara Di Gregorio   For Sara, success as a Scrum Master isn't measured by what the team delivers—it's measured by how they grow. She knows that if you facilitate team growth in communication and collaboration, delivery will naturally improve.  The indicators she watches for are subtle but powerful. When teams come to her with specific requests outside the regular schedule—"Can we have 30 minutes to talk and reflect mid-sprint?"—she knows something has shifted. When teams want to reflect outside the retrospective cycle, it means they've internalized the value of continuous improvement, not just going through the motions. She listens for the word "goal" during sprint planning.  When team members start their planning by talking about goals, she feels a surge of recognition: "Okay, for me, this is very, very, very important." Success shows up in unexpected places. One of her colleague's teams pushed back during a cross-team meeting, saying "We're going out of the timebox" and suggesting they move the discussion to a different time. That kind of proactive leadership and accountability signals maturity. It means the team isn't just attending Scrum events because they have to—they truly understand why each event matters and actively participate to make them valuable.  When Sara first met a team, they asked if she wanted to change things. She said no. What she focuses on is how people improve and understand the process better. For her, it starts with the people—when people change and understand the value, that's when real changes happen in the company. It's about helping people feel good and be guided well, because when they're working well, that's when transformation becomes possible. As Sara reminds us, Scrum isn't just a process to follow—it's a way of working that teams must embrace, understand, and make their own.   Self-reflection Question: Are your teams coming to you asking for reflection time outside scheduled events, and what does that tell you about how deeply they've internalized continuous improvement? Featured Retrospective Format for the Week: Unstructured Retrospective After facilitating many structured retrospectives, Sara started experimenting with an unstructured format that brought new energy to team reflection. Instead of using predefined frameworks, she brings white paper, sticky notes, and sharpies of different colors. She opens with a simple question: "Guys, what impacted you mostly during the last week? How do you feel today?" Sometimes she starts with data and metrics; other times, she begins with how the team is feeling.  The key is creating open space for conversation rather than forcing it into a predetermined structure. What Sara discovered is remarkable: "They are more engaged, more open, and more present in the conversation, maybe because it was something new." Instead of the same structured format every time, the unstructured approach breaks the routine and creates space for true reflections that bring out something deeper and more meaningful. It allows people to express what's genuinely going on for them, not just what fits into a predefined template.  Sara doesn't abandon structured formats entirely—she alternates between structured and unstructured to keep retrospectives fresh and engaging. She also recommends, if you work hybrid, trying to schedule unstructured retrospectives for days when the team is in the office together. The physical presence combined with the open format creates an environment where teams can be more vulnerable, more creative, and more honest about what's really happening. The unstructured retrospective isn't about chaos—it's about trusting the team to surface what matters most to them, with the Scrum Master providing light facilitation and space for authentic reflection.   [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.   Buy Now on Amazon   [The Scrum Master Toolbox Podcast Recommends]   About Sara Di Gregorio   Sara is a people-centered Scrum Master who champions trust, collaboration, and real value over rigid frameworks. With experience introducing Agile practices, she fosters empathy, inclusion, and clarity in every team. As an Advanced Scrum Master, she helps teams grow, perform, and deliver with enthusiasm and purpose.   You can link with Sara Di Gregorio on LinkedIn.

Sara Di Gregorio: Facilitating Deeper Retrospectives—When to Step In and When to Step Back 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: http://bit.ly/SMTP_ShowNotes.   "When they start connecting and having an interesting discussion, I go to the corner, and I'm only trying to listen." - Sara Di Gregorio   Sara faces a challenge that many Scrum Masters encounter: teams that want to discuss too many topics during retrospectives without going deep on any of them. The team had plenty to talk about, but conversations stayed surface-level, never reaching the insights that drive real improvement. Sara recognized that the aim of the retrospective isn't to talk about everything—it's to go deeper on topics the team genuinely cares about.  So she started coaching teams to select just three main topics they wanted to discuss, helping them understand why prioritization matters and making explicit which topics are most important. But her real skill emerged in how she facilitated the discussions. When she saw communication starting to flow and team members becoming deeply connected to the topic, she moved to the corner and listened. She didn't abandon the team—she remained present, ready to help shy or quiet members speak up, watching the clock to respect timeboxes.  But she understood that when teams connect authentically, the Scrum Master's job is to create space, not fill it. Sara learned to ask better questions too. Instead of repeatedly asking "Why? Why? Why?"—which can feel accusatory—she reformulated: "How did you approach it? What happens?" When teams started blaming other teams, she redirected: "What can we influence? What can we do from our side?" She used visual tools like white paper, sharpies, and sticky notes to help teams visualize their discussion steps and create structured moments for questions.  Sometimes, when teams discussed complex technical topics beyond her understanding, she empowered them: "You are the main expert of this topic. Please, when someone sees that we're going out of topic or getting too detailed, raise your hand and help me bring the communication back to what we've chosen to talk about."  This balance—knowing when to step in with structure and when to step back and listen—is what transforms retrospectives from checkbox events into genuine opportunities for team growth.   Self-reflection Question: In your facilitation, are you creating space for deep team connection, or are you inadvertently filling the space that teams need to discover insights for themselves?   [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.   Buy Now on Amazon   [The Scrum Master Toolbox Podcast Recommends]   About Sara Di Gregorio   Sara is a people-centered Scrum Master who champions trust, collaboration, and real value over rigid frameworks. With experience introducing Agile practices, she fosters empathy, inclusion, and clarity in every team. As an Advanced Scrum Master, she helps teams grow, perform, and deliver with enthusiasm and purpose.   You can link with Sara Di Gregorio on LinkedIn.

Sara Di Gregorio: Rebuilding Agile Team Connection in the Remote Work Era 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: http://bit.ly/SMTP_ShowNotes.   "The book helped me to shift from reacting to connecting, which completely changed the quality of conversation." - Sara Di Gregorio   When COVID forced Sara's team into full remote work, she noticed something troubling—the team was losing real connection. Replicating in-office meetings online simply didn't work. People attended meetings but weren't truly present. The spontaneous coffee machine conversations that built relationships and surfaced important information had vanished.  So Sara started experimenting. She introduced 5-minute chit-chat sessions at the start of every meeting: "Guys, how are you today? What happened yesterday?" She created "coffee all together" moments—10-minute virtual breaks where the team could drink coffee or have aperitivos together, sometimes three times per week. She established weekly feedback sessions every Friday morning—30 minutes to recap the week and understand what could improve.  These weren't just social niceties; they were deliberate efforts to recreate the human connections that remote work had stripped away. Sara recognized that mechanized interactions—"here are the things I need you to do, let's talk next steps"—kill team dynamics. Teams need moments where they relate to each other as people, not just as functions.  The experiments worked because they created space for genuine connection, allowing the team to maintain the trust and collaboration that makes effective teamwork possible, even when working remotely.   In this episode, we refer to Non-Violent Communication concepts and practices.   Self-reflection Question: How are you creating moments for your remote or hybrid team to connect as people, not just as colleagues executing tasks? Featured Book of the Week: Nonviolent Communication by Marshall Rosenberg Sara credits Nonviolent Communication by Marshall Rosenberg (translated in Italian as "Words are Windows, or They are Walls") as having a deep impact on her career. The book explores how to listen without judging, how to ask the right questions, and how to observe people to understand their real needs. But above all, it teaches how to communicate in a way that builds connection rather than creating barriers.  For Sara, the book was remarkably practical—she didn't just read it, she experimented with the techniques afterward. She explains: "I think that without this mindset, it's easy to fall into reactive communication, trying to defend, justify, or give quick answers. But that often blocks real understanding." The book helped her shift from reacting to connecting, which completely changed the quality of her conversations.  As a Scrum Master working with people every day—facilitating meetings, mediating conflicts, supporting teams—the way we communicate determines whether we open dialogue or close it. Sara found that taking time to reflect instead of giving quick answers transformed her ability to help teams discover dependencies, improve dialogue, and address communication issues. For anyone in the Scrum Master role, this book provides essential skills for building the kind of connection that makes true collaboration possible. In this segment, we also refer to the NVC episodes we have on the podcast. Check those out to learn more about Nonviolent Communication   [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.   Buy Now on Amazon   [The Scrum Master Toolbox Podcast Recommends]   About Sara Di Gregorio   Sara is a people-centered Scrum Master who champions trust, collaboration, and real value over rigid frameworks. With experience introducing Agile practices, she fosters empathy, inclusion, and clarity in every team. As an Advanced Scrum Master, she helps teams grow, perform, and deliver with enthusiasm and purpose. You can link with Sara Di Gregorio on LinkedIn.

Sara Di Gregorio: When Teams Lose Trust—How Scrum Masters Rebuild It One Small Change at a Time 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: http://bit.ly/SMTP_ShowNotes.   "I continue to approach this situation with openness, positivity, and trust, because I truly believe that even the smallest changes can make a difference over time." - Sara Di Gregorio   Sara faced one of the most challenging situations a Scrum Master can encounter—a team member who had lost all trust in change, creating a negative atmosphere that weighed heavily on the entire team. She remembers the heaviness on her shoulders, feeling personally responsible for the team's wellbeing. The negativity was palpable during every meeting, and it threatened to undermine the team's progress.  But Sara refused to give up. She started experimenting with different approaches: one-to-one conversations to understand what was happening, bringing intentional energy to meetings, and trying new facilitation techniques in retrospectives. She added personal check-ins, asking "How are you today?" at the start of stand-ups, consciously bringing positive energy even on days when she didn't feel it herself.  She discovered that listening—truly listening, not just hearing—means understanding how people feel, not just what they're saying. Sara learned that the energy you bring to interactions matters deeply. Starting the day with genuine interest, asking about the team's wellbeing, and even making small comments about the weather could create tiny shifts—a small smile that signaled something had changed.  Her approach was rooted in persistence and belief: she continued approaching the situation with openness, positivity, and trust, knowing that even the smallest changes can make a difference over time. For Sara, reestablishing a good environment wasn't about quick fixes—it was about showing up every day with the right energy and never giving up on her team.   Self-reflection Question: What energy are you bringing to your interactions with the team today, and how might that be shaping the team's atmosphere?   [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.   Buy Now on Amazon   [The Scrum Master Toolbox Podcast Recommends]   About Sara Di Gregorio   Sara is a people-centered Scrum Master who champions trust, collaboration, and real value over rigid frameworks. With experience introducing Agile practices, she fosters empathy, inclusion, and clarity in every team. As an Advanced Scrum Master, she helps teams grow, perform, and deliver with enthusiasm and purpose.   You can link with Sara Di Gregorio on LinkedIn.

BONUS: Flawless Execution — Translating Fighter Pilot Precision to Business Results In this powerful conversation, former fighter pilot Christian "Boo" Boucousis reveals how military precision translates into agile business leadership. We explore the FLEX model (Plan-Brief-Execute-Debrief), the critical difference between control-based and awareness-based leadership, and why most organizations fail to truly embrace iterative thinking. From Cockpit to Boardroom: An Unexpected Journey "I learned over time that it doesn't matter what you do if you're always curious, and you're always intentional, and you're always asking questions." — Christian "Boo" Boucousis   Christian's path from fighter pilot to leadership consultant wasn't planned—it was driven by necessity and curiosity. After 11 years as a fighter pilot (7 in Australia, 4 in the UK), an autoimmune condition ended his flying career at age 30. Rather than accepting a comfy job flying politicians around, he chose entrepreneurship. He moved to Afghanistan with a friend and built a reconstruction company that grew to a quarter billion dollars in four years. The secret? The debrief skills he learned as a fighter pilot. By constantly asking "What are you trying to achieve? How's it going? Why is there a gap?" he approached business with an agile mindset before he even knew what agile was. This curiosity-driven, question-focused approach became the foundation for everything that followed. The FLEX Model: Plan-Brief-Execute-Debrief "Agile and scrum were co-created by John Sutherland, who was a fighter pilot, and its origins sit in the OODA loop and iteration. Which is why it's a circle." — Christian "Boo" Boucousis   The FLEX model isn't new—fighter pilots have used this Plan-Brief-Execute-Debrief cycle for 60 years. It's the ultimate simple agile model, designed to help teams accelerate toward goals using the same accelerated learning curve the Air Force uses to train fighter pilots. The key insight: everything in this model is iterative, not linear. Every mission has a start, middle, and end, and every stage involves constant adaptation. Afterburner (the company Christian now leads as CEO) has worked with nearly 3,800 companies and 2.8 million people over 30 years, teaching this model. What's fascinating is that the DNA of agile is baked into fighter pilot thinking—John Sutherland, co-creator of Scrum, wrote the foreword for Christian's book "The Afterburner Advantage" because they share the same roots in the OODA loop and iterative thinking. Why Iterative Thinking Doesn't Come Naturally "Iterative thinking is not a natural human model. Most of the time we learn from mistakes. We don't learn as a habit." — Christian "Boo" Boucousis   Here's the hard truth: agile as a way of working is very different from the way human beings naturally think. Business leadership models still hark back to Frederick Winslow Taylor's 1911 book on scientific management—industrial era leadership designed for building buildings, not creating software. Time is always linear (foundation, then structure, then finishing), and this shapes how we think about planning. Humans also tend to organize like villages with chiefs, warriors, and gatherers—hierarchical and political. Fighter pilots created a parallel system where politics exist outside missions, but during execution, personality clashes can't interfere. The challenge for business isn't the method—it's getting human minds to embrace iteration as a habit, not just a process they follow when forced. Planning: Building Collective Consciousness, Not Task Lists "Planning isn't all about sequencing actions—that's not planning. That's the byproduct of planning, which is collectively agreeing what good looks like at the end." — Christian "Boo" Boucousis   Most people plan in their head or in front of a spreadsheet by themselves. That's not planning—that's collecting thoughts. Real planning means bringing everyone on the team together to build collective consciousness about what's possible. The plan is always "the best idea based on what we know now." Once airborne, everything changes because the enemy doesn't cooperate with your plan. Planning is about the destination, not the work to get there. Think about airline pilots: they don't tell you about traffic delays on their commute or maintenance issues. They say "Welcome aboard, our destination is Amsterdam, there's weather on the way, we'll land 5 minutes early." That's a brief—just the effect on you based on all their work. Most business meetings waste 55 minutes on backstory and 5 minutes deciding to have another meeting. Fighter pilots focus entirely on: What are we trying to achieve? What might get in the way? Let's go. Briefing: The 25-Minute Focus Window "You need 25 minutes of focus before your brain really focuses on the task. You program your brain for the mission at hand." — Christian "Boo" Boucousis   The brief is the moment between planning and execution when the plan is as accurate as it'll ever get. It's called "brief" for a reason—it's really short. The team checks that everyone understands the plan in today's context, accounting for last-minute changes (broken equipment, weather, personnel changes). Then comes the critical part: creating the mission bubble. From the brief until mission end, there are no distractions, no notifications. If someone tries to interrupt a fighter pilot walking to the jet, the response is clear: "I'm in my mission bubble. No distractions." This isn't optional—research shows it takes 25 minutes of uninterrupted focus before your brain truly locks onto a task. Yet most business leaders expect constant availability, with notifications pinging every few minutes. If you need everyone to have notifications on to run your business, you're doing a really bad job at planning. Execution: Awareness-Based Leadership vs. Control-Based Leadership "The reason we have so many meetings is because the leader is trying to control the situation and own all the awareness. It's not humanly possible to do that." — Christian "Boo" Boucousis   During execution, fighter pilots fly the plan until it doesn't work anymore—then they adapt. A mission commander might lead 70 airplanes, but can't possibly track all 69 others. Instead, they create "gates"—checkpoints where everyone confirms they're in the right place within 10 seconds. They plan for chaos, creating awareness points where the team is generally on track or not. The key shift: from control-based leadership (the leader tries to control everything) to awareness-based leadership (the leader facilitates and listens for divergences). This includes "subordinated leadership"—any of the four pilots in a formation can take the lead if they have better awareness. If a wingman calls out a threat the leader doesn't see, the immediate response is "Press! You take the lead." This works because they planned for it and have criteria. Business teams profess to want this kind of agile collaboration, but struggle because they haven't invested in the planning and shared understanding that makes fluid leadership transitions possible. Abort Criteria: Knowing When to Stop "We have this concept called abort criteria. If certain criteria are hit, we abort the mission. I think that's a massive opportunity for business." — Christian "Boo" Boucousis   There are degrees of things going wrong: a little bit, a medium amount, and everything going wrong. When everything's going wrong, fighter pilots stop and turn around—they don't keep pressing a bad situation. This "abort criteria" concept is massively underutilized in business. Too often, teams press bad situations, transparency disappears, people stop talking, and everyone goes into survival mode (protect myself, blame others). This never happens with fighter pilots. If something goes wrong, they take accountability and make the best decision. The most potent team size is four people: a leader, deputy leader, and two wingmen. This small team size with clear roles and shared abort criteria creates psychological safety to call out problems and adapt quickly. The Retrospective Mindset: Not Just a Ritual "A retrospective isn't a ritual. It's actually a way of thinking. It's a cognitive model. If you approached everything as a retrospective—what are we trying to achieve? How's it going? Why is it not going where we want? What's the one action to get back on track?" — Christian "Boo" Boucousis   The debrief—the retrospective—is the most important part of fighter pilot culture translated into agile. It's not just a meeting you have at the end of a sprint. It's a mindset you apply to everything: projects, relationships, personal development. Christian introduces "Flawless Leadership" built on three M's: Method (agile practices), Mindset (growth mindset developed through acting iteratively), and Moments (understanding when to show up as a people leader vs. an impact leader). The biggest mistake in technology: teams do retrospectives internally but don't include the business. They get a brief from the business, build for two months, come back, and the business says "What is this? This isn't what I expected." If they'd had the business in every scrum, every iteration, trust would build naturally. Everyone involved in the mission must be part of the planning, briefing, executing, and debriefing. Leading in the Moment: Three Layers of Leadership "Your job as a scrum master, as a leader—it doesn't matter if you're leading a division of people—is to be aware. And you're only going to be aware by listening." — Christian "Boo" Boucousis   Christian breaks leadership into three layers: People Leadership (political, emotional, dealing with personalities and overwhelm), Impact Leadership (the agile layer, results-driven, scientific), and Leading Now (the reactive, amygdala-driven panic response when things go wrong). The mistake: mixin

Alidad Hamidi: When Product Owners Facilitate Vision Instead of Owning It 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: http://bit.ly/SMTP_ShowNotes. The Great Product Owner: Co-Creating Vision Through Discovery "The best product owner I worked with was not a product owner, but a project manager. And she didn't realize that she's acting as a product owner." - Alidad Hamidi   The irony wasn't lost on Alidad. The best Product Owner he ever worked with didn't have "Product Owner" in her title—she was a project manager who didn't even realize she was acting in that capacity. The team was working on a strategic project worth millions, but confusion reigned about what value they were creating. Alidad planned an inception workshop to create alignment among stakeholders, marketing, operations, advisors, and the team.   Twenty minutes into the session, Alidad asked a simple question: "How do we know the customer has this problem, and they're gonna pay for it?" Silence. No one knew. To her immense credit, the project manager didn't retreat or deflect. Instead, she jumped in: "What do we need to do?" Alidad suggested assumptions mapping, and two days later, the entire team and stakeholders gathered for the workshop. What happened next was magic. "She didn't become a proxy," Alidad emphasizes. She didn't say, "I'll go find out and come back to you." Instead, she brought everyone together—team, stakeholders, and customers—into the same room.   The results were dramatic. The team was about to invest millions integrating with an external vendor. Through the assumption mapping workshop, they uncovered huge risks and realized customers didn't actually want that solution. "We need to pivot," she declared. Instead of the expensive integration, they developed educational modules and scripts for customer support and advisors. The team sat with advisors, listening to actual customer calls, creating solutions based on real needs rather than assumptions. The insight transformed not just the project but the project manager herself. She took these discovery practices across the entire organization, teaching everyone how to conduct proper discovery and fundamentally shifting the product development paradigm. One person, willing to facilitate rather than dictate, made this impact. "Product owner can facilitate creation of that [vision]," Alidad explains. "It's not just product owner or a team. It's the broader stakeholder and customer community that need to co-create that."   Self-reflection Question: Are you facilitating the creation of vision with your stakeholders and customers, or are you becoming a proxy between the team and the real sources of insight? The Bad Product Owner: Creating Barriers Instead of Connections "He did the opposite, just creating barriers between the team and the environment." - Alidad Hamidi   The Product Owner was new to the organization, technically skilled, and genuinely well-intentioned. The team was developing solutions for clinicians—complex healthcare work requiring deep domain understanding. Being new, the PO naturally leaned into his strength: technical expertise. He spent enormous amounts of time with the team, drilling into details, specifying exactly how everything should look, and giving the team ready-made solutions instead of problems to solve.   Alidad kept telling him: "Mate, you need to spend more time with our stakeholder, you need to understand their perspective." But the PO didn't engage with users or stakeholders. He stayed comfortable in his technical wheelhouse, designing solutions in isolation. The results were predictable and painful. Halfway through work, the PO would realize, "Oh, we really don't need that." Or worse, the team would complete something and deliver it to crickets—no one used it because no one wanted it. "Great person, but it created a really bad dynamic," Alidad reflects. What should have been the PO's job—understanding the environment, stakeholder needs, and market trends—never happened. Instead of putting people in front of the environment to learn and adapt, he created barriers between the team and reality.   Years later, Alidad's perspective has matured. He initially resented this PO but came to realize: "He was just being human, and he didn't have the right support and the environment for him." Sometimes people learn only after making mistakes. The coaching opportunity isn't to shame or blame but to focus on reflection from failures and supporting learning. Alidad encouraged forums with stakeholders where the PO and team could interact directly, seeing each other's work and constraints. The goal isn't perfection—it's creating conditions where Product Owners can connect teams to customers rather than standing between them.   Self-reflection Question: What barriers might you be unintentionally creating between your team and the customers or stakeholders they need to serve, and what would it take to remove yourself from the middle?   [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.   Buy Now on Amazon   [The Scrum Master Toolbox Podcast Recommends]   About Alidad Hamidi   Alidad is a strategic advisor in human-centred transformation, focused on organisational design for autonomy, ownership, and impact. A recovering Agility Coach, he draws on years across delivery and coaching roles to help build organisations truly fit for humans—resilient, adaptive, and designed for people, not just processes.   You can link with Alidad Hamidi on LinkedIn. You can also visit his website at desirablefutures.group.

Alidad Hamidi: Maximizing Human Potential as the Measure of Success 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: http://bit.ly/SMTP_ShowNotes.   "Does my work lead into maximizing human potential? Maximizing the ability of the human to use their potential and freedom." - Alidal Hamidi   Alidad calls himself a "recovering agility coach," and for good reason. For years, he struggled to define success in his work. As an enterprise coach, he plants seeds but never sees the trees grow. By the time transformation takes root, he's moved on to the next challenge. This distance from outcomes forced him to develop a more philosophical definition of success—one rooted not in deliverables or velocity charts, but in human potential and freedom.   His measure of success centers on three interconnected questions. First, are customers happy with what the teams create? Notice he says "create," not "deliver"—a deliberate choice. "I really hate the term product delivery, because delivery means you have a feature factory," he explains. Creating value requires genuine interaction between people who solve problems and people who have problems, with zero distance between them. Second, what's the team's wellbeing? Do they have psychological safety, trust, and space for innovation? And third, is the team growing—and by "team," Alidad means the entire organization, not just the squad level.   There's a fourth element he acknowledges: business sustainability. A bank could make customers ecstatic by giving away free money, but that's not viable long-term. The art lies in balance. "There's always a balance, sometimes one grows more than the other, and that's okay," Alidad notes. "As long as you have the awareness of why, and is that the right thing at the right time." This definition of success requires patience with the messy reality of organizations and faith that when humans have the freedom to use their full potential, both people and businesses thrive.   Self-reflection Question: If you measured your success solely by whether you're maximizing human potential and freedom in your organization, what would you start doing differently tomorrow? Featured Retrospective Format for the Week: Six Intrinsic Motivators Alidad's favorite retrospective format comes from Open Systems Theory—the Six Intrinsic Motivators. This approach uses the OODA Loop philosophy: understanding reality and reflecting on actions. "Let's see what actually happened in reality, rather than our perception," Alidad explains.   The format assesses six elements. Three are personal and can have too much or too little (rated -10 to +10): autonomy in decision making, continuous learning and feedback, and variety in work. Three are team environment factors that you can't have too much of (rated 0 to 10): mutual support and respect, meaningfulness (both socially useful work and seeing the whole product), and desirable futures (seeing development opportunities ahead).   The process is elegantly simple. Bring the team together and ask each person to assess themselves on each criterion. When individuals share their numbers, fascinating conversations emerge. One person's 8 on autonomy might surprise a teammate who rated themselves a 3. These differences spark natural dialogue, and teams begin to balance and adjust organically. "If these six elements don't exist in the team, you can never have productive human teams," Alidad states. He recommends running this at least every six months, or every three months for teams experiencing significant change. The beauty? No intervention from outside is needed—the team naturally self-organizes around what they discover together.   [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.   Buy Now on Amazon   [The Scrum Master Toolbox Podcast Recommends]   About Alidad Hamidi   Alidad is a strategic advisor in human-centred transformation, focused on organisational design for autonomy, ownership, and impact. A recovering Agility Coach, he draws on years across delivery and coaching roles to help build organisations truly fit for humans—resilient, adaptive, and designed for people, not just processes.   You can link with Alidad Hamidi on LinkedIn. You can also visit his website at desirablefutures.group.  

Alidad Hamidi: The Tax Agile Teams Pay for Organizational Standards 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: http://bit.ly/SMTP_ShowNotes.   "If you set targets for people, they will achieve the target, even if that means destroying the system around them." - W. Edwards Deming (quoted by Alidad)   The tension is familiar to every Scrum Master working in large organizations: leadership demands standard operating models, flow time metrics below specific numbers, and reporting structures that fit neat boxes. Meanwhile, teams struggle under the weight of context-insensitive measurements that ignore the nuanced reality of their work. Alidad faces this challenge daily—creating balance between organizational demands and what teams actually need to transform and thrive.   His approach starts with a simple but powerful question to leaders: "What is it that you want to achieve with these metrics?" Going beyond corporate-speak to have real conversations reveals that most leaders want outcomes, not just numbers. Alidad then involves teams in defining strategies to achieve those outcomes, framing metrics as "the tax we pay" or "the license to play." When teams understand the intent and participate in the strategy, something surprising happens—most metrics naturally improve because teams are delivering genuine value, customers are happy, and team dynamics are healthy.   But context sensitivity remains critical. Alidad uses a vivid analogy: "If you apply lean metrics to Pixar Studio, you're gonna kill Pixar Studio. If you apply approaches of Pixar Studio to production line, they will go bankrupt in less than a month." Toyota's production line and Pixar's creative studio both need different approaches based on their context, team evolution, organizational maturity, and market environment. He advocates aligning teams to value delivery with end-to-end metrics rather than individual team measurements, recognizing that organizations operate in ecosystem models beyond simple product paradigms.   Perhaps most important is patience. "Try to not drink coffee for a week," Alidad challenges. "Even for a single person, one practice, it's very hard to change your behavior. Imagine for organization of hundreds of thousands of people." Organizations move through learning cycles at their own rhythm. Our job isn't to force change at the speed we prefer—it's to take responsibility for our freedom and find ways to move the system, accepting that systems have their own speed.   Self-reflection Question: Which metrics are you applying to your teams without considering their specific context, and what conversation do you need to have with leadership about the outcomes those metrics are meant to achieve?   [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.   Buy Now on Amazon   [The Scrum Master Toolbox Podcast Recommends]   About Alidad Hamidi   Alidad is a strategic advisor in human-centred transformation, focused on organisational design for autonomy, ownership, and impact. A recovering Agility Coach, he draws on years across delivery and coaching roles to help build organisations truly fit for humans—resilient, adaptive, and designed for people, not just processes.   You can link with Alidad Hamidi on LinkedIn. You can also visit his website at desirablefutures.group.