TECHNICALLY JOYFUL - Building Change Capacity in the Age of AI

Gabrielle Kohlmeier - AI Leadership & Change Capacity
  • 5.0 (17)
  • Management

Change is coming faster than ever. Joy helps us keep up — and shape what comes next. Look closely at the people doing hard things extraordinarily well — creating change that lasts, building what didn’t exist before, turning ambitious ideas into reality — and you’ll notice something: joy is often part of the fuel. They are technically joyful. Host Gabrielle Kohlmeier has used joy again and again to build with others what seemed impossible — and create outcomes beyond what anyone thought possible. In Technically Joyful, she shares what she’s learned and brings together people doing hard, consequential things differently: leaders, builders, thinkers, and wonderfully curious humans exploring what they’re seeing, what they’re learning, what isn’t obvious yet, and what the rest of us can use. We’ll tackle the hard questions. We’ll make the invisible work of change visible. We’ll find signal in the noise. And we’ll get practical about what actually helps people and organizations move — from technology, strategy, and systems to judgment, incentives, relationships, courage, and the wonderfully human messiness in between. Instead of fear as fuel, we use curiosity, connection, usefulness, awe, and the gentle persistence of joy. Joy gives us energy to engage with hard things — to stay curious longer, see more possibilities, connect more dots, and keep going. Every episode is designed to leave you seeing something differently, understanding something useful, and feeling more capable of acting — at work, in your organization, and in the much bigger experiment we’re all part of as AI reshapes our world. Expect hard questions, fascinating people, useful ideas, unexpected connections — and to come out stronger than you went in. Change is a muscle. Joy helps us build it. Welcome to Technically Joyful. Some Questions We‘ll Explore:  Why does being a beginner feel so threatening once you’re successful?What happens when the work that disappears was also the training ground?Why do some people seem energized by uncertainty while others freeze?What are we losing when efficiency becomes the dominant measure of value?How do you know when doing nothing is actually the riskier choice?What becomes possible when we stop treating curiosity as frivolous?What does AI reveal about work that was already broken?How do we keep our judgment while changing how we use it?What becomes more valuable — not less — as AI gets better?Why might joy actually make us better at doing hard things?

Episodes

  1. 4d ago

    The Joy of Learning Out Loud: How to Help Shape the AI Era | Laura Belmont

    What if the biggest barrier to learning, leading, and taking a risk is the permission we haven’t yet given ourselves? Laura Belmont has spent her career asking who a system was built for, who it leaves behind, and how it could work better, from disability-rights advocacy and Big Law to Comcast, Civis Analytics, and now The Suite. Laura and Gabrielle explore what it means to learn out loud in a profession that prizes being right. Laura shares how becoming General Counsel helped her recognize her strengths, and reflects on learning to offer herself the same grace she encourages in her children: the first attempt is practice, not proof of failure.  That willingness to learn, experiment, and question assumptions matters even more as organizations navigate and incorporate AI. Laura shares the story of working to build an elaborate Slack bot… with less than perfect results.  But experimentation still matters. Laura explains why moving quickly is not the same as moving forward, why lawyers need to understand the tools they are advising on, and how making broad fears more specific can turn them into questions we can actually investigate and address. And while so much about AI is still being defined, Gabrielle and Laura challenge the assumption that we simply have to adapt to the systems being built around us. We can ask better questions, push for what we need, and help shape the standards that come next. Joy has a role in that work. Not as a way to ignore the risks or hard questions, but as fuel for curiosity, learning, experimentation, and the agency to participate in shaping what comes next.  In This Episode: Why Laura stopped defining herself as risk-averse and started questioning what fear was actually holding her back fromWhat learning out loud makes possible in professions where people are expected to already know the answerWhy the simplest solution can be better than an over-engineered AI workflowThe difference between moving fast with AI and moving with directionWhy experimentation with AI can build useful capability even before the destination is clearWhy lawyers need firsthand understanding of AI tools in order to advise organizations effectivelyWhat Laura means when she says every lawyer is now a product counselHow breaking broad AI fears into specific concerns makes them easier to evaluate and addressWhy responsible AI adoption does not have to be a binary yes or noWhy all of us have a role in shaping the standards of the AI era Your Transformation Gym Rep Choose one AI concern you’re carrying.  Ask your AI tool: ‘Interview me until we can name exactly what I’m worried about. Then help me break that concern into smaller, testable pieces.’ Take the best question it gives you to an actual human.  And, as Laura suggests, try one low-stakes use case that is simply fun. (Interview-me format inspired by Allie K. Miller.)  Meet Laura Laura Belmont is General Counsel of The Suite and leads content and programming strategy for The L Suite. Previously, she served as General Counsel of Civis Analytics and held legal leadership roles at Comcast and Latham & Watkins. Ways to Connect with Gabrielle Subscribe to Technically Joyful on Apple Podcasts, Spotify, and YouTube: technicallyjoyful.com Newsletter: technicallyjoyful.com GK Strategic Advisory: gkstrategic.com LinkedIn: linkedin.com/in/gabrielle-kohlmeier

  2. Sep 8

    A Map Is a Form of Agency: Strategy Under Uncertainty

    How do you make a strategy when the terrain keeps changing underneath you? We often want a map to tell us what will happen next. But maybe that’s asking a map to do the wrong job. In this episode of Technically Joyful, Gabrielle Kohlmeier explores what maps can teach us about navigating uncertainty: from her children learning to find their way around Berlin to Cold War ghost stations, an infamous story about lost soldiers carrying the wrong map, to her own experience leading transformation when no reliable route to the destination existed. Even the best map does not eliminate uncertainty. It does give us the directional energy to make a choice, pay attention to what happens, and adjust. That distinction matters in the AI era, when leaders are being asked to make decisions about technology, organizations, careers, and investment without knowing exactly what the terrain will look like a year from now. There is no complete map for where AI, work, or our organizations are headed. But we can still map forward: identify what we know, decide what matters enough to become our North Star, name our assumptions, sketch plausible routes, make a move small enough to learn from, and watch for signals that tell us when to change course. Gabrielle also examines the limits of maps. Every map reflects choices about what gets included, what disappears, and whose experience of the terrain is represented. Organizations have their own “ghost stations”: capabilities people cannot access, knowledge that does not move, and people close to the problem who were never invited to help draw the map. And this is where joy becomes useful. Fear can make every blank space feel dangerous. Joy and curiosity can widen the field enough to notice another route, another person who sees something we don't, or another possibility worth testing. The goal isn't to know exactly where the route ends. It's to have enough agency to take the next step, learn from the terrain, and keep drawing the map forward.  In This Episode Why a map can create agency without creating certaintyWhat Berlin's transit system taught Gabrielle about orientation and independenceWhy even an imperfect map can interrupt paralysisHow maps reveal some things while making others disappearThe “ghost stations” that can exist inside organizationsWhy speed is not the same thing as agency, but paralysis isn't safety either Why asking what isn't going to change can be as useful as predicting what will What strategy under uncertainty actually looks likeWhy there is no complete map for the future of AI or workHow joy and curiosity widen the routes we are able to seeUsing AI to uncover assumptions, missing routes, and signals for change Your Transformation Gym Rep: Draw a Small Map Pick one change you're navigating right now: organizational, professional, or deeply personal. In the center, write “You are here,” and underneath it write three things you know to be true, not what you predict and not what you fear. At the top, write your North Star: what you're moving toward or what matters enough to protect even if the route changes. Draw two possible routes, with one reasonable next step on each. Then mark one blank space, something important you don't know yet, and one signal that would make you update the map. Show your map to an AI tool and ask: What assumption am I treating as fact?What plausible route am I missing?What signal should I watch that might tell me to change course?Don't ask AI to choose your destination. That's your job. Use it to widen the map. You don't need to listen to it or believe it. It's there to open up your perspective. Then pick one small move to make this week.  Sources & Resources Data Feminism, by Catherine D'Ignazio and Lauren F. Klein A powerful examination of how power shapes what gets counted, represented, and omitted - and how data practices can help challenge unequal systems. The book is also available in an open-access edition. Same as Ever: A Guide to What Never Changes, by Morgan Housel A book about using the things that remain consistently true - especially patterns of human behavior - to navigate an unpredictable future. The map of the Pyrenees story The story of Hungarian soldiers finding their way through the Alps with a map that turned out to depict the Pyrenees was popularized in organizational thinking by Karl E. Weick. Its earlier source is Miroslav Holub's poem "Brief Thoughts on Maps," based on a story attributed to Hungarian scientist Albert Szent-Györgyi. Its precise historical status is uncertain, so it is best understood as a parable about orientation, action, and sensemaking rather than documented military history. Berlin's ghost stations After the Berlin Wall was constructed in 1961, Western S-Bahn and U-Bahn trains continued to travel beneath East Berlin on certain lines, but they passed slowly through sealed stations without stopping. The dimly lit platforms were guarded by East German border forces and became known as "ghost stations." Ways to Connect with Gabrielle Subscribe to Technically Joyful on Apple Podcasts, Spotify, and YouTube: technicallyjoyful.com Newsletter: technicallyjoyful.com GK Strategic Advisory: gkstrategic.com LinkedIn: linkedin.com/in/gabrielle-kohlmeier

  3. Sep 4

    The Joy of Building: How to Design a Human + Agent Organization with Geoff Schaefer

    What happens when AI agents stop being tools we occasionally use and start becoming members of our teams? Geoff Schaefer is literally writing the book on it. Geoff joins Gabrielle to vision what the agentic organization will actually look like, and how we can build it deliberately rather than simply letting it happen to us. They explore Geoff‘s framework for Building an Agentic Organization, and Gabrielle’s change framework, spanning strategy, governance, and economics, and get into some of the wonderfully complicated questions hiding underneath “AI transformation.” How do humans and agents divide work? What happens when agents can produce in eight hours what used to take two months? How do you budget for a workforce that includes salaries and tokens? How should an agent earn our trust? And what work becomes more valuable when machines can do almost anything? Along the way, they talk about creativity, radically diverse teams, culture, customer experience, and why some of the most important human work may move both further upstream into imagination and strategy and further downstream toward relationships, judgment, taste, and value. And the theme running through all of it: agency in getting to build this. In this episode • Why Geoff thinks agents should be treated as cultural actors, not just technology • His formula for agent trust: Earned Trust ≥ Required Trust • The Strategy, Governance & Economics framework behind his forthcoming book • Why AI may absorb the “midstream” work while humans move upstream and downstream • What happens when AI delivers work faster than organizations can absorb it • Why agent economics may mean managing token budgets alongside people budgets • How radically different perspectives make teams more creative • Why joy, curiosity, and creative freedom can become sources of organizational stamina • How working with AI can make us better at communicating our own intent Your Transformation Gym Rep Choose one recurring piece of work, ideally something mildly annoying. But don’t simply ask AI to do it. Give the AI a job description first. Ask it to interview you about what you’re actually trying to accomplish. Together, create a short role charter: its purpose, responsibilities, constraints, what good looks like, and when it should come back to you. Then do one small piece of the work together. The rep isn’t just about delegation. It’s practice in making your own intent clearer. About Geoff Schaefer Geoff Schaefer is an AI strategy and governance leader and the author of the forthcoming Building an Agentic Organization: The Strategy, Governance, and Economics of Agentic AI. He previously served as Vice President of AI Strategy and Governance at Leidos and led responsible AI work at Booz Allen Hamilton. He is also one of Gabrielle’s favorite people to call with an unfinished idea because his instinct is rarely “that won’t work.” It’s “how could we build it?” Resources Mentioned Building an Agentic Organization — Geoff Schaefer’s forthcoming book, expected Spring 2027 https://www.linkedin.com/in/geoffschaefer/ IDEO + Design Thinking https://designthinking.ideo.com/blog/60-minutes-and-the-future-of-design-thinking The ELIZA Effect https://aiethicslab.rutgers.edu/glossary/eliza-effect/ Kevin Allison + Minerva Technology Futures https://minervapolicy.com/our-team/ Keep the conversation going Who in your life hears “impossible” and gets curious instead of careful? Send them this episode. If Technically Joyful is earning a place in your week, follow the show, leave a review, and subscribe on Apple Podcasts, Spotify, or YouTube. And send Gabrielle your own AI show-and-tells: the useful, surprising, joyful, or tragically funny experiments you’ve tried. Some may make their way onto the show. Email: gabrielle@gkstrategic.com Ways to Connect with Gabrielle Subscribe to Technically Joyful on Apple Podcasts, Spotify, and YouTube: technicallyjoyful.com Newsletter: technicallyjoyful.com GK Strategic Advisory: gkstrategic.com LinkedIn: linkedin.com/in/gabrielle-kohlmeier

  4. Sep 1

    No One Has the Whole Picture: Why Connection Is a Leadership Capability

    What if the reason you can’t figure something out isn’t that you haven’t thought hard enough? What if part of the answer lives with someone else? When change is moving quickly, no one person has the whole picture. The knowledge we need is distributed across the people closest to the work, technical experts, skeptics, customers, people navigating risk, and sometimes the person who quietly tried six months ago what everyone else is still debating. That changes what expertise looks like. In this episode of Technically Joyful, Gabrielle Kohlmeier explores why connection is not just a nice leadership trait. It is a capability for navigating complexity. Drawing on her experience leading generative AI transformation inside a Fortune 30 company, Gabrielle shares how what first looked like a technology challenge quickly revealed an interconnected system of people, processes, incentives, risks, dependencies, and knowledge that no one person or function could see alone. The job wasn’t to know every piece. It was to get better at finding the pieces, connecting them, and exercising judgment across what emerged. Connection also gives us something else: energy. Sometimes another person gives us the question we hadn’t thought to ask, shows us a possibility we’d stopped seeing, or simply makes a difficult problem interesting again. Hard things require energy. Change requires energy. Learning requires energy. Sometimes we borrow that energy from one another. That’s joy as fuel. In This Episode Why no one person has the whole pictureHow distributed knowledge changes what expertise looks likeWhy “Who knows something we don’t?” can be a better question than “Who needs to approve this?”How human relationships help knowledge moveWhy accountability is different from solitary knowledge ownershipHow connection can replenish energy for hard thingsHow AI can surface missing perspectives without replacing lived knowledgeWhy curiosity says “I can learn” and connection says “I don’t have to learn alone” Your Rep: Widen the Aperture Think of one real thing you’re trying to figure out. Ask your AI tool: “I’m trying to figure out X. Give me five perspectives I may be missing, who might hold each one, and one question I should ask them.” Then pick one actual person who holds a perspective you need and ask: “I’m trying to figure out X. What are you seeing?” AI can widen your aperture. It can’t give you someone else’s lived knowledge. One person. One question. One rep. Sources & Resources Paul Leonardi & Tsedal Neeley, “What Managers Need to Know About Social Tools,” Harvard Business ReviewAmanda Palmer, The Art of AskingCarol Tavris & Elliot Aronson, Mistakes Were Made (But Not by Me) Ways to Connect with Gabrielle Subscribe to Technically Joyful on Apple Podcasts, Spotify, and YouTube: technicallyjoyful.com Newsletter: technicallyjoyful.com GK Strategic Advisory: gkstrategic.com LinkedIn: linkedin.com/in/gabrielle-kohlmeier

  5. Sep 1

    The Joy of Exploring: Leading AI Change Before the Map Exists | Anna Gressel, Partner and Co-Chair of AI Practice at Freshfields

    How do you lead through AI-driven change when the map hasn’t been drawn yet? Anna Gressel, partner and global co-head of AI at Freshfields, has built a career exploring questions without established answers, from neuroscience to some of the hardest legal, safety, governance, and strategy questions in AI. In this conversation, Anna and Gabrielle explore what it takes to move into unfamiliar territory with curiosity, creativity, and sound judgment. For Anna, the fact that something is new isn’t a reason to avoid it. It can be the reason to explore. That mindset shapes how she approaches novel problems: turning the prism, connecting ideas across disciplines, asking what might still be missing, and “scaffolding forward” toward challenges that haven’t fully arrived yet. But exploration isn’t the opposite of rigor. Anna works on high-stakes AI matters where safety, compliance, liability, and judgment matter enormously. The joy comes from helping clients solve hard problems, create responsibly, and find a wise path forward. The conversation also moves from individual AI fluency to organizational strategy. AI often doesn’t create entirely new organizational problems; it throws existing questions into sharper relief. What should we preserve? What needs to change? What is our competitive edge? Are we adopting AI because it serves a strategic goal, or simply for adoption’s sake? The goal isn’t predicting exactly where AI will be in five years. It’s building capabilities now that create more options later. In This Episode Why unexplored territory can be an invitation rather than a warningTurning the prism: connecting ideas across disciplinesBuilding AI fluency through experimentation and peer learningWhy even AI experts still feel behindHolding joy, creativity, risk, and judgment at the same timeWhy AI can surface organizational challenges that already existedStrategic AI adoption vs. adoption for adoption’s sakeBuilding capabilities now to create future optionalityUnlearning the comfort of familiar patterns Your Rep: Challenge the Familiar Think of one thing you hate doing or one familiar process you rarely question. Ask AI to interview you about how it works today, where the pain points are, and what might be removed, simplified, or done differently. Then ask: What could I stop doing? What could AI help me automate? What would I redesign if I were starting from scratch? You don’t have to automate everything. The rep is to challenge the comfort of the pattern and explore what might be possible. Chapter Markers 02:32 Everyday AI joy: spreadsheets as a thought partner 04:15 Why unexplored territory is worth pursuing 11:00 Turning the prism across disciplines 17:05 Building AI fluency through exploration 22:05 Why even experts feel behind 26:00 Joy, risk, and sound judgment 33:15 How AI surfaces existing organizational challenges 35:35 Why AI adoption needs a strategy 38:15 Building capabilities for an uncertain future 39:25 Unlearning the comfort of the pattern 42:20 Your Rep: challenge a familiar way of working 43:30 What makes the future of AI exciting Sources & Resources Anna Gressel, The AI Drop (https://www.freshfields.com/en/our-thinking/podcasts/the-ai-drop)ABA Commission on Women in the Profession + ABA Center for Innovation, 21 Days of AI: A Grit and Growth Mindset Challenge (https://www.americanbar.org/groups/diversity/women/initiatives_awards/grit-project/ai-grit-challenge-home/)Sebastian Seung / EyeWire, connectomics and brain-mapping research Ways to Connect with Gabrielle Subscribe to Technically Joyful on Apple Podcasts, Spotify, and YouTube: technicallyjoyful.com Newsletter: technicallyjoyful.com GK Strategic Advisory: gkstrategic.com LinkedIn: linkedin.com/in/gabrielle-kohlmeier

  6. Sep 1

    You Don’t Need to Catch Up on AI: Curiosity Is Your Change Strategy

    Feel like everyone else has figured out AI while you’re still trying to catch up? Here’s the problem: “caught up” may be the wrong goal. AI is changing too quickly for any of us to finish learning it. The leaders who will navigate this era best won’t be the people who know everything. They’ll be the people who build the capacity to keep learning, ask better questions, exercise judgment, experiment, and adapt as the ground moves. In the first episode of Technically Joyful, Gabrielle Kohlmeier explores why curiosity may be one of our most important change strategies in the AI era, especially for accomplished people who are used to being the ones with the answers. Drawing on her own journey from perfectionism to leading AI transformation, Gabrielle explores growth mindset, digital fluency, intellectual humility, psychological safety, and the power of becoming comfortable being experienced and a beginner at the same time. And this is where joy matters. Joy is not the opposite of rigor or discipline. It is fuel for exploration. Fear narrows our field of view. Curiosity, interest, and positive emotion can help broaden it, giving us more capacity to see possibilities, take smart risks, and keep learning when the work gets uncomfortable. Because you don’t need to catch up before you begin. Beginning is how you catch up. In This Episode Why AI fluency is not the same as knowing everythingThe “30% rule” for digital fluencyMoving from “I don’t know” to “I don’t know yet” to “let’s find out”How to be experienced and a beginner at the same timeHow perfectionism can disguise itself as excellenceWhy intellectual humility is different from insecurityWhy leaders need to model beginnerhoodHow joy can fuel learning and changeReframing anxiety as excitementWhy curiosity is a change strategy Your Rep: Play the ELI Game Pick one thing you keep thinking you should already understand. Ask your AI tool to explain it at progressively deeper levels: ELI7: Explain it like I’m seven. ELI12: Explain it like I’m 12. What did you add? ELI17: I’m 17 and pretty smart. Take me a level deeper. ELII: Explain it like I’m an intern. ELIE: Explain like I’m an expert. What are the three things I actually need to understand, and what can I safely ignore for now? Keep going until you move from “I don’t understand this” to “I have a foothold.” Then verify what matters. AI can hallucinate, oversimplify, and miss nuance. The goal is not to hand over your judgment. It is to use AI to accelerate curiosity while retaining it. Sources & Resources Tsedal Neeley & Paul Leonardi, The Digital MindsetCarol S. Dweck, MindsetReshma Saujani, Brave, Not PerfectAmy C. Edmondson, Right Kind of WrongTenelle Porter et al., “Predictors and Consequences of Intellectual Humility”Barbara L. Fredrickson, “The Role of Positive Emotions in Positive Psychology”Alison Wood Brooks, “Get Excited: Reappraising Pre-Performance Anxiety as Excitement” Ways to Connect with Gabrielle Subscribe to Technically Joyful on Apple Podcasts, Spotify, and YouTube: technicallyjoyful.com Newsletter: technicallyjoyful.com GK Strategic Advisory: gkstrategic.com LinkedIn: linkedin.com/in/gabrielle-kohlmeier

  7. Aug 24

    Welcome to Technically Joyful!

    What if joy could make us better at navigating change, not by making hard things easier, but by helping us stay curious, engaged, and willing to keep going? As AI reshapes how we work, lead, and make decisions, the challenge isn’t simply keeping up with technology. It’s building our capacity to navigate constant change and having the agency to help shape what comes next. This show explores the people, ideas, systems, and wonderfully human messiness behind meaningful change. Expect hard questions, fascinating conversations, unexpected connections, and practical ideas about AI, leadership, innovation, and what actually helps people and organizations move. Because change is a muscle. Joy helps us build it. Welcome to Technically Joyful.  Ways to Connect with Gabrielle Subscribe to Technically Joyful on Apple Podcasts, Spotify, and YouTube: technicallyjoyful.com Newsletter: technicallyjoyful.com GK Strategic Advisory: gkstrategic.com LinkedIn: linkedin.com/in/gabrielle-kohlmeier

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Change is coming faster than ever. Joy helps us keep up — and shape what comes next. Look closely at the people doing hard things extraordinarily well — creating change that lasts, building what didn’t exist before, turning ambitious ideas into reality — and you’ll notice something: joy is often part of the fuel. They are technically joyful. Host Gabrielle Kohlmeier has used joy again and again to build with others what seemed impossible — and create outcomes beyond what anyone thought possible. In Technically Joyful, she shares what she’s learned and brings together people doing hard, consequential things differently: leaders, builders, thinkers, and wonderfully curious humans exploring what they’re seeing, what they’re learning, what isn’t obvious yet, and what the rest of us can use. We’ll tackle the hard questions. We’ll make the invisible work of change visible. We’ll find signal in the noise. And we’ll get practical about what actually helps people and organizations move — from technology, strategy, and systems to judgment, incentives, relationships, courage, and the wonderfully human messiness in between. Instead of fear as fuel, we use curiosity, connection, usefulness, awe, and the gentle persistence of joy. Joy gives us energy to engage with hard things — to stay curious longer, see more possibilities, connect more dots, and keep going. Every episode is designed to leave you seeing something differently, understanding something useful, and feeling more capable of acting — at work, in your organization, and in the much bigger experiment we’re all part of as AI reshapes our world. Expect hard questions, fascinating people, useful ideas, unexpected connections — and to come out stronger than you went in. Change is a muscle. Joy helps us build it. Welcome to Technically Joyful. Some Questions We‘ll Explore:  Why does being a beginner feel so threatening once you’re successful?What happens when the work that disappears was also the training ground?Why do some people seem energized by uncertainty while others freeze?What are we losing when efficiency becomes the dominant measure of value?How do you know when doing nothing is actually the riskier choice?What becomes possible when we stop treating curiosity as frivolous?What does AI reveal about work that was already broken?How do we keep our judgment while changing how we use it?What becomes more valuable — not less — as AI gets better?Why might joy actually make us better at doing hard things?

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