In this Mistake of the Week, Mark Graban breaks down an incident involving an American Airlines A319 on final approach to Phoenix — captured on video with its landing gear still up. A cockpit alert sounded, the crew realized what was missing, and the pilots executed a safe go-around. Their explanation to air traffic control? A perfectly understated: “It wasn’t configured in the appropriate manner.”

Mark explores why these near-misses are less about individual oversight and more about systems built to detect — and correct — human error. From checklists to cockpit warnings to the decision to go around instead of pushing forward, this episode highlights why safety depends on catching mistakes early, not pretending they don't happen.

My guest for Episode #330 of the My Favorite Mistake podcast is Debra Clary, a leadership strategist, researcher, and executive coach with more than four decades of experience at organizations including Frito-Lay, Coca-Cola, Jack Daniel’s, and Humana.

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She’s also a TEDx speaker, former off-Broadway performer, and the author of the new book The Curiosity Curve: A Leader’s Guide to Growth and Transformation Through Bold Questions.

In this episode, Debra shares one of her favorite mistakes—an unexpected wrong train stop in Italy that turned into a memorable discovery—and how that happy accident helped shape her approach to curiosity, flexibility, and exploring the unexpected. That theme carries through the conversation as Debra and I discuss how curiosity shows up in leadership, why assumptions can derail teams, and why “having the answers” is often the wrong place to start.

Debra walks us through the research behind The Curiosity Curve, including how her team developed a validated diagnostic for measuring curiosity and what they learned about its connection to engagement, retention, innovation, and decision speed. She shares practical examples of how leaders unintentionally shut down curiosity and how small shifts in inquiry can unlock better thinking and stronger team performance.

We also explore how curiosity interacts with psychological safety, how leaders can avoid the trap of reflexive certainty, and why curiosity becomes even more important in high-pressure or high-uncertainty situations. Debra closes by discussing the role curiosity plays in an AI-driven world—why it remains uniquely human, and how tools like AI can actually help people deepen their inquiry rather than replace it.

If you’re interested in how leaders can cultivate better questions, better conversations, and better outcomes, this episode will spark ideas you can put to use right away.

• What’s your favorite mistake?
• Were there similar moments in your career where a “missed stop” led to an unexpected opportunity?
• Was starting as a Frito-Lay route driver a deliberate development path, or was that unusual?
• Where did your passion for curiosity begin?
• Is there a way to gauge curiosity in a team or organization?
• How do you measure something like curiosity in a meaningful way?
• How do you help leaders learn to be more curious instead of just telling people to “be curious”?
• When hiring, is it better to select already-curious people or rely on the culture to develop curiosity?
• Is there such a thing as too much curiosity—can it slow execution or decision-making?
• From your research or coaching, what’s an example of curiosity being missing and causing problems?
• How do you help leaders understand that curiosity and psychological safety are building blocks for innovation—not optional extras?
• Do you see leaders struggle with the difference between knowing, assuming, and figuring things out?
• In urgent or high-pressure situations, does stress make it harder for people to stay curious?
• Do you have examples where curiosity helped prevent a small mistake from turning into a big one?
• Have you seen situations where people used questions in unhelpful or critical ways while claiming they were being “curious”?
• How do you think about Ed Schein’s idea of humble inquiry?
• Can AI replace curiosity—or does curiosity still give humans a unique advantage?
• Can interacting with AI actually help people strengthen their curiosity?

My guest for Episode #329 of the My Favorite Mistake podcast is Dr. Melissa Robinson-Winemiller, a TEDx speaker, empathy and leadership expert, and author of The Empathic Leader: How EQ via Empathy Transforms Leadership for Better Profit, Productivity, and Innovation.

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Melissa shares the story of her “favorite mistake” — leaving her music and academic career after experiencing a toxic culture and institutional failure to protect her following an assault by a colleague. What began as heartbreak became the foundation for her life’s work: helping leaders build empathy, trust, and psychologically safe workplaces.

We discuss how empathy differs from sympathy and compassion, and why leaders often misunderstand empathy as weakness. Melissa explains why true empathy isn’t about being nice—it’s about being kind—and how self-empathy is the first step toward leading others effectively.

Her framework for self-empathy includes observing, reflecting, building awareness, and practicing compassion toward oneself. That self-understanding helps leaders respond constructively when mistakes happen—creating cultures where learning and accountability can thrive.

“Empathy isn’t soft. It’s kind.” “Empathy doesn’t mean no boundaries—it means understanding through another’s perspective.”

Melissa also discusses findings from her doctoral research in interdisciplinary leadership at Creighton University and her viral TEDx Talk on self-empathy and self-judgment, which has drawn tens of thousands of views within days of release.

In this edition of Mistake of the Week, Mark Graban tells a story that didn’t appear in any safety report or headline — it happened on a pickleball court. Early in learning the sport, Mark found his old tennis instincts taking over, leading to a very incorrect serve and a moment of embarrassment. What followed was a small but meaningful lesson in feedback, psychological safety, and the challenge of unlearning deeply wired habits.

Supportive coaching, timely correction, and a friendly playing environment turned an awkward mistake into a productive one. Mark reflects on why unlearning is often harder than learning, and how leaders can create conditions where people feel safe enough to improve.

In this week’s Mistake of the Week, Mark Graban tells the story of a Maine hospital system that accidentally mailed condolence letters to 531 very-much-alive patients. The cause? A computer glitch — and a few missing fail-safes. Mark explores what this bizarre mix-up reveals about system design, automation, and trust in healthcare. Beyond the absurd headline lies a familiar pattern: when we blame people instead of learning from process failures, we guarantee more mistakes. So what does “fully resolved” really mean? And what can leaders learn from a mistake that’s literally to die for? If you received this episode through your podcast app and not a séance, you’re doing fine.

We’re going back to Episode 30 from January 2021, featuring Katie Anderson — author of Learning to Lead, Leading to Learn — and Isao Yoshino, the longtime Toyota leader whose career and lessons inspired her book.

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It was such a privilege to talk with them then, and even more meaningful now, because I recently got to spend time with Mr. Yoshino in Japan last October during Katie’s Learning to Lead, Leading to Learn experience. Seeing him there — humble, curious, and still passionate about developing others — really reinforced everything we talked about in that episode.

Mr. Yoshino shared a story from early in his Toyota career, when a mistake on the shop floor could have led to punishment, but instead led to learning. His leaders didn’t blame him — they worked with him to fix the system. That experience shaped how he led and coached for decades.

Katie shared her own favorite mistake — a story about feedback early in her career that helped her realize the power of listening, asking questions, and helping others find their own answers.

Together, we explored what it means to create a culture where people feel safe to learn, improve, and grow — the kind of culture that turns mistakes into progress.

My guest for Episode #328 of the My Favorite Mistake podcast is Emily Aborn, a small business copywriter, speaker, and host of the Small Business Casual podcast.

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Emily helps entrepreneurs bring clarity, creativity, and authenticity to their marketing. Before finding her true calling, she owned a brick-and-mortar organic mattress store—a business that looked great on paper but didn’t align with her passions or strengths.

Emily shares how this “perfect-on-paper” business became her favorite mistake. Though the store was profitable, she found herself feeling trapped, unfulfilled, and disconnected from the work she truly loved. Through closing that chapter, Emily discovered what she actually enjoyed most—writing, connection, and storytelling—and turned those insights into a business built around her natural skills.

Today, Emily works with entrepreneurs across industries to find their authentic voice and create meaningful marketing. In this episode, she and Mark explore lessons about self-awareness, alignment, and how mistakes can guide us toward a more fulfilling path. Emily also shares practical insights on copywriting, understanding your audience, and why genuine collaboration beats fear-based marketing every time.

• What was your favorite mistake, and what did you learn from it?
• Why did that business seem like such a good idea on paper?
• What made you realize it wasn’t the right fit?
• How did running that store help you discover your passion for copywriting?
• What were some of the marketing lessons you learned from that experience?
• What are the most common copywriting or branding mistakes you see small businesses make?
• How can business owners find and express their authentic voice in their marketing?
• What are “problem-aware,” “solution-aware,” and “symptom-aware” customers—and why does that matter?
• How do you approach repurposing content the right way instead of just copying and pasting?
• What has hosting your own podcast taught you about communication and creativity?
• Have you ever made a memorable mistake as a podcaster yourself?

My guest for Episode #327 of the My Favorite Mistake podcast is Dr. Maya Ackerman, AI pioneer, researcher, and CEO of WaveAI. She’s also an associate professor of Computer Science and Engineering at Santa Clara University and the author of the new book Creative Machines: AI, Art, and Us.

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In this episode, Maya shares her favorite mistake — one that changed how she builds technology and thinks about creativity. Early in her journey as an entrepreneur, her team at WaveAI created an ambitious product called “Alicia,” designed to assist with every step of music creation. But in trying to help too much, they accidentally took freedom away from users. That experience inspired her concept of “humble AI” — systems that step back, listen, and support human creativity rather than take over.

Maya describes how that lesson led to their breakthrough success with Lyric Studio, an AI songwriting tool that empowers millions of artists by helping them create while staying true to their own voices. She also shares insights from her research on human-centered design, the philosophy behind generative models, and why we should build AI that’s more collaborative than competitive.

Together, we discuss why mistakes — whether made by people or machines — can spark innovation, and how being more forgiving toward imperfection can help both leaders and creators thrive.

“If AI is meant to be human-centric, it must be humble. Its job is to elevate people, not replace them.” — Maya Ackerman

“Who decided machines have to be perfect? It’s a ridiculous expectation — and a limiting one.” — Maya Ackerman

• What was your favorite mistake — and what did you learn from it?
• What went wrong with your second product, “ALYSIA,” and how did that shape your later success?
• How did you discover the concept of “humble creative machines”?
• What makes Lyric Studio different from general AI tools like ChatGPT?
• How do you design AI that supports — rather than replaces — human creativity?
• What’s the real difference between AI and a traditional algorithm?
• How do you think about ethical concerns, like AI imitating living artists?
• What do you mean by human-centered AI — and how can we build it?
• Why do AI systems “hallucinate,” and can those mistakes actually be useful?
• How can embracing mistakes — human or machine — lead to more creativity and innovation?
• What are your thoughts on AI’s future — should we be hopeful or concerned?