Episodes
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AI is making it easier than ever to build products, automate work, and scale ideas. The challenge is no longer access to technology. It's designing the systems, stories, and customer understanding that turn AI into real business outcomes.
In this episode of Unlearn, I'm joined by Eric Baxley, Chief Marketing Officer at Nobody Studios. Eric shares how a seventh-grade summer teaching himself to program on an Atari 800 sparked a 30-plus year career spanning software development, product management, marketing, sales, business development, and partnerships.
We explore what Eric has had to unlearn while building companies in the AI era—from challenging assumptions before execution and replacing corporate polish with authentic storytelling, to designing scalable systems instead of disconnected tools. Along the way, Eric explains why great marketing still starts with deeply understanding customers, and why AI works best when it amplifies human judgment rather than replacing it.
Key TakeawaysChallenge the foundation before execution: Eric shared that in a previous large business, the team was “doing things right,” but not “doing the right things.” The segmentation was off, and correcting who they were really going after helped the team hit its goals for the next three years.Authentic stories build trust: Eric has had to unlearn the corporate habit of making everything polished before sharing it. He believes people respond when you show the journey, talk about the hardships, and ask for feedback along the way.Systems matter more than scattered tools: Eric warned against building a set of siloed point products. In a venture studio building multiple companies at once, he said you need systems that can scale, especially with the speed of AI.Use AI to strengthen your thinking, not replace it: Eric described writing and revising a LinkedIn post himself before turning to AI. The post performed well, and his takeaway was that people could sense it was naturally written and not simply generated.Real messaging starts with real customers: When Eric joined Nobody Studios, one of the first things he did was speak directly with patent attorneys for Evalify. That helped him understand their language, their concerns, and what message would actually resonate.
Additional InsightsStorytelling has to match the person and the moment: Eric explained that messaging should change based on persona, stage in the buyer journey, industry, and country. A CIO, CTO, or chief product officer may each need to hear the story differently.The right message needs different levels of depth: Eric talked about having a 30-second version, a 90-second version, and a longer version of the message ready. The point is to be prepared for the amount of attention and context the listener actually has.B2B messaging has to speak to head, heart, and wallet: Eric said that in larger enterprise deals, especially six- or seven-figure buying decisions, messaging needs to appeal to logic, emotion, and business economics.Consistency across channels is hard but necessary: Eric noted that messages can quickly become confusing when sales, TikTok, Instagram, LinkedIn, and other channels are all saying different things. The challenge is keeping the story consistent while still tailoring it to the audience.Automation still needs personalization: Eric uses some automated systems, but he emphasized that he still fine-tunes and personalizes messages based on someone’s background. Otherwise, outreach becomes the kind of generic message people ignore.
Episode Highlights00:00 - Episode Recap
Eric Baxley explains why company building in the AI era requires scalable systems, curiosity, grit, and a willingness to dig into the details rather than staying at a high level.
01:53 - Guest Introduction: Eric Baxley
Barry introduces Eric Baxley, Chief Marketing Officer at Nobody Studios, and highlights his work across growth, marketing, partnerships, and company building.
03:13 - The Seventh-Grade Spark
Eric shares how teaching himself to program on an Atari 800 while growing up in Germany sparked his interest in technology and shaped the rest of his career.
05:10 - Unlearning Assumptions
Eric explains why he no longer assumes the base foundation of a business is solid, using a segmentation mistake from a large business as an example.
06:20 - Moving Past Corporate Polish
Eric talks about unlearning the need for everything to be buttoned up and why showing the real journey can make the work more relatable.
07:39 - Authentic Stories in a Noisy Market
Barry and Eric discuss why honest stories about what is working, what is difficult, and what is still being learned can stand out from exaggerated AI claims.
10:48 - Tailoring the Story
Eric breaks down how messaging needs to be adapted by persona, buyer journey stage, industry, and country.
13:24 - Learning From Patent Attorneys
Eric shares how he started shaping Evalify’s messaging by speaking directly with patent attorneys instead of creating sales and marketing materials in a vacuum.
18:08 - Head, Heart, and Wallet
Eric explains why enterprise messaging needs more than a clinical problem-and-solution structure; it also needs emotion, business value, and a clear story.
22:40 - Building Systems Backwards From the Customer
Eric talks about the explosion of marketing technology and why he starts with the persona, the outcome, and the channels where customers actually spend time.
27:37 - Writing Before AI
Eric describes how he wrote and revised a LinkedIn post himself before involving AI, and why he believes the human work helped it resonate.
31:48 - Human-in-the-Loop AI for Patent Attorneys
Eric explains how Evalify helps patent attorneys with work that can take 20 to 30 hours, while making clear that the product amplifies their work rather than replacing them.
33:49 - Building Companies Faster and More Frugally
Eric shares why he is excited that small teams can now use AI capabilities to build, fund, and scale companies differently than in the past.
35:36 - Closing Reflections
Barry thanks Eric for sharing lessons from his work at Nobody Studios and looks forward to continuing to build together.
FAQsQ1. Who is Eric Baxley?
Eric Baxley is the Chief Marketing Officer at Nobody Studios. In the episode, he describes a career that began in software development and later moved into product management, marketing, sales, business development, and partnerships.
Q2. What does Eric Baxley say leaders need to unlearn?
Eric says he has had to unlearn assuming the foundation is already right, relying too much on corporate polish, and building around siloed tools instead of scalable systems.
Q3. Why does Eric Baxley focus so much on customer segmentation?
Eric believes many teams jump straight to execution without checking whether they are going after the right customers. He shared an example where fixing segmentation helped a business focus on the right audience and hit its goals.
Q4. How does Eric Baxley approach messaging for AI products?
Eric starts by talking to the people the product is meant to serve. With Evalify, he spoke with patent attorneys, used their language, tested the message, and worked with an advisory board to see whether the story resonated.
Q5. What role should AI play in marketing, according to this episode?
AI can help with speed, systems, and efficiency, but Eric and Barry emphasize that human judgment still matters. Eric’s examples show that personalization, customer understanding, and careful writing are still needed for the message to land.
Useful ResourcesEric Baxley on LinkedIn - https://www.linkedin.com/in/ericbaxley/ Nobody Studios on LinkedIn - https://www.linkedin.com/company/nobodycrowd/ Nobody StudiosEvalifyThe Challenger SaleArtificial Organizations - https://artificialorganizations.com/
Follow the HostBarry O’Reilly on LinkedIn: https://www.linkedin.com/in/barryoreillyBarry O’Reilly’s website: -
AI is changing how leaders think, decide, and work with their teams. But as John Cutler points out in this conversation, the real shift is not simply about faster answers or more productivity. It is about becoming more aware of the judgment systems we already use, often without noticing.
In this episode of the Unlearn Podcast, I’m joined again by John Cutler, product thinker, systems explorer, and Head of Product at Dotwork. We explore how AI can help leaders expose their thinking, pressure test decisions, and build stronger team judgment, while also making it easier to accelerate poor habits, shallow work, and false confidence.
John shares practical examples from product prioritization, survey design, objection handling, and team collaboration to show where AI can genuinely improve decision quality. We also get into the tradeoffs: why AI can make work feel like “hard mode,” why downtime still matters, and why intentionality is becoming one of the most important leadership skills in this moment.
Key TakeawaysAI exposes how leaders make decisions: AI tends to amplify the decision system already there. When a leader’s thinking is clear, AI can help make it visible and reusable; when it is vague, AI can make that vagueness move faster.
Judgment is built differently depending on the situation: John explains that some judgment comes from repetition and tacit pattern recognition, while other judgment develops through coaching, discussion, and working alongside people with more experience.
AI can help turn intuition into something teams can use: John’s example of documenting his product prioritization heuristic shows how AI can help make internal judgment concrete. The value comes from helping others understand why certain decisions matter, not just what the decision is.
Better AI use starts with knowing what you know: John contrasts product prioritization, where he has deep experience, with survey design, where he knows there is established expertise to draw from. The skill is recognizing whether AI should extend your own judgment or help you borrow from a domain expert.
Teams using AI well can raise decision quality: Barry shares how AI can help teams pressure test assumptions, run scenarios, and ask disconfirming questions without losing momentum. The real advantage comes when AI strengthens collaboration rather than replacing it.
AI can also accelerate bad instincts: John warns that AI can make poor thinking look polished. A team can paste AI onto an existing process and call it transformation without changing how decisions are actually made.
Intentionality matters more than productivity: AI can reduce friction, but it can also remove the pauses where judgment forms. Leaders need to design space for reflection, not just optimize for more output.
Additional InsightsIndividual metacognition: This is understanding how you think and make decisions. John’s examples show that leaders get more value from AI when they can first make their own judgment system visible.
Social metacognition: This is understanding that other people think, perceive, and engage differently. AI becomes more useful when it supports the conversation between people instead of flattening everyone into the same process.
Computational metacognition: This is understanding what LLMs are good at, where they fail, and how to work with them responsibly. John argues that leaders need this skill so they know when to trust AI, when to challenge it, and when to bring in human expertise.
Objection handling as a repeatable system: John’s team did not ask AI to create a generic sales guide. They role-played real objections, captured the discussion, compared their responses against best practices, and turned that into a system that could review future calls.
The deeper lesson: AI becomes more useful when it is connected to real work, real context, and a team’s actual judgment. Without that grounding, it risks creating more output without improving the quality of decisions.
Episode Highlights00:00 – Episode Recap
John Cutler opens with a story about how judgment often comes from repetition and tacit signals, not neat frameworks. The episode explores what happens when AI starts making those hidden decision systems visible.
02:02 – Guest Introduction: John Cutler
Barry welcomes back John Cutler, product thinker, systems explorer, and Head of Product at Dotwork, for a conversation about judgment, decision making, and collaboration in the age of AI.
04:59 – How Judgment Gets Built
John explains that judgment develops differently depending on the context: through individual practice, repeated exposure, mentorship, team discussion, and comparison against examples of quality.
08:58 – Making Prioritization Thinking Visible
John shares how he used AI to document his own scoring heuristic for product prioritization, giving a teammate deeper insight into why certain ideas mattered more than others.
12:11 – Knowing When to Borrow Expertise
Using survey design as an example, John explains how AI can help access existing expert knowledge when you are not the expert yourself. The key is being honest about the limits of your own judgment.
13:56 – From Answers to Better Questions
Barry reflects on the shift from using AI to get answers toward using it to challenge thinking, improve decisions, and bring stronger questions to colleagues.
18:04 – Why Better Surveys Lead to Better Decisions
John explains how improving a survey from average to strong can materially change the quality of insight a team gets back, which then affects the quality of product decisions.
23:04 – Teams, AI, and Decision Advantage
Barry shares how AI can help teams maintain momentum during ideation by quickly pressure testing scenarios, asking disconfirming questions, and bringing outside information into the room.
27:48 – Turning Objection Handling into a System
John describes how his team recorded a live objection-handling exercise, analyzed it against best practices, and turned the team’s collective knowledge into a reusable system.
31:32 – The Three Forms of Metacognition
John introduces individual, social, and computational metacognition as three skills leaders need to work effectively with AI and with each other.
35:19 – AI Exposes Leadership Systems
Barry and John discuss why AI can feel uncomfortable for leaders: it reveals whether there is a real decision-making system underneath the confidence.
37:34 – When AI Makes Every Decision Feel Hard
John raises an important limitation: AI can remove small pauses in the workday, leaving people constantly operating at high cognitive load.
41:58 – Productivity Fatigue and Agent Overload
Barry and John discuss the temptation to run too many AI-assisted tasks at once, and why that can create more noise rather than better outcomes.
44:23 – Designing Time to Think
Barry shares how he intentionally creates time for walking, exercise, and reflection to avoid over-optimizing for fast, reactive decisions.
46:38 – Intentionality Over Process Theater
John explains why intentionality is different from rigid process. The opportunity is to design better systems without flattening the richness of how teams actually work.
50:11 – Closing Reflections
Barry wraps the conversation by reflecting on the opportunity for leaders to use AI not just to move faster, but to become more aware of how they think, decide, and scale judgment across teams.
Useful ResourcesDotwork – John Cutler’s work focuses on helping teams and organizations better understand how work, decisions, and systems connect.Artificial Organizations – Barry references the book and the CSTA loop as part of his work on AI, decision making, and organizational performance.Daniel Kahneman’s System 1 and System 2 Thinking – Referenced in the discussion on snap decisions, deeper thinking, and productivity fatigue.Pugh Analysis – John mentions this as an example of a prioritization approach originally intended to help experts independently rate options and then discuss differences in judgment.
Follow the HostLinkedIn: https://www.linkedin.com/in/barryoreilly
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Jim Highsmith has been thinking about decision-making for a long time. When he wrote Agile Project Management in 2004, he went looking for practical guidance on decision-making in the project management literature and found very little. That gap matters even more now.
In this episode, Jim and I talk about why AI raises the stakes for executive judgment. AI can remove friction, speed up work, and take on repeatable tasks, but it can also make it easier for leaders to stop practicing the very capabilities they are paid to use. Jim brings this to life through John Boyd’s OODA loop, the risk of judgment atrophy, mountaineering decisions, Rob Hall’s Everest threshold, Phil Knight’s pattern recognition at Nike, and a personal story from Jim’s own time leading a collaborative project team at Nike.
This conversation is really about how leaders build judgment deliberately: by making consequence-bearing decisions, setting thresholds before pressure arrives, creating space for slow thinking, and reflecting honestly on how decisions were made.
Key TakeawaysAI can weaken judgment when leaders stop practicing it: Jim compares the risk to driving an autonomous car: the more the system takes over, the less sharp the driver becomes. AI can remove low-value effort, but leaders still need to practice making consequence-bearing decisions.The OODA loop is mostly about orientation: Jim explains that John Boyd’s edge was not just speed, but his ability to update his mental model quickly. For leaders, the real work is noticing when old assumptions no longer fit the situation.Capability is knowledge plus experience plus judgment: AI can make knowledge easier to access, but it cannot replace the experience of carrying consequences. Judgment develops when people make real decisions, reflect on the outcome, and adjust how they think.Thresholds only work when enforced under pressure: Jim uses Rob Hall’s Everest story to show why decision thresholds matter before emotion, ambition, or sunk cost take over. In business, those thresholds might be cost, risk, customer impact, or reversibility.Leaders need to separate fast decisions from slow judgment: Some repeatable, data-heavy decisions can be automated with guardrails. Higher-context decisions still need human orientation, pattern matching, and time to think.Reflection turns experience into better pattern matching: Barry shares his practice of documenting decisions, what was known at the time, and why the call was made. That kind of review helps leaders improve the decision process, not just judge the outcome.
Additional InsightsRole modeling beats mandates: Jim describes how Boyd taught by showing the mechanics of his performance. Barry connects this to AI adoption: leaders create more movement by sharing how they are using the tools in real work.Productivity fatigue is a real AI-era risk: Barry reflects on how AI can increase output while shrinking the space to think. That matters because senior leadership work often depends on judgment, not just throughput.AI transformation is still a people problem: Jim returns to Jerry Weinberg’s reminder that “no matter what they tell you, it’s a people problem.” Tools help, but organizations still need to redesign the work, behaviors, and decisions around them.Pattern matching is different from gut feel: Jim uses Phil Knight’s Nike decisions to show how instinct can come from years of context. What looks intuitive on the surface is often pattern recognition built through experience.
Episode Highlights00:00 – Episode Recap – Jim Highsmith frames the core tension of the episode: AI can accelerate work, but it can also expose whether leaders have a real decision-making system or are quietly handing judgment to the machine.
01:45 – Guest Introduction – Barry introduces Jim Highsmith, a pioneer of adaptive leadership and original Agile Manifesto signatory whose work has shaped how organizations navigate uncertainty and make high-stakes decisions. (Jim Highsmith)
04:27 – Decision-Making Was Missing from the Playbook – Jim explains that when he wrote his first Agile Project Management book in 2004, he found surprisingly little practical guidance on decision-making in standard project management sources.
05:47 – The Real Power of the OODA Loop – Jim revisits John Boyd’s observe, orient, decide, act model and argues that orientation, the ability to update mental models under pressure, is the part leaders often underdevelop.
07:19 – From Process-Centric to Judgment-Centric Management – Jim makes the case that if AI takes over more process improvement work, organizations need decision-making capacity distributed through the system, not concentrated at the top.
09:14 – The Judgment Muscle Can Atrophy – Barry and Jim use the autonomous car example to show how useful automation can quietly weaken a capability when people stop practicing it.
12:33 – Role Modeling Beats Mandates – Jim explains how Boyd taught fighter pilots by showing the mechanics of superior performance, which Barry connects to leaders demonstrating their own AI experiments instead of simply telling others what to do.
15:50 – Capability Is More Than Knowledge – Jim defines capability as knowledge plus experience plus judgment, pointing out that LLMs can provide knowledge but not the consequence-bearing experience that shapes better calls.
18:56 – Thresholds Keep Decisions Honest – Jim shares the Rob Hall Everest story to show why thresholds only matter if leaders are willing to honor them when pressure, ambition, or sunk cost pushes the other way.
20:58 – Automate the Right Decisions – Jim distinguishes fast, data-dependent System One decisions from slower System Two judgments, giving leaders a practical way to decide what to automate and what to protect.
24:31 – From Search Engine to Human-Agent Teams – Jim describes his own progression from using AI as a search engine to working daily with multiple humans and agents, showing that the practice evolves through use.
27:06 – Productivity Fatigue and Constant Execution – Barry reflects on how AI can create more throughput while leaving less space for slow thinking, especially for leaders whose real value is making judgment calls.
31:05 – Relearning the People Problem – Jim returns to Jerry Weinberg’s reminder that “no matter what they tell you, it’s a people problem,” and Barry connects that to companies buying AI tools without redesigning how people work.
33:21 – Pattern Matching Is Not Gut Feel – Jim uses Phil Knight’s early Nike decisions to explain why seasoned executives often seem intuitive because they have built patterns from industry knowledge, relationships, and lived context.
36:09 – Decision Journaling Builds Better Judgment – Barry describes documenting decisions, the information available, and the rationale at the time as a way to learn from both strong and weak outcomes.
37:22 – A Nike Lesson in Collaborative Judgment – Jim recalls a project decision at Nike where the team agreed with the outcome but challenged the process, giving him a lasting lesson about when people need to be part of the call.
38:51 – Closing Reflections – Barry thanks Jim and points listeners toward his writing as these long-standing ideas about judgment, adaptability, and decision-making become even more relevant in the AI era.
Useful ResourcesJim Highsmith’s website – Jim’s home base for his bio, books, articles, podcasts, and current work. (Jim Highsmith)The Adaptive EDGE – Jim’s Substack on leadership, adaptability, and AI. (jimhighsmith.substack.com)The Agile Manifesto – The original manifesto and signatories list, including Jim Highsmith. (Agile Manifesto)Adaptive Leadership: Accelerating Enterprise Agility by Jim Highsmith – The book Jim references when discussing his earlier work on adaptive leadership and decision-making. (Google Books)Robot-Proof: When Machines Have All the Answers, Build Better People by Vivienne Ming – The book Jim mentions as influencing his thinking about creative human capability in the AI era. (Google Books)Boyd: The Fighter Pilot Who Changed the Art of War by Robert Coram – A deeper look at John Boyd, the OODA loop, and the “40-second Boyd” story discussed in the episode. ( -
AI is changing how work gets done — but more importantly, it’s changing how people understand their value, identity, and ability to navigate uncertainty.
That’s one of the reasons I wanted Chris Walker on the show. Chris has spent years helping companies rethink growth, systems, and organizational performance, but this conversation goes far beyond marketing or AI tactics. Drawing on ideas from his new book The Frequency Era, Chris explores what happens when the work that once made people feel valuable can suddenly be done by AI and automation.
One idea that stood out to me most in this conversation is that decision quality depends less on information and more on the person making the decision's internal state. In a world where AI can accelerate execution and analysis, judgment, discernment, and emotional clarity become increasingly valuable leadership capabilities — the very qualities machines cannot replicate.
Key TakeawaysAI is reshaping identity, not just jobs: Chris explains that many people attach their self-worth to the work they perform. As AI absorbs more execution-based tasks, leaders will need to help teams navigate the emotional disruption that comes with that shift.Judgment becomes more valuable as automation increases: AI can accelerate execution and analysis, but leaders are still responsible for interpreting context, weighing tradeoffs, and making decisions under uncertainty.Decision quality is driven by internal state: Chris argues that calm, present leaders consistently make better long-term decisions under pressure than leaders operating from anxiety or fear.Creativity requires psychological safety: The conversation explores why innovation suffers in environments dominated by pressure and fear, and why teams create better ideas when people feel safe enough to challenge assumptions.Leaders need a compass more than a map: In fast-changing environments, rigid plans become less useful. Adaptability, awareness, and self-trust become more valuable than certainty.
Additional InsightsAI exposes weak leadership systems faster: As AI accelerates execution, unclear decision-making, poor communication, and weak organizational alignment become more visible.Fear changes how people interpret information: Chris explains how anxiety and subconscious patterns can distort communication, amplify uncertainty, and affect leadership behavior.Experienced leaders reduce noise and focus on signal: Barry and Chris reflect on how strong operators simplify complexity and make clear decisions even when conditions are uncertain.Self-awareness becomes a leadership advantage: Understanding personal triggers, assumptions, and subconscious patterns improves both decision-making and interpersonal effectiveness.
Episode Highlights00:00 – Episode Recap
AI is not just changing how work gets done. It is forcing people to rethink identity, judgment, leadership, and the human capabilities that matter most in an uncertain future.
01:42 – Guest Introduction: Chris Walker
Barry introduces Chris Walker, entrepreneur, systems thinker, and author of The Frequency Era, exploring how subconscious patterns shape leadership, performance, and decision-making.
03:23 – Systems Thinking Beyond Marketing
Chris explains how thinking like a CEO and understanding entire systems shaped his approach to business, leadership, and organizational growth.
08:11 – AI Is Elevating Human Capacity
Chris shares the core idea behind The Frequency Era, arguing that AI is not replacing humans but pushing people toward higher-order capabilities like judgment, creativity, and discernment.
10:37 – When Identity Is Tied to Work
The conversation explores why AI feels threatening for many people. Chris explains how attaching identity to specific tasks or roles creates fear and instability during periods of technological change.
14:21 – Judgment Becomes the Competitive Advantage
Barry and Chris discuss why judgment may become the most important human skill in an AI-driven world, especially as people increasingly outsource interpretation and thinking to machines.
18:58 – Calm Leaders Make Better Decisions
Barry reflects on why the best leaders are often the most present under pressure. Chris explains how emotional state directly affects decision quality and long-term outcomes.
20:58 – Creativity Requires Psychological Safety
The discussion shifts toward innovation and team dynamics. Barry and Chris unpack why fear suppresses creativity and how strong leaders create environments where people feel safe to challenge ideas.
24:41 – Emotional Sovereignty and Uncertainty
Chris explains why anxiety, imposter syndrome, and self-doubt should be viewed as trainable patterns rather than permanent traits, especially in periods of rapid change.
26:45 – Leaders Need a Compass, Not a Map
The conversation explores why rigid planning becomes less effective in fast-changing environments and why adaptability, self-trust, and clarity matter more than certainty.
36:03 – The 30-Second Identity Test
Chris shares a simple but revealing exercise that exposes how unclear most people are about their own identity and direction.
39:38 – Defining Your Own Direction
Barry reflects on why intentionality and self-awareness become critical leadership tools during periods of ambiguity and constant change.
41:08 – Closing Reflections on Leadership and Identity
The episode closes with reflections on self-awareness, adaptability, and the kind of leadership needed to navigate the AI era with confidence.
FAQsQ1. What is The Frequency Era about?Chris Walker’s book explores how subconscious patterns, beliefs, and emotional states influence leadership, decision-making, and performance, especially during periods of rapid technological change.
Q2. Why does Chris Walker believe judgment is becoming more important in the AI era?As AI automates more execution-based work, leaders still need to interpret context, evaluate tradeoffs, and make decisions under uncertainty. Judgment becomes a differentiator when information and output are abundant.
Q3. How does AI affect leadership and organizational culture?The episode explains that AI increases the pace of work and exposes weaknesses in communication, trust, and decision-making. Leaders need stronger emotional regulation and clearer principles to guide teams effectively.
Q4. Why is psychological safety important for creativity?Chris and Barry discuss how fear and anxiety limit experimentation. Teams are more likely to produce innovative thinking when people feel safe enough to challenge ideas, make mistakes, and contribute openly.
Q5. What human skills become more valuable as AI advances?The conversation highlights judgment, empathy, ethical reasoning, adaptability, communication, and self-awareness as essential skills that remain difficult to automate.
Useful ResourcesChris Walker’s book: The Frequency Era - https://a.co/d/0aUgBFeU Chris Walker on LinkedIn - https://www.linkedin.com/in/chriswalker171/ Encoded Website - https://www.encoded.ai/ Barry O’Reilly’s book: Artificial Organizations - https://geni.us/artificialorgs
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Incorruptible with Eric Ries
What if the companies that last the longest are the ones building enough trust that people want to keep participating in them? That’s the idea behind this conversation with Eric Ries — entrepreneur, author of The Lean Startup, and now Incorruptible.
Through stories such as Volvo giving away the seatbelt patent, Tony’s Chocolonely opening its ethical supply chain to competitors, and Mary Parker Follett’s idea of the “invisible leader,” we explore how organizations create lasting advantage through trust, shared purpose, and systems that hold together as companies scale.
We also unpack why so many businesses drift toward short-term extraction, what leaders misunderstand about organizational health, and why AI is exposing deeper weaknesses in how companies operate.
If you’re building a company and questioning whether business-as-usual is still the right operating system, this conversation is for you.
Key TakeawaysEthical business can outperform extractive business models: Eric argues that mission-driven companies are not sacrificing performance. In many cases, trust, alignment, and long-term thinking create stronger economic outcomes.Volvo used open ecosystems as strategy: Giving away the three-point seat belt patent helped establish safety as an industry standard while positioning Volvo as the global leader in automotive safety.Tony’s Chocolonely treats its mission as infrastructure: The company’s goal is not simply selling chocolate. Its mission is to eliminate child slavery from the cacao supply chain through systems that competitors can also adopt.Positive externalities can strengthen competitive advantage: Eric explains how companies can create value by improving the broader ecosystem around them instead of maximizing short-term value extraction.Organizations are shaped by invisible leadership: Mary Parker Follett’s idea of the “invisible leader” shows how shared purpose influences decisions when executives are not in the room.Organizational health cannot be commanded: Leaders can issue instructions, but trust, accountability, and commitment have to be cultivated through systems and behavior over time.
Additional InsightsThe current business narrative rewards extraction over durability: Barry and Eric discuss how modern startup culture often glorifies hyper-efficient solo founders, aggressive cost-cutting, and short-term returns while ignoring long-term organizational health.
AI is amplifying leadership weaknesses, not solving them: As companies use AI to accelerate decision-making and productivity, leaders are being forced to confront whether their systems actually create clarity, trust, and aligned behavior.
Mission statements are easy. Mission transmission is harder: Eric argues that values only matter when they shape real decisions, incentives, hiring, product tradeoffs, and customer experience.
Open systems can expand both impact and market position: From Linux and Git to Netflix influencing AWS through open source tooling, the episode explores how sharing infrastructure can strengthen an ecosystem while also benefiting the originating company.
Profit becomes dangerous when it ignores externalities: Eric explains how traditional profit models often fail to account for long-term brand damage, human cost, environmental impact, and deferred liabilities.
Episode Highlights00:00 – Episode Recap
Eric Ries explains why organizations are living systems, not machines to be controlled. Leaders can command action, but organizational health has to be cultivated through purpose, trust, and the systems people use when no one is watching.
00:57 – Barry’s Opening Reflection
Barry connects AI, leadership, and decision-making systems before introducing Eric’s new book, Incorruptible.
02:14 – Guest Introduction: Eric Ries
Barry introduces Eric Ries, entrepreneur, author of The Lean Startup, and author of Incorruptible, framing the conversation around ethical business as a path to long-term prosperity.
04:34 – Researching the Stories Behind Incorruptible
Eric shares how much research went into the book, including the challenge of finding stories that were not just interesting, but genuinely useful for leaders.
08:07 – Volvo and the “Seatbelt Heist”
Eric breaks down how Volvo’s decision to give away the three-point seat belt patent created a prosperity cascade that reshaped the industry while strengthening Volvo’s long-term brand position around safety.
16:45 – Open Source as Strategy
Barry connects Volvo’s story to Netflix and cloud computing, where open sourcing internal tools helped shape the direction of the broader ecosystem.
17:57 – Positive Externalities as Business Strategy
Eric explains why companies often overlook opportunities to create value by improving the wider system around them.
20:18 – Tony’s Chocolonely and Slave-Free Chocolate
Eric tells the story of how a Dutch journalist turned frustration over child labor in cacao production into a fast-growing chocolate company with a much larger mission.
24:03 – Mission Beyond the Product
Tony’s mission is not simply making chocolate. The business exists to eliminate child slavery from the cacao supply chain and align economics with ethical sourcing.
26:00 – Tony’s Open Chain
Eric explains how Tony’s opened its ethical supply chain to competitors while requiring them to commit to the same standards across all their chocolate products.
30:32 – The False Tradeoff Between Ethics and Performance
Eric challenges the business-school assumption that companies must choose between mission and profit, arguing that the data often shows the opposite.
33:23 – Redefining Profit
Barry and Eric discuss why traditional definitions of profit often ignore externalities, deferred liabilities, human cost, and long-term brand damage.
39:19 – The Myth of the Solo Founder
Barry pushes back on modern founder mythology and explains why anything built to last depends on systems, teams, and shared ownership.
40:36 – Mary Parker Follett and the Invisible Leader
Eric introduces management thinker Mary Parker Follett and explains why her ideas about shared purpose and distributed authority were decades ahead of their time.
45:00 – What Guides Decisions When Leaders Aren’t Present
Eric explores Follett’s idea of the invisible leader: the shared sense of purpose that influences behavior when no executive is in the room.
49:35 – Organizations as Living Systems
Eric compares organizations to emergent intelligence systems like ant colonies or the human body, arguing that leaders can cultivate organizational health but cannot directly command it.
52:30 – Closing Reflections
Barry and Eric reflect on the need for new business models that prioritize trust, mission alignment, and long-term value creation over extraction.
Useful ResourcesEric Ries — IncorruptibleEric Ries — The Lean StartupEric Ries on LinkedIn - https://www.linkedin.com/in/eries/ The Eric Ries Show YouTube - https://www.youtube.com/@theericriesshow Barry O’Reilly — Artificial Organizations - https://geni.us/artificialorgs
FAQsQ1: What is Eric Ries’ book Incorruptible about?Incorruptible explores how leaders can build companies that stay aligned with their mission as they grow. Eric looks at stories from business history to show how purpose, governance, incentives, and ownership shape whether companies create long-term value or lose their way.
Q2: Why does Eric Ries use Volvo as an example?Volvo’s three-point seat belt story shows how a company can create value by spreading a mission beyond its own products. By making the patent available to others, Volvo helped establish safety as an industry standard while strengthening its own reputation for safety.
Q3: What is Tony’s Chocolonely trying to change?Tony’s Chocolonely is trying to eliminate child slavery from the cacao supply chain. The company sells chocolate, but the deeper mechanism is building an ethical supply chain that other companies can use through Tony’s Open Chain.
Q4: What does Mary Parker Follett mean by the invisible leader?The invisible leader is the shared purpose that guides people’s decisions when no formal leader is present. It is what shapes behavior in everyday moments, such as how teams handle quality issues, customer problems, or ethical tradeoffs.
Q5: Can leaders... -
Most people think growth comes from doing more—more services, more offers, more complexity. But in this episode, I sit down with Tas Bober, who did the exact opposite. She stripped everything back, focused on one problem, and built a business so clear people can describe it in a single sentence. This conversation is about the courage to simplify—and why that’s far harder (and more powerful) than it sounds.
Tas didn’t plan to become an entrepreneur. After layoffs, burnout, and a side experiment on LinkedIn, she found herself with unexpected demand—but no clear direction. It wasn’t until she made a bold, uncomfortable decision to niche down into landing pages that everything changed. What followed is a masterclass in clarity, positioning, and designing a business that actually fits your life—not the other way around.
Key TakeawaysNiching down creates clarity: Focusing on one problem made it obvious what Tas does—and why clients should choose her.Doing less accelerates growth: Eliminating distractions and context switching improved both quality and income.Clarity beats capability: Being known for one thing is more valuable than being able to do many.Positioning drives inbound demand: Clear positioning meant clients showed up with defined problems—making selling easier.Data should guide decisions: Tracking time revealed which work actually delivered the highest return.Design your business around your life: Tas optimized for time, flexibility, and energy—not scale for the sake of it.
Additional InsightsTrying to do everything can make you lose authority: You shift from expert to order taker.Community accelerates growth: Trusted peers help challenge thinking and shorten the learning curve.Scarcity mindset delays focus: Holding onto everything early can prevent meaningful progress.AI amplifies thinking—it doesn’t replace it: Expertise and nuance still drive better outcomes.Simplicity requires discipline: Even after success, the temptation to expand never goes away.
Episode Highlights00:00 – Episode Recap
Tas shares how narrowing her focus to one specific problem transformed her business, income, and lifestyle.
01:00 – The Accidental Entrepreneur
Tas reflects on being laid off twice and how a side experiment on LinkedIn unexpectedly opened new opportunities.
05:00 – The Struggle of Starting Out
She describes the early chaos of offering everything, underpricing, and trying to figure out what problem she actually solved.
08:30 – The Niching Down Breakthrough
A peer challenges Tas to focus on landing pages—and within a week, everything changes.
12:30 – Why Clarity Wins in Business
Barry and Tas unpack why being known for one thing beats showcasing a wide range of capabilities.
17:00 – The Power of Focused Repetition
Tas explains how working on the same problem repeatedly builds deep expertise and pattern recognition.
20:30 – The Economics of Specialization
Tracking her time reveals a stark difference in earnings between general consulting and niche work.
24:30 – Cutting Everything Else
Tas makes the difficult decision to eliminate all other services and go all-in on landing pages.
26:00 – Resisting the Urge to Expand
Even after success, the temptation to do more returns—and why discipline is required to stay focused.
29:00 – Fast Decisions and Iteration
Tas shares her approach to reversible decisions and rapid experimentation.
31:00 – Building a Values-Driven Business
She discusses choosing clients based on alignment and maintaining an audience-first mindset.
34:00 – The Role of Simplicity in Growth
Barry highlights how clear positioning is often the biggest unlock for entrepreneurs.
36:50 – Designing a Business Around Life
Tas reflects on working three days a week and prioritizing enjoyment and flexibility.
38:00 – AI, Creativity, and Human Insight
Why AI can’t replace nuanced expertise—and how human judgment remains critical.
39:30 – Closing Reflections
A final look at growth, experimentation, and the ongoing journey of building something meaningful.
FAQsQ1. Why is niching down important for business growth?
Niching down creates clarity in your positioning, making it easier for customers to understand what you do and why they should choose you. It also improves inbound demand and simplifies sales conversations.
Q2. Can focusing on one service really increase revenue?
Yes. Specializing allows you to become more efficient, deliver higher-quality results, and charge premium rates—often earning more while working less.
Q3. How do you choose the right niche for your business?
The best niche sits at the intersection of your experience, market demand, and repeatable problems you’ve solved. Testing a niche for a defined period can help validate it quickly.
Q4. What are the benefits of clear positioning in a crowded market?
Clear positioning helps you stand out by making you the first person people think of when they have a specific problem, reducing competition and increasing trust.
Q5. How does specialization compare to using AI tools in business?
AI can support execution, but it lacks the nuanced insight and pattern recognition that comes from deep specialization. Experts who focus on one problem can deliver more valuable and differentiated outcomes.
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Most leaders think AI is a technology shift. It’s not. It’s a behavior shift.
In this episode, I sit down with Melanie Steinbach—former Chief HR Officer at McDonald’s, Cameo, and MasterClass—to unpack what’s actually changing inside organizations as AI becomes embedded in how we work.
Melanie has spent her career solving business problems through people. But she challenges a core assumption: that performance problems are solved by replacing people. Instead, the real leverage comes from coaching, clarity, and creating the conditions for people to do their best work.
We explore why AI doesn’t replace leadership—it exposes it. And what that means for AI leadership and decision-making inside modern organizations. Same tools. Same access. Completely different outcomes. The difference comes down to how leaders think, make decisions, and design systems around their teams.
We also unpack a critical shift most organizations aren’t ready for: redefining what “valuable work” actually means. For years, being busy—and being in meetings—has been treated as a proxy for value. But when AI handles execution, value moves to judgment, context, and decision quality.
If you’re leading teams, navigating transformation, or trying to understand where AI actually fits in your organization, this conversation will change how you think about leadership, work, and performance.
Key TakeawaysSolving business problems through people isn’t about replacement: The real leverage comes from coaching, clarity, and creating the conditions for people to succeed.AI exposes how you lead: The same tools produce radically different outcomes depending on how you think and make decisions.Clarity drives performance: When expectations are vague, even high performers struggle to deliver.Context is now the constraint: Information is everywhere, but leaders create value by helping teams interpret and act on it.Busy work is losing its signal: Meetings and activity no longer define value—decision quality does.AI requires behavior change, not just adoption: The advantage goes to leaders who change how they work, not just what tools they use.Judgment is the differentiator: AI can generate answers, but leaders are still responsible for making the call.
Additional InsightsPerformance problems are often system problems: Most people want to do a good job, but unclear expectations and missing context get in the way.Onboarding is being rebuilt in real time: AI enables “what you need to know, when you need to know it” instead of static training programs.Leadership is shifting from answers to perspective: The value is no longer having information—it’s providing context and nuance.Meetings were a proxy for value: Being busy created the illusion of impact, but that signal is breaking down fast.Work is being unbundled: Roles are no longer fixed—they’re collections of tasks being redistributed between humans and machines.
Episode Highlights00:00 – Episode Recap
Melanie Steinbach reframes how organizations solve business problems, shifting the focus from replacing people to unlocking their potential through clarity, coaching, and better systems.
01:30 – Guest Introduction: Melanie Steinbach
Former Chief HR Officer at McDonald’s, Cameo, and MasterClass, Melanie has led transformation at scale across some of the world’s most recognized organizations.
03:49 – From Replacement to Development
Melanie shares the moment she realized solving business problems through people isn’t about hiring differently—it’s about developing the people you already have.
06:35 – Why People Want to Do a Good Job
Most employees aren’t underperforming by choice—they’re missing clarity, skills, or expectations.
08:24 – The Cost of Missing Clarity
Unclear systems create friction, confusion, and unnecessary failure—even in high-performing environments.
11:18 – Culture Shapes Behavior
In some organizations, asking questions signals curiosity. In others, it signals weakness—and that changes everything.
18:14 – AI Changes How People Learn
Onboarding and development become dynamic, personalized, and driven by real-time needs.
22:02 – From Knowledge to Context
Leadership evolves from delivering information to helping teams interpret and apply it effectively.
24:41 – Presence Becomes a Superpower
AI reduces cognitive load, allowing leaders to show up focused, prepared, and ready to make decisions.
28:06 – Why Humans Still Matter
Technology amplifies systems, but judgment, meaning, and connection remain human.
32:00 – Rethinking Valuable Work
Being busy is no longer proof of impact—decision quality is.
35:16 – A New Metric for Performance
High-quality decisions—made faster with better context—become the new standard.
38:58 – Thinking Is the New Advantage
Creating space to think clearly becomes one of the most valuable leadership skills.
41:55 – Work Is Being Redefined
Jobs are breaking into tasks, with AI handling execution and humans focusing on judgment.
42:33 – Why This Moment Matters
Melanie shares why she’s stepping in to help organizations navigate this shift across industries.
44:04 – Closing Reflections
This isn’t a small shift—it’s a fundamental redesign of how work gets done and how leaders create value.
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AI isn’t changing the game—it’s exposing how you think. In this episode, I sit down with Misty Shafer Sterne, Vice President of Commercial Technology at American Airlines, to explore what it really takes to lead with AI inside a complex, high-stakes organization. We go beyond the usual productivity narrative and dig into something far more powerful: how AI can sharpen decision-making, surface better questions, and help leaders operate with greater clarity and intent.
Misty shares her journey from chasing efficiency to building a personal system for thinking—using AI as a partner to capture ideas, pressure test decisions, and improve how she shows up as a leader. We also unpack why experimentation matters more than metrics early on, how to avoid automating broken processes, and what it looks like to lead in the open so teams can follow. This is a conversation about performance, not productivity—and what it means to truly unlearn how we work.
Key TakeawaysAI amplifies how you think: The real advantage isn’t speed but improving clarity, judgment, and decision-making quality.Productivity is just the entry point: The biggest gains come from using AI to enhance performance, not just efficiency.Experimentation must come before measurement: Over-indexing on productivity metrics too early can shut down innovation.Leaders must unlearn being the “answer person”: Great leadership shifts toward asking better questions rather than having all the answers.Decision velocity matters more than idea volume: Success comes from quickly identifying which ideas are worth pursuing, not generating more ideas.
Additional InsightsAI as a thinking partner: Misty’s breakthrough came when she used AI to pressure test ideas instead of manage tasks.Externalizing thinking creates clarity: Capturing raw, messy thoughts helps reveal patterns and improve decision-making.Your thinking becomes a reusable asset: AI enables leaders to build a system that stores and evolves their ideas over time.Automating bad processes makes them worse: AI should be used to redesign workflows, not just accelerate existing inefficiencies.Leadership requires learning in public: Vulnerability and visible experimentation help drive adoption across teams.
Episode Highlights00:00 – Episode Recap
A shift from chasing productivity to unlocking better thinking transforms how leaders use AI—turning it into a true decision-making partner rather than just a tool.
02:00 – Guest Introduction: Misty Shafer Sterne
Barry introduces Misty, VP of Commercial at American Airlines, leading AI-driven decision-making across pricing, customer experience, and revenue.
04:25 – From Perfection to Curiosity
Misty reflects on her journey from needing all the answers to embracing vulnerability and asking better questions as a leader.
07:45 – The Productivity Trap
Early AI use focused on inbox management and efficiency, but Misty realized this wasn’t where real value lies.
09:30 – AI as a Thinking Partner
Using AI to externalize thoughts, identify patterns, and pressure test ideas unlocks a new level of clarity and decision-making.
12:30 – Performance Over Productivity
The real benefit of AI is improving how leaders show up, think, and collaborate—not just getting more done.
15:15 – Capturing Ideas Before They’re Lost
Verbal processing and real-time capture help preserve insights and connect ideas over time.
18:18 – Building a System of Thinking
Accumulating ideas creates a long-term asset that helps leaders identify patterns and improve decisions.
21:25 – Why Experimentation Needs Space
Over-measuring productivity too early can limit exploration and reduce the potential of AI adoption.
24:33 – Context Matters in Decisions
Capturing why decisions were made enables better future judgment as conditions change.
29:04 – Leading by Example
Misty shares how modeling experimentation helped shift her organization from fear to adoption.
33:40 – The Danger of Automating Bad Processes
AI can amplify poor systems—leaders must rethink workflows, not just speed them up.
36:03 – Redesigning Work for Better Outcomes
True transformation comes from changing behavior and systems, not just adopting tools.
38:45 – Unlocking Ideas Across the Organization
AI democratizes innovation, requiring leaders to step back and let the best ideas emerge from anywhere.
FAQs1. What is the biggest mistake leaders make when adopting AI?
Focusing too much on productivity metrics early on instead of creating space for experimentation and learning.
2. How should leaders actually use AI in their daily work?
As a thinking partner—to capture ideas, pressure test decisions, and improve clarity, not just automate tasks.
3. What does “decision velocity” mean?
It’s the ability to make faster, higher-quality decisions with confidence by using better information and structured thinking.
4. Why is experimentation so important in AI adoption?
Because the real value emerges through exploration—rigid expectations can limit discovery and innovation.
5. How can leaders avoid damaging their teams when introducing AI?
By leading with transparency, modeling behavior, and ensuring AI enhances collaboration rather than creating pressure or fear.
Useful ResourcesMisty Shafer on LinkedInAmerican Airlines on LinkedInAmerican Airlines WebsiteArtificial Organizations by Barry O’ReillyBrené Brown – “Rumbling” and leadership frameworks
Follow the HostLinkedIn: https://www.linkedin.com/in/barryoreillyPersonal site: https://barryoreilly.comFacebook: https://www.facebook.com/barryoreillyauthor/Twitter: https://x.com/barryoreillyInstagram: https://www.instagram.com/barryoreilly/
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What role should businesses play in society today?
In this episode of the Unlearn Podcast, I sit down with investor, ecosystem builder, and Foundry Group co-founder Seth Levine to explore how capitalism itself may be evolving. Seth’s latest book, Capital Evolution, examines a fundamental question: can modern capitalism create broader opportunity, stronger communities, and more inclusive ownership?
Our conversation ranges from declining economic mobility and generational uncertainty to the role of values-driven companies and the rise of AI-powered work. We also dive into how leaders can navigate uncertainty—balancing profit, purpose, and technological disruption.
Along the way, Seth shares how a single dinner conversation sparked a two-year research journey, interviewing more than 100 leaders, academics, and entrepreneurs to understand where capitalism may be headed next.
This conversation also builds on ideas we’ve explored before on the podcast—particularly with Seth’s long-time collaborator Brad Feld. In our earlier discussion on Give First leadership, Brad challenged the idea that success comes from extraction, instead arguing that generosity, long-term thinking, and community building are the real drivers of sustainable impact. Together, these conversations offer a powerful lens on how leadership, capitalism, and value creation are being redefined.
If you’re thinking about the future of work, leadership in an AI-powered world, or how organizations can create both economic and societal value, this episode will challenge some assumptions.
Key TakeawaysCapitalism is already evolving: Many leaders still operate as if we’re in a shareholder-first world—but that model has already shifted. Businesses now face growing pressure to balance profit with broader societal impact.Economic mobility is declining: While economies continue to grow in aggregate, fewer people are able to move up financially. This shift is reshaping how younger generations view opportunity and fairness.Values-driven companies are becoming more visible: Organizations like Patagonia, Hobby Lobby, and Chick-fil-A show that companies can operate with clear values. What matters most is transparency—being honest about what the organization stands for.AI is changing how leaders work: Seth describes using AI tools like Claude as an operating system for his daily work—drafting ideas, exploring questions, and accelerating thinking. Leaders who combine human judgment with machine intelligence can dramatically increase their effectiveness.Curiosity and listening are leadership superpowers: One of Seth’s biggest lessons from writing the book was the value of listening to perspectives outside his own experience. Engaging with different viewpoints reveals insights leaders often miss.
Additional InsightsThe danger of misleading economic averages: Seth describes the “Jeff Bezos walks into a bar” problem—where averages distort reality. Aggregate growth can hide widening inequality and declining mobility.The difference between values and politics in business: Companies should be clear about their values—but that doesn’t mean every company needs to take political positions. Transparency builds trust with employees, investors, and customers.Why younger generations feel uncertain: Many are entering a world shaped by rapid technological change, rising costs of living, and shifting job markets. AI both excites and worries people about what work will look like.AI rewards experimentation: The people benefiting most from AI are those who continuously experiment. Treating AI as a collaborator—not just a tool—opens entirely new ways of working.
Episode Highlights00:00 – Episode Recap
Seth Levine reflects on the changing nature of capitalism and why declining economic mobility, shifting values, and AI-driven disruption are forcing leaders to rethink how businesses create value for society.
02:40 – Guest Introduction: Seth Levine
Barry introduces Seth Levine, co-founder and partner at Foundry Group, entrepreneur advocate, and author of Capital Evolution, a book exploring how capitalism can evolve to create broader opportunity.
05:00 – The Dinner Conversation That Sparked a Book
Seth describes the boardroom conversation that sparked the idea behind Capital Evolution—a question about whether investors would accept lower returns in order to live their values.
07:53 – Why the Capitalism Debate Is Growing
Research for the book revealed that roughly half of people under 40 believe capitalism isn’t working—prompting a deeper exploration of how the system might evolve.
10:33 – Values-Driven Businesses in Practice
Examples like Patagonia and Hobby Lobby show how companies can operate with strong values while still pursuing business success.
19:14 – Generational Anxiety About the Future
Younger generations face growing uncertainty about careers, technology disruption, and economic opportunity.
23:38 – Learning From Different Perspectives
Travel, conversations, and research helped Seth recognize how limited our understanding can be when we stay within familiar social and professional circles.
29:30 – Experimenting With AI at Work
Seth shares how tools like Claude have become part of his daily workflow—helping him explore ideas, draft writing, and accelerate thinking.
33:38 – Why AI Feels Exciting Again
After decades in venture capital, Levine says experimenting with AI tools has reintroduced a sense of novelty and curiosity into his work.
40:51 – The Pattern of Every New Technology
From automobiles to AI, every major technological shift initially sparks fear before becoming normalized.
42:07 – A Simple Leadership Habit: Listen More
Seth encourages leaders to actively seek conversations with people who hold different perspectives—and listen without trying to persuade.
45:00 – Closing Reflections
Barry wraps the conversation, highlighting the importance of curiosity, experimentation, and openness as leaders navigate the evolving relationship between business, society, and technology.
FAQsQ1. What is Capital Evolution and why is it important?Capital Evolution describes how capitalism is shifting beyond a shareholder-first model toward creating broader societal value. It’s important because businesses are now expected to balance profit with impact, ownership, and community outcomes.
Q2. Why is economic mobility declining today?Economic mobility is declining because wealth and opportunity are increasingly concentrated. Even as economies grow overall, fewer people can move up income levels, making it harder for younger generations to improve their financial position.
Q3. What role should businesses play in society today?Businesses should generate profit while also contributing to society through clear values, responsible decision-making, and long-term thinking. The most effective companies align economic success with positive societal impact.
Q4. How is AI changing leadership and the future of work?AI is transforming leadership by enhancing decision-making and productivity. Leaders who combine human judgment with AI tools can move faster, process more information, and make better strategic decisions.
Q5. Why are younger generations questioning capitalism?Younger generations are questioning capitalism due to rising living costs, job uncertainty, and reduced economic mobility. These challenges make traditional systems feel less fair and less effective than in the past.
Useful Resources:Seth Levine on LinkedIn - https://www.linkedin.com/in/sethjlevine/ Foundry Website - https://foundry.vc/ Seth Levine Book: Capital Evolution - https://www.amazon.com/Capital-Evolution-New-American-Economy/dp/1637747780 Unlearn Episode 160 with Brad Feld - https://barryoreilly.com/explore/podcast/give-first-leadership-brad-feld/
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AI can now generate code in seconds. Deployment pipelines are faster than ever. And yet, many teams still feel slow.
In this episode, I sit down with Nicole Forsgren, world-renowned researcher, co-author of Accelerate, and Senior Director of Developer Intelligence at Google. We explore why speed alone doesn’t create performance — and how hidden friction inside systems, culture, and decision-making quietly holds teams back.
Nicole breaks down the SPACE framework, explains why activity metrics create blind spots, and challenges leaders to rethink what productivity really means in the era of AI agents. If you're measuring output but still not seeing impact, this conversation will help you recalibrate.
Key TakeawaysProductivity is multidimensional, not just output: Measuring activity alone creates blind spots. Real performance includes satisfaction, quality, collaboration, and flow.System constraints determine team speed: Improving individual teams isn’t enough. Performance improves only when bottlenecks across the entire value stream are addressed.AI accelerates existing systems: Automation increases throughput, but it doesn’t remove friction. Weak processes and structural gaps become more visible as speed increases.Trust becomes a performance factor in AI workflows: As agents contribute to development, validation systems, guardrails, and confidence mechanisms become essential.Strategy must come before acceleration: Building the wrong thing faster does not create value. Leaders must define direction before optimizing delivery.
Additional InsightsOrganizations scrutinize AI more than human decisions: We often ask whether AI is producing the right output. Yet we rarely question whether human teams are building the right thing either.AI forces leaders to clarify judgment: Working with agents requires teams to make their assumptions explicit by defining heuristics, edge cases, and decision rules that previously lived in intuition.Many bottlenecks are decision bottlenecks: Delays often come from postponed decisions, including security reviews, approvals, and quality checks placed late in the workflow.AI exposes the limits of existing infrastructure: Faster development cycles put pressure on testing systems, CI/CD pipelines, and operational workflows designed for slower environments.
Episode Highlights00:00 – Episode Recap
Even as AI accelerates development, many teams feel slower than ever — revealing that friction isn’t about code speed but about how systems, culture, and decisions are designed.
02:38 – Guest Introduction: Nicole Forsgren
Barry introduces Nicole Forsgren — researcher, co-author of Accelerate, and Senior Director of Developer Intelligence at Google — whose work has redefined how technology performance is measured.
07:08 – The SPACE Framework Explained
Nicole breaks down Satisfaction, Performance, Activity, Communication, and Efficiency — a practical guardrail to measure productivity across multiple dimensions.
10:19 – Why Optimizing Locally Creates Bottlenecks
Teams often improve within their own scope, only to worsen constraints elsewhere in the system. Real performance requires zooming out.
12:37 – Simple Surveys That Surface Hidden Friction
A few focused questions can quickly reveal productivity barriers — especially when frequency of disruption is measured alongside frustration.
15:51 – Culture, Curiosity, and System Design
Most structural problems come from rational past decisions. Approaching friction with curiosity — not blame — creates safety and clarity.
18:07 – Moving Decisions Upstream
From flaky tests to security reviews, many delays are postponed decisions. The opportunity is shifting confidence-building earlier in the workflow.
22:18 – Making Implicit Judgment Explicit
AI agents force leaders to articulate the heuristics and assumptions they previously ran on instinct — improving both human and machine judgment.
25:48 – Are Humans Building the Right Thing?
We question AI correctness — but rarely apply the same scrutiny to human output. Strategy clarity remains a leadership responsibility.
30:01 – AI Amplifies Existing Bottlenecks
As agents increase throughput, weaknesses in pipelines, testing, and infrastructure become more visible — and more urgent.
32:05 – Removing Friction to Unlock Real Performance
True competitive advantage comes from redesigning systems of work — not just accelerating output.
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AI isn’t about productivity. It’s about presence.
In this special episode, the tables turn and I’m interviewed by Sham Colegado about my new book, Artificial Organizations. We explore why 95% of AI projects fail, why executives don’t want more tools — they want their life back — and how the real competitive edge isn’t automation, but judgment at speed.
If you’ve been overwhelmed by the explosion of AI tools or unsure where to start, this episode will help you reframe the conversation. This isn’t about doing more. It’s about deciding better — faster, with clarity and confidence — by combining human instinct with machine intelligence.
Key TakeawaysAI Used Only for Productivity Fails: When AI is treated as a cost-cutting tool instead of a transformation system, it rarely creates lasting value.Presence Is the Real Advantage: The goal isn’t more output. It’s showing up calmer, clearer, and better prepared — so decisions improve.Decision Velocity + Decision Advantage Wins: Make decisions faster and with better information. Speed without clarity is noise. Clarity without speed is stagnation.The Future Belongs to Human + Machine Judgment: Executives who combine instinct with machine intelligence will outperform those relying on either alone.
Additional InsightsExecutives Don’t Want More Tools — They Want Their Life Back: Leaders aren’t overwhelmed by lack of tools. They’re overwhelmed by fragmented workflows, constant context switching, and decision fatigue. AI must reduce cognitive load, not add to it.Presence Drives Performance: When AI handles capture and synthesis, leaders show up calmer, more prepared, and more focused. Productivity improves — but performance and clarity are the real unlock.The Identity Threat of AI: Many executives privately fear incompetence. They don’t want to look behind or uninformed. That hesitation often shows up as skepticism or avoidance.Decision Velocity Is the New Differentiator: Artificial organizations move faster because they reduce decision latency. Meetings become focused. Context is pre-loaded. Choices are made with confidence.Traits + Tasks + Tools (T3 Model): Start with how you naturally work best. Then amplify your highest-leverage tasks with the right tools.Capture, Transcribe, Synthesize, Act: A simple workflow that turns every conversation into a reusable data asset. This loop compounds judgment and accelerates learning over time.
Episode Highlights00:00 – Episode Recap
Barry explains why AI used purely for productivity fails — and why the real advantage comes from transforming how leaders make decisions.
02:58 – Guest Introduction: Sham Colegado
Barry welcomes Sham Colegado, a key member of the Artificial Organizations team, who interviews Barry about the book and its core ideas.
03:32 – “Executives Don’t Want More AI Tools”
Barry shares the personal burnout moment that sparked a shift from productivity chasing to rethinking how he works.
06:02 – AI’s Real Promise: Presence Over Productivity
Why performance and clarity matter more than output — and how AI can make leaders calmer and more focused.
09:30 – The Identity Threat of AI
Executives reveal a hidden fear of incompetence and why one-on-one learning environments matter.
12:26 – Decision Velocity & Decision Advantage
The two engines of artificial organizations and how reducing decision latency compounds competitive advantage.
15:15 – The Traits, Tasks, Tools Flywheel
How aligning natural strengths with high-leverage work determines which AI tools actually create impact.
19:01 – What the Best AI Adopters Do Differently
Curiosity, experimentation, and comfort with discomfort separate leaders who accelerate from those who stall.
22:46 – The First Workflow to Build
Capture → Transcribe → Synthesize → Act — a simple loop that transforms meetings into strategic assets.
26:05 – The Executive of the Future
The most valuable leaders won’t rely on instinct alone — they’ll pair judgment with machine intelligence to make better decisions faster.
Useful ResourcesArtificial Organizations (Book) – https://artificialorganizations.comBarry O’Reilly – https://barryoreilly.com
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What if success isn’t about scaling faster, shipping more, or chasing perfection — but about building something so honest it can last for generations?
In this episode, I sit down with Gerry Khouri, Founder & Managing Director of Bufori, one of the world’s longest-running handcrafted automobile companies. For nearly 40 years, Gerry has gone against almost every rule of modern business — choosing craftsmanship over scale, long-term thinking over short-term returns, and integrity over imitation.
We explore what Gerry had to unlearn to stay in the game for decades: the myth of perfection, the pressure of shareholder expectations, and the idea that success must look a certain way. This conversation is a masterclass in leadership, product thinking, and building businesses that endure.
Key TakeawaysPerfection is a fantasy — luxury is honesty. Products that last are built on integrity, not impossible standards.Success starts with finishing, not selling. The real win is building something real — everything else is a bonus.Craftsmanship scales through capability, not volume. Deep skills create optionality and diversification.The real competition isn’t the market — it’s yourself. Long-term builders focus on self-mastery, not rivals.Great businesses are built by people who challenge you, not agree with you.
Additional InsightsGerry built his first car in a garage behind his house — bigger than the house itself — with no external funding.Bufori operates debt-free after nearly 40 years, an extreme outlier in modern manufacturing.The company makes more parts in-house than most car manufacturers, turning necessity into innovation.What started as survival-driven resourcefulness became multiple profit centers through engineering services.Leadership longevity comes from unlearning ego, listening deeply, and leading by example.
Episode Highlights00:00 – Episode Recap
Gerry Khouri reflects on a pivotal realization: perfection doesn’t build lasting products — honesty, craftsmanship, and long-term thinking do. This mindset reshaped how he built cars, teams, and a business designed to outlive him.
02:15 – Guest Introduction: Gerry Khouri
Barry introduces Gerry Khouri, founder of Bufori, a handcrafted automobile company that has spent nearly four decades defying the rules of modern manufacturing.
04:14 – Building the First Car Against All Odds
Gerry shares how a backyard hobby, relentless passion, and going against everyone’s advice led him to build his first car from nothing.
07:10 – Redefining What Success Really Means
Success wasn’t about money or validation — it was about starting something and finishing it, no matter the odds.
11:54 – Leading Without Resources
With no books, no mentors, and no capital, Gerry explains how necessity forced invention and deep mastery of craft.
19:50 – Unlearning Perfectionism in a Luxury Business
Why perfection is an illusion, and how focusing on luxury, durability, and intention keeps products moving forward.
23:12 – What Craftsmanship Actually Looks Like
Gerry breaks down what it means to truly “make” a product — from designing for repairability to building for generations.
27:29 – Competing With Yourself, Not the Market
The most dangerous competitor isn’t another company — it’s complacency and losing the hunger to improve.
31:10 – Unlearning Shareholder-First Thinking
Why prioritizing short-term financial returns can destroy long-term craftsmanship and culture.
35:07 – Turning Internal Capabilities Into New Businesses
How Bufori transformed hard-earned internal skills into diversified engineering services.
38:10 – Advice for Founders Scaling Passion Projects
Dream big, be honest with yourself, ignore the noise — and don’t fear hard work or criticism.
42:54 – Building Teams That Challenge You
Why great leaders surround themselves with people who tell them what they need to hear, not what they want to hear.
FAQsWhat does it mean to unlearn perfectionism in product building?
Unlearning perfectionism means letting go of the belief that products must be flawless before they can be shipped. In this episode, Gerry Khouri explains why progress, honesty, and durability matter more than chasing an impossible standard of perfection.
How do you build products that last for decades?
Gerry shares that long-lasting products are built through craftsmanship, attention to detail, and designing for repairability and longevity — not speed, shortcuts, or mass production.
Who is Gerry Khouri and why is he notable?
Gerry Khouri is the founder of Bufori, a handcrafted automobile company that has operated for nearly 40 years. He’s known for building bespoke luxury cars by hand and for leading a debt-free business focused on long-term value.
Is perfectionism bad for startups and founders?
Perfectionism can become a liability when it slows decision-making, delays launches, or prevents learning. Gerry explains how redefining excellence allowed him to keep building while maintaining extremely high standards.
What does long-term thinking in business actually look like?
Long-term thinking means designing products, teams, and systems to endure — focusing on durability, skills, culture, and customer trust rather than quarterly results or fast exits.
Useful ResourcesGerry Khouri on LinkedIn - https://www.linkedin.com/in/gerry-khouri-08507788/ Bufori Motor Cars Website - https://bufori.com/
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LinkedIn: https://www.linkedin.com/in/barryoreillyWebsite: https://barryoreilly.comTwitter (X): https://x.com/barryoreillyInstagram: https://www.instagram.com/barryoreilly/Facebook: https://www.facebook.com/barryoreillyauthor/
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From graduate engineer to CTO, Andrew Phillips’ 16-year journey at Skyscanner is a story of continuous reinvention. He didn’t chase titles—he chased growth, deliberately stepping out of his comfort zone and unlearning the habits that no longer served him. What’s kept him at the company for over a decade isn’t status, but challenge: new teams, unfamiliar problems, and the chance to stay close to the work, even as his scope of leadership expanded.
In this episode, we explore how Andrew is now applying that same mindset to leading in the AI era—personally and professionally. He shares how he’s built a personal AI stack to stay more present, how Skyscanner is blurring traditional team roles to unlock speed, and why “directed autonomy” is more important than ever. For leaders navigating scale, technology, and the desire to make meaningful impact without burning out, Andrew offers a powerful perspective.
Key TakeawaysGrowth through discomfort: Andrew’s biggest accelerations came from switching roles and leaving his comfort zone—not climbing a predefined ladder.AI as a leadership enabler: He uses AI tools to be more present, thoughtful, and effective—especially during high-stakes meetings.From feature factory to outcome focus: Leaders must reconnect people to impact, not just output.Directed autonomy: Empowering teams with AI means giving clear goals—not micromanaging the execution.Unlearning process overreach: Traditional roles, ticketing systems, and rigid handoffs are ripe for reinvention in AI-native organizations.
Additional InsightsThe personal AI stack Andrew uses includes ChatGPT, Otter, Cursor, and SpecKit—enabling him to ideate on walks, build apps during board meetings, and maintain strategic presence.Skyscanner’s senior engineers are back coding, using AI to close the gap between architectural thinking and execution.AI-driven productivity unlocks don’t just mean faster work—they mean better work-life balance, deeper engagement, and more human leadership.
Episode Highlights00:00 – Episode Recap
Andrew Phillips shares how stepping into uncertainty—and building his own AI stack—transformed his leadership at Skyscanner. From personal growth to organizational reinvention, he’s leading the charge on what modern technology leadership looks like.
01:35 – Guest Introduction: Andrew Phillips
Barry introduces Andrew Phillips, CTO of Skyscanner, reflecting on their 15-year relationship and Andrew’s rise from graduate engineer to technology leader.
05:45 – The One Trick Pony Moment
Andrew recalls the pivotal moment when a CEO challenged him to move teams and stop playing it safe—triggering his real leadership evolution.
12:33 – Starting with Yourself in AI
Before transforming your company with AI, Andrew urges leaders to start by experimenting personally and learning from the ground up.
15:15 – Writing Better Prompts, Building Better Specs
AI tools thrive on clear direction. Andrew realized that better prompting and crisp product requirements accelerated his results dramatically.
20:01 – Directed Autonomy in the AI Era
Giving AI tools (and people) the “why” rather than micromanaging the “how” builds trust, speed, and better outcomes.
24:56 – Parallel Productivity and Boardroom Apps
How Andrew built an entire app—during a board meeting—by offloading work to AI and staying fully present in the room.
27:13 – Reclaiming Work-Life Balance
AI allows Andrew to unload his mental backlog—using voice notes and assistants so he can be more present at home.
31:21 – Avoiding the AI Cost Trap
Not every solution needs an LLM. Andrew shares how Skyscanner balances innovation with cost and pragmatism.
36:58 – Blurring the Lines Between Roles
Designers writing code, engineers making design tweaks—Andrew explains why role flexibility is a hallmark of high-performing, AI-native teams.
42:32 – Unlearning the Process Fetish
It’s time to rethink JIRA tickets, handoffs, and audits. In a machine-collaborative world, many processes should be automated or eliminated.
43:36 – The CTO’s Excitement for the Next Quarter
Andrew sees a future where everyone—from architects to senior ICs—is back building again, connected to outcomes, not just output.
46:36 – Closing Reflections
Leadership is about presence, purpose, and people. Andrew shares his optimism for what’s possible when teams are empowered to ship and grow.
FAQsQ1. How is Skyscanner using AI internally?
Teams are using tools like Cursor, ChatGPT, and SpecKit to prototype faster, write code, and automate workflows—blurring traditional role boundaries.
Q2. What is “directed autonomy” and why does it matter?
Directed autonomy means giving teams (and AI) clear goals and guardrails while allowing freedom in how outcomes are achieved. It increases speed, trust, and creativity.
Q3. What does Andrew mean by “blurring the lines between roles”?
At Skyscanner, designers are fixing front-end issues, engineers are influencing product direction, and architects are coding again—enabled by AI tools that lower technical barriers.
Q4. What AI tools does Andrew personally use?
Andrew’s AI stack includes ChatGPT, Cursor, SpecKit, and Otter—used for building apps, drafting comms, and capturing ideas while on the move.
Q5. How does AI help leaders stay present?
By offloading execution to AI (like building apps during meetings or drafting emails from voice notes), leaders can stay focused in key moments and reduce context switching.
Useful ResourcesSkyscannerCursor – AI pair programming toolOtter.ai – Voice transcription and meeting notesBarry O’Reilly’s AI Executive Coaching
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What if machines could truly see and understand how we move? In this episode, I sit down with Sherry Shang, CEO and co-founder of Neural Lab, a company reimagining how we interact with technology through visual intelligence AI and gesture-based interfaces.
Sherry’s journey from Intel technologist to startup founder began with a pivotal moment during the pandemic. What started as a side project in her living room became Neural Lab—a platform that turns basic webcams into powerful tools for gesture recognition, with no specialized hardware required.
Now, Neural Lab is unlocking new ways to deliver care, boost performance, and support human potential. From sterile surgery rooms to personalized rehab and coaching, touchless interaction is creating fresh possibilities for how we live and work with AI.
Key TakeawaysComputer vision is gaining eyes: Sherry frames visual intelligence as the “missing sense” in AI—complementing language models with sight.Entrepreneurship is about timing: Sherry waited until her kids were older to build Neural Lab, choosing to innovate on her own terms.Gesture recognition is real—and ready: Neural Lab’s technology translates hand motions into universal commands with no need for specialized hardware.Human-centered design is essential: From recognizing intentional gestures to modeling real-world physicality, their design is inspired by how humans naturally interact.Healthcare leads the way: Use cases like sterile surgical environments are proving to be strong early markets for gesture control.
Additional InsightsVisual intelligence is the missing sense in AI: Sherry describes computer vision as adding "eyes" to AI, enabling machines to interpret physical space just as large language models allow them to process language.Entrepreneurship is about timing: Sherry chose to start Neural Lab once her children were older, aligning her professional ambitions with personal priorities.Gesture recognition is real—and ready: Their product works with any basic camera and translates 15 customizable gestures into commands for existing applications—no new hardware required.Designing for human nuance matters: Neural Lab focuses on distinguishing intentional from unintentional gestures using cues like eye gaze and body motion—mimicking how humans communicate.Healthcare is an urgent use case: Environments like surgery rooms benefit immediately from touchless interaction, helping maintain sterility and reduce unnecessary patient radiation.The interface is evolving beyond the mouse: Sherry sees gesture-based interaction as a more natural, immersive input method—moving us beyond traditional tools like keyboards and mice.Customer feedback drives innovation: From live demos to direct use-case discovery, Neural Lab adapts based on what real users need and how they react in context.AI can coach, not just compute: Sherry envisions AI-enabled coaching in sports, physical therapy, and even surgery—delivering expert guidance in real time, at scale.
Episode Highlights00:00 – Episode Recap
Sherry Chang shares how her journey from Intel technologist to founder of Neural Lab began with a desire to create immersive, meaningful technology—and a pivotal moment during the pandemic when gesture-based interaction suddenly became essential.
02:14 – Guest Introduction: Sherry Chang
Barry introduces Sherry Chang, CEO of Neural Lab, former Intel leader, and innovator in computer vision and immersive interaction.
06:27 – Starting Up During the Pandemic
Sherry shares how the idea for Neural Lab came to life in her living room, driven by a vision for safer, touchless human-computer interaction.
09:30 – From Prototype to Minority Report
Barry recalls early demos that felt like science fiction—using just a webcam to control computers with hand gestures.
12:00 – Designing for Intentionality
Sherry explains the challenge of recognizing intentional vs. accidental gestures—and how eye-gaze and motion patterns help filter noise.
14:57 – Gesture as Input Device
They discuss how gestures open new interaction possibilities—from whiteboards to evaluating athletic movements.
18:26 – Finding Product-Market Fit in Healthcare
Sherry shares insights from radiology conferences—surgeons see immediate value in touchless interfaces for sterile environments.
22:21 – Reimagining Clinical Workflows
Gesture-based interaction eliminates the need for voice commands or assistants in the OR—streamlining workflow and reducing risks.
25:35 – The Bigger Picture
Barry reflects on the paradigm shift—freeing people from fixed tools like keyboards to interact with tech naturally.
28:56 – Unlocking Human Potential with AI Coaching
Sherry envisions AI coaches for physical therapy, sports, even surgery—democratizing access to expert feedback and improving outcomes.
33:11 – The AI Augmentation Mindset
Rather than replacing jobs, gesture-based AI enhances human performance and creativity, enabling new ways of working.
35:21 – Closing Reflections
Barry highlights the promise of technologies like Neural Lab—empowering people to interact more intuitively with machines and unlock new capabilities.
FAQsQ1. What is gesture recognition technology?
Gesture recognition uses computer vision to detect and interpret human body movements—like hand gestures—as input commands to control software or devices.
Q2. How does Neural Lab's gesture control work?
Neural Lab’s system uses any standard camera to detect 15 configurable gestures, translating them into commands compatible with most applications—no special hardware needed.
Q3. Is gesture recognition practical in healthcare?
Yes. Surgeons can use gestures to manipulate images mid-procedure without breaking sterility, improving workflow and reducing radiation exposure.
Q4. Can gesture-based AI help in physical therapy?
Absolutely. It enables real-time coaching, posture correction, and progress tracking for rehab patients—making at-home therapy more effective.
Q5. How is AI augmenting human potential with this tech?
By combining visual intelligence with feedback loops, gesture-based AI allows for elite-level coaching and real-time assistance in fields like sports, surgery, and workplace ergonomics.
Useful ResourcesNeural Lab Official Site - https://neural-lab.com/Connect with Sherry on LinkedIn - https://www.linkedin.com/in/sherryschang/
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Today’s guest is someone I first came across on the Irish People in VC list—and I’m really glad I reached out. Because it turns out Maureen Haverty has one of the most fascinating jobs you can imagine: helping build the future of space. As a Principal at Seraphim Space, the world’s leading space-focused VC firm, she invests globally in technologies pushing the boundaries of what’s possible —and shaping the future of space startup investment.
Maureen began her career in nuclear engineering, earning a PhD from the University of Manchester before making the leap into startups. At Apollo Fusion, she survived a hard pivot into space, ultimately becoming COO and steering the company through a $150M acquisition by Astra. That experience—what she calls a startup “baptism by fire”—now informs how she backs early-stage founders as both investor and board director. Her insights have been featured in The Times, and she’ll soon take the stage at Web Summit to speak on “Space as a Strategic Frontier.”
Key Takeaways“Build just enough”: Space startups win by testing early and often, not waiting for perfection.Kill fewer dreams: Rigor matters—but so does nurturing half-formed ideas.Get to space ASAP: In-orbit validation creates trust and unlocks massive growth.From Gantt charts to fast loops: High-performing teams test weekly, not quarterly.Customer conversations still matter: Even in space, talking to users beats assumptions.
Additional InsightsWhy VC funding in space is shifting toward earlier MVPs.The hidden costs of acquisition for startup culture and speed.How Starship may reshape what's possible—size, cost, and assembly in orbit.The role of government contracts in fostering a competitive space ecosystem.
Episode Highlights00:00 – Episode Recap
Maureen Haverty shares how balancing rigor with creativity helped her evolve from nuclear engineer to space startup COO to VC. The key? Learning when to test, when to build, and when to let wild ideas breathe.
01:35 – Guest Introduction: Maureen Haverty
Barry introduces Maureen Haverty, Principal at Seraphim Space and advocate for grounded rigor in an industry literally aiming for the stars.
03:35 – Learning When Not to Kill Ideas
Maureen reflects on being labeled a “dream killer” and how she transformed that mindset to foster innovation with constructive rigor.
07:34 – Applying Rigor Without Stifling Innovation
How Apollo used just-enough testing, internal prototyping, and diverse team strengths to build better, faster.
13:54 – Rethinking MVPs in Space Startups
Why even space companies now push to generate early revenue and test hardware pre-launch.
18:19 – Customers Want Something They Can See
Building a physical, testable product—even a crude one—outperforms pitch decks every time.
20:32 – The $70M Lesson of In-Space Testing
How one flight test flipped customer hesitation into a flood of contracts.
26:12 – Surviving the Shift from Prototype to Production
The real scaling challenge: maintaining culture and customer trust while redesigning for scale.
30:15 – The Hidden Power of Primes and Policy
Why space remains deeply shaped by government buyers—and how that’s changing with new VC-backed players.
35:33 – Starship and the Future of Space
Maureen shares what could shift when larger payloads, faster launch cadences, and orbital assembly become possible.
39:25 – Closing Reflections
Space is finally catching up to the urgency of its people. In an industry where “yesterday” is always the best time to start, speed is the differentiator.
FAQsWhat is Maureen Haverty known for?Maureen Haverty is a Principal at Seraphim Space, the world’s leading venture capital firm focused on space technology. She’s also known for her leadership at Apollo Fusion, where she helped scale the company to a $150M acquisition by Astra.What does Seraphim Space invest in?Seraphim Space invests in early-stage space technology startups globally, backing innovations in satellites, launch systems, in-orbit services, and deep tech infrastructure critical to the future of space exploration.What did Maureen Haverty learn from her time at Apollo Fusion?Maureen learned the importance of balancing rigor with experimentation. Her experience taught her to support bold ideas without stifling them and to build “just enough” before validating with customers—especially critical in high-stakes industries like space hardware.How do space startups approach product testing and market validation?Unlike SaaS startups, space companies face high costs and long timelines. The most successful ones focus on testing early and often, getting hardware into orbit quickly, and talking to customers well before finalizing product designs.Why is in-space testing so important for space companies?Even with rigorous ground-based testing standards, nothing builds customer confidence like real in-orbit validation. Maureen shares how one space test led to $70M in contracts within weeks—proving that live demonstrations are a major unlock for credibility and growth.What trends are shaping the future of the space industry?Maureen highlights the shift toward faster iteration, more venture-backed growth (vs. acquisition), and the game-changing potential of SpaceX’s Starship, which could enable larger structures, faster launch cycles, and more ambitious projects in orbit.
Useful ResourcesMaureen Haverty on LinkedInSeraphim Space
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Back when I first worked with Jana Werner at Tesco Bank, I saw firsthand how a crisis could be a crucible for innovation and transformation. Her ability to unlock potential in even the most challenged teams was unforgettable. Now, teaming up with Phil Le-Brun—a transformational leader I came to know through his work at McDonald’s—they’ve co-authored The Octopus Organization, a guide for thriving in an age of continuous transformation.
In this episode, we go behind the scenes of their book and explore the anti-patterns that hold organizations back, the behaviors leaders must unlearn, and the mindset shifts required to succeed when change never stops. Whether you’re a CEO, change agent, or team lead, you’ll leave with small, actionable experiments to start evolving your organization—today.
Key TakeawaysUnlearning blame-based leadership: Shifting focus from fixing people to fixing systems unlocks performance and trust.Spotting anti-patterns in everyday behavior: Habits like jargon, silos, and avoidance subtly block progress.Embracing uncertainty in leadership: Probabilistic thinking builds better decisions and psychological safety.Driving transformation through small experiments: Distributed action outperforms top-down mandates.Leading with curiosity in the age of AI: Execs must actively engage with tech to stay relevant and credible.
Additional InsightsBehind the book: Why The Octopus Organization centers on 36 anti-patterns and how they uncovered themReal-world leadership stories: Lessons from Tesco Bank, McDonald’s, Amazon, and FerrariTransformation fatigue is real: Overengineered change efforts often create fear and resistanceAlignment breakdowns in leadership teams: Many transformations fail because leaders aren't truly on the same pageReframing performance: Asking “what did you stop doing” reveals deeper impact than traditional goals
Episode Highlights00:00 – Episode Recap
Jana Werner shares how she took over a struggling tech team, discovered their true strengths, and transformed their performance by rebuilding culture and trust. Phil Le-Brun describes the importance of creating a culture of trust in organizations, allowing people to test ideas and make a real difference.
02:46 – Guest Introduction: Jana Werner & Phil Le-Brun
Barry O'Reilly introduces guests Jana Werner and Phil Le-Brun, describing their collaboration during times of crisis at Tesco Bank, their leadership backgrounds, and their shared vision for adaptive, purpose-driven organizations as captured in their new book.
04:36 – Revitalizing a Demotivated Team at Tesco Bank
Jana Werner narrates how she took over a demotivated technology team, overcame her initial preconceptions, and transformed the group into a top-performing unit by changing culture, empowering individuals, and shifting organizational dynamics.
07:07 – Lessons from McDonald's: Balancing Centralization and Agility
Phil Le-Brun explains McDonald's transformation journey, the need to unify local and corporate efforts, and the financial impact of building trust and alignment.
10:16 – Learning from Industry Leaders
Phil recounts interviews with CEOs like Indra Nooyi and Benedetto Vigna, highlighting that true leadership requires humility, storytelling, and ongoing curiosity.
14:14 – Unlearning the Need for Certainty
Jana Werner discusses shifting away from needing all the answers and embracing uncertainty, drawing on insights from Annie Duke and other leaders.
21:30 – Small Changes, Big Impact
Jana introduces the book's structure around "anti-patterns" and advocates for making small, distributed changes rather than massive, top-down transformations.
26:29 – Leadership Alignment: Avoiding Transformation Pitfalls
Phil highlights the need for alignment among leadership teams and points out common failures in transformation projects due to lack of shared understanding.
29:09 – Becoming "Technology Teenagers"
Phil and Jana emphasize the importance of leaders learning to experiment and engage directly with new technologies, encouraging curiosity and hands-on learning with AI.
32:12 – Start Small and Experiment
Both authors encourage listeners to pick a tip from the book and try it right away—emphasizing the value of experimentation, feedback, and removing old practices to spark growth.
Useful ResourcesJana Werner on LinkedIn - https://www.linkedin.com/in/janawerner1/ Phil Le-Brun on LinkedIn - https://www.linkedin.com/in/phillebrun/ The Octopus Organization – Book by Jana Werner & Phil Le-Brun - https://www.amazon.com/Octopus-Organization-Thriving-Continuous-Transformation-ebook/dp/B0DRZ2MXBR Related episode: Accelerating Transformation in Crisis – Tesco Bank Case Study - https://barryoreilly.com/explore/articles/accelerating-transformation/ Amy Edmondson – Research on Psychological Safety - https://amycedmondson.com/psychological-safety/ Annie Duke – Thinking in Bets - https://www.annieduke.com/books/ Indra Nooyi – Leadership Insights - https://www.indranooyi.com/Follow the Host
LinkedIn: Barry O’ReillyWebsite: barryoreilly.comTwitter/X: @barryoreillyInstagram: @barryoreillyFacebook: Barry O’Reilly
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In this episode of The Unlearn Podcast, Barry O’Reilly is joined by Steve Elliott, a serial entrepreneur, product leader, and investor with two decades of experience advising high-growth companies. Steve is the founder of Dotwork, an AI-driven platform that connects strategy to execution, and co-founder of The Uncertainty Project, a community for product leaders focused on better decision-making.
He previously served as Head of Product at Atlassian, where he helped scale Jira Align after selling his company AgileCraft for $166M—earning recognition as a Fortune Best Small Business in America and a finalist for the Ernst & Young Entrepreneur of the Year. With five successful exits under his belt, Steve brings rare depth to the art of building and unbuilding what no longer serves.
In this conversation, Barry and Steve explore how to design for the messy reality of modern work, the role of unlearning in leadership, and how AI is redefining what it means to be a decisive company.
Key TakeawaysFrom CTO to CEO – Why Steve transitioned from tech leader to founder and the personal growth that came with it.Scaling after acquisition – The emotional and strategic shifts required when your startup becomes part of a larger machine.Why strategy execution breaks – Most alignment tools assume order—Steve builds for complexity.Agentic AI in the enterprise – How Dotwork uses knowledge graphs and AI to surface insight in context, not just dashboards.Decisive companies – What it really means to help leaders make faster, more confident decisions.
Additional InsightsUnlearning the idea that startups are for the young—Steve didn’t found his first company until his 40s.How Dotwork is building a “context memory engine” for both executives and AI agents.The future of AI-native tools isn’t more interfaces—it’s less friction and smarter context delivery.Why the most valuable enterprise products aren’t flashy—they’re quiet, ambient, and deeply integrated.
Episode Highlights00:00 – Episode Recap
Steve Elliott shares how each startup exit taught him something new—but also how returning to the founder’s seat means unlearning old assumptions. Now, with Dotwork, he’s not just building a tool—he’s rethinking how organizations make decisions in complexity.
01:45 – Guest Introduction: Steve Elliott
Barry introduces Steve Elliott, founder of AgileCraft (acquired by Atlassian) and CEO of Dotwork, with a track record of five successful exits and a deep focus on enterprise work management.
03:40 – Early career shifts
From a consulting career at PwC to software experiments that took off—how Steve found his way into entrepreneurship.
08:55 – From technologist to founder
The value of combining tech expertise with business empathy—and why startups offer unmatched learning opportunities.
11:05 – Unlearning post-acquisition mindsets
What Steve had to unlearn transitioning from CEO to leader within a larger company—and back again.
13:36 – Building tools for strategic decisions
Why enterprise tools fail to support real-time, strategic decisions—and how Steve is tackling the problem differently.
17:50 – The rise of agentic frameworks
How Dotwork is using knowledge graphs and agentic AI to reflect the dynamic, decentralized nature of modern organizations.
23:31 – Breaking through transformation fatigue
How Dotwork builds trust not through marketing, but by showing real, contextual results fast.
26:23 – Beyond dashboards: AI-native UX
Why true AI-native platforms don’t ask you to log in—they come to you with insight in the moment.
32:44 – Coaching execs on AI
Barry shares his experience coaching executives on AI—and why hands-on experimentation is the only path to mastery.
36:07 – Context engines for agents
Steve explains how Dotwork unintentionally became a context memory platform—crucial for the future of autonomous agents.
40:36 – Magic moments in enterprise UX
When engineering hasn’t seen the reports their software generates—because the platform is that intuitive.
43:17 – Closing Reflections
Steve reflects on the value of doing over theorizing—and the importance of staying close to the problem if you want to innovate meaningfully.
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In this episode of the Unlearn Podcast, I sit down with Cass Pratt, Chief Human Resources Officer at Progyny, to explore how HR is evolving into a design discipline that blends human connection with AI-powered productivity. From building bots to boost employee experience to reshaping how we think about roles in an automated world, Cass shares an honest look at how she’s bringing people along on a transformation journey—with curiosity, experimentation, and heart.
We discuss her pivotal decision to say yes to opportunities beyond her comfort zone, the strategic shifts she's leading inside a fast-scaling company, and why the future of HR is about enhancing humanity, not replacing it. If you’re wondering what leadership looks like when AI meets empathy, this one’s for you.
Key TakeawaysUnlearning expertise-dependence: Cass shifted from relying on experts to co-creating solutions with AI tools before engaging others.
AI as a force for elevation: At Progyny, AI is used to give employees time back, not take roles away—enabling deeper focus on human-centric work.
Low-code leadership: Cass, a self-described non-technical leader, built HR bots and reimagined policies through practical AI applications.
Scaling culture through consistency: AI chatbots improved response times, standardized answers, and gave insight into employee concerns.
Embedding experimentation: Teams are encouraged to ask, "What should I stop doing?"—sparking a culture of reinvention and initiative.
Additional InsightsProgyny’s “Super Fans” initiative reframes AI gains as an opportunity to deepen customer and employee relationships.
Training is done in cohorts to build shared understanding and reduce AI anxiety.
Cross-functional collaboration with junior team members—like the intern who built the HR bot—shows how innovation can come from any level.
Cass uses AI to simplify and globalize complex frameworks like competency models, improving alignment across teams and geographies.
Episode Highlights00:00 – Episode Recap
Cassandra Pratt shares how embracing discomfort led her to leap into healthcare, build a transformative HR function, and lead with AI—not to eliminate roles, but to elevate people and amplify their impact.
02:37 – Guest Introduction: Cassandra Pratt
Barry introduces Cass Pratt, Chief People Officer at Progyny, a fertility and family-building benefits company scaling rapidly with a human-first, tech-empowered culture.
04:48 – Saying Yes to Growth
Cass reflects on a missed opportunity that taught her the cost of saying no—and set her on a path to jump into unknowns with conviction.
08:04 – Startup Lessons and Leadership Growth
From 50 to 850 employees, Cass shares what it means to grow with a company and embrace mistakes as part of the journey.
11:00 – Diving into AI Without a Tech Background
Despite lacking technical skills, Cass threw herself into generative AI—learning by doing and discovering intuitive ways to drive value.
13:10 – Unlearning the Expert Reflex
Cass rethinks her default of turning to experts first—instead starting with AI to shape stronger ideas and bring others in as collaborators.
15:13 – Redesigning Processes, Not Just Tools
AI opened up opportunities to rethink workflows from scratch, not just automate existing inefficiencies.
20:35 – Making AI Safe and Human
Cass shares how transparent messaging, training, and cultural reinforcement helps ease AI anxieties and keep the focus on people.
25:00 – Building the HR Bot with an Intern
An intern-built benefits chatbot improved response times, consistency, and surfaced new insights—highlighting the power of junior talent and experimentation.
28:41 – Simplifying Competency Models with AI
Cass uses AI to refine complex frameworks, making them scalable across geographies and easier for leaders to apply.
30:00 – Rethinking Work Through Elimination
By asking what should be stopped—not added—Cass surfaces high-leverage opportunities to transform HR workflows.
34:33 – The Two Extremes of HR and AI Adoption
Cass observes a divide: HR teams either lead AI transformation—or risk being the last to catch up.
40:45 – Cross-Functional Collaboration and Culture
AI transformation is a team sport—embedding HR into company-wide initiatives empowers better collaboration and outcomes.
43:38 – Freeing Up Time to Be Present
Cass highlights how AI helps reclaim time for the most human part of HR: being present, listening, and solving meaningful problems together.
Useful ResourcesProgyny: https://www.progyny.comConnect with Cassandra Pratt: LinkedInAI Executive Coaching by Barry: https://barryoreilly.com
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When most leaders think about transformation, they reach for tools and tactics. But real, lasting change doesn’t start with new methods—it starts with culture. In this episode, I sit down with Phil Gilbert, the former General Manager of Design at IBM, who led one of the boldest reinventions in corporate history. After selling his third startup to IBM in 2010, Phil was asked to transform how IBM’s teams worked using design thinking and agile. That effort reshaped the experience of over 400,000 employees and became the subject of a Harvard Business School case study, the documentary The Loop, and coverage in the New York Times and Fortune.
We explore how culture drives outcomes, why the team is the atomic unit of change, and how to design a leadership structure that earns trust and creates momentum. Phil brings sharp insight, rich stories, and practical frameworks drawn from a 45-year career spanning startups, scale-ups, and global enterprises. If you’re leading change—or trying to get others to believe in it—this conversation is your blueprint.
Phil Gilbert is best known for scaling IBM’s global design transformation. He was inducted into the New York Foundation for the Arts Hall of Fame in 2018 and named an Oklahoma Creativity Ambassador in 2019. Since retiring from IBM in 2022, Phil has focused on helping business and military leaders shift culture at scale to improve innovation and team performance.
Key TakeawaysCulture is the system: Real transformation means rewiring people, practices, and places—not just teaching new skills.Teams are the atomic unit of change: Change doesn’t scale through individual mandates. It scales when cross-functional teams deliver new outcomes.Design scales empathy: Phil shares how design thinking isn’t just about aesthetics—it’s a tool for scaling understanding and improving systems.Transformation needs protection: Change teams need structural support and a leadership “shell” that shields them while engaging the broader org.Momentum beats mandates: Leaders can’t impose change—they must earn it by showing results, listening deeply, and integrating across silos.
Additional Insights"Every day is a prototype": Phil’s mantra that gives teams permission to change, test, and learn continuously.The virus model of leadership: To spread new ways of working, Phil designed his leadership team like a virus—with spikes into HR, finance, comms, and IT.Designers aren’t the barrier—systems are: In companies with weak design reputations, the problem isn’t the designers. It’s the culture around them.Shadow IT kills transformation: Real progress happens when change leaders partner with CIOs—not work around them.Most AI efforts are missing the point: Phil argues that AI transformation fails when it focuses on individuals instead of improving team-level outcomes.
Episode Highlights00:00 - Episode Recap
Barry O’Reilly recaps the episode’s theme, discussing leadership challenges, reclaiming strategic focus, and leveraging frameworks, executive habits, and AI to drive impactful business outcomes.
2:26 - Guest Introduction
Barry introduces Phil Gilbert, renowned for leading a major cultural transformation at IBM through human-centered design. He previews Phil’s new book, “Irresistible Change,” and sets expectations for a discussion on leadership, empathy, and executing change at scale.
3:21 - Official Start of Conversation
Phil Gilbert reflects on pivotal career moments, including his experience founding early startups, the challenge of driving adoption for new technologies, and discovering the power of empathy and design. He introduces his guiding philosophy, “every day is a prototype.”
9:15 - The Power of Prototyping and Embracing Change
Phil explains how prototyping and a willingness to challenge the status quo lead to organizational and personal growth. He shares his “every day is a prototype” mantra and stresses the role of openness in innovation.
13:48 - Culture as a Driver of Outcomes
Phil outlines his formula for driving real change, focusing on people, practices, and places. He discusses his use of journaling and intentional observation to systematically build curiosity and support for change in teams.
20:47 - Designing Transformation at Scale
Phil discusses the challenge of leading IBM’s company-wide design movement. He explains his strategy to reach and influence 400,000 employees and the importance of building a diverse leadership team to support transformative efforts.
31:29 - Practical Tactics for Organizational Change
Phil details the need to integrate HR, tooling, and communications into the transformation process, sharing stories about revamping career ladders and piloting new tools. He emphasizes collaboration and transparency with key stakeholders like HR and CIOs.
37:51 - Lessons for Modern AI Transformation
Phil and Barry examine current challenges with AI change efforts, arguing that teams—not just individuals—are the fundamental units for successful transformation. They discuss why team-level outcomes should guide measurement and strategy for adopting new technologies.
41:09 - Hopes and Irresistible Change for the Future
Phil shares his vision for the next wave of business transformation, especially regarding AI. Drawing inspiration from cloud computing’s impact, he hopes leaders will adopt principles that empower teams to drive industry-defining change.
Useful ResourcesPhil Gilbert – Irresistible Change (book): Buy on AmazonConnect with Phil on LinkedIn: Phil GilbertBarry’s blog on AI
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When it comes to product positioning, clarity isn’t just a communication tool—it’s a strategic advantage. In this episode, I sit down with Anthony Pierri, co-founder of FletchPMM, a product marketing consultancy that’s helped over 400 B2B software startups discover and sharpen their positioning. We explore how founders can unlearn generic marketing advice, clarify their message, and activate their strategy through one often-overlooked asset: their homepage.
Anthony brings practical frameworks, real-world stories, and a refreshing candor to a space that’s often muddled with jargon. This is a must-listen for any founder, PMM, or GTM leader tired of being misunderstood—and ready to focus.
FletchPMM is a product marketing consultancy that helps B2B tech startups nail their positioning and bring it to life through a purpose-built homepage. Alongside co-founder Rob Kaminski, he’s helped more than 400 companies craft focused, champion-centered messaging that converts.
Key TakeawaysClarity wins: Positioning isn’t about vision—it’s about specificity, segmentation, and telling your champion’s story.Unlearn the fluff: Ditch the vague benefits and generic promises. Customers need to know what you do and how it helps them.Focus = traction: Trying to be everything to everyone dilutes your impact. Specialization creates memorability and repeatability.Your homepage is your positioning: It’s the one asset every stakeholder sees—customers, investors, your team. Make it count.Position for the champion, not the budget holder: Focus your messaging on the person closest to the problem—not the executive who cuts the check.
Additional InsightsPositioning is pattern recognition: Anthony shares how lessons from church leadership and freelancing helped him recognize early signs of positioning misalignment—even before he had the language for it.Inbound scale comes from consistency, not creativity: With over 500 companies served, Fletch’s success has come from delivering one service, the same way, every time—not by chasing new ideas or tactics.Founders often confuse luck with repeatability: Anthony reveals how many early startup wins come from personal networks—and how this masks the real need for scalable positioning and segment focus.Mispositioning starts with the homepage: Anthony critiques vague, benefits-only messaging like “Make Yes Work”—demonstrating how the lack of a clear product reference point derails understanding and action.Repositioning is an organizational act: Referencing Klaviyo and Meta, Anthony shows how homepage messaging isn’t just about marketing—it forces internal alignment by making strategic bets visible to every team member.
Episode Highlights00:00 – Episode Recap
Anthony Pierri shares how a seemingly minor contradiction in a church’s mission statement became his first exposure to a positioning problem—planting the seed for a career built around clarity.
01:30 – Guest Introduction: Anthony Pierri
Barry introduces Anthony, co-founder of FletchPMM, a consultancy that’s helped 400+ B2B software startups craft focused, conversion-driving homepages.
05:09 – The Real Cost of Doing Everything
Why trying to serve every persona or use case is the quickest way to stall traction—and how narrowing your focus builds momentum.
07:14 – Specialization is a Strategic Advantage
Anthony explains how one service, delivered one way, to one segment unlocked a scalable, inbound engine for Fletch.
11:42 – Sales Strategy or Sales Chaos?
The folly of hiring SDRs before narrowing your GTM focus—and why customer acquisition doesn’t scale without segment clarity.
14:03 – Champion-Centric Positioning
Don’t aim for the budget holder—speak to the person closest to the problem. They’ll become your internal advocate.
22:07 – How AI Will Impact Product Positioning
As software creation and discovery become more agent-driven, Anthony sees the same need for ultra-specific, capability-first messaging.
29:19 – Talking About Yourself Without Talking About Yourself
Positioning isn’t self-promotion—it’s about telling a compelling story that reflects your champion’s reality.
35:15 – The “Tell Me More” Effect
Great positioning doesn’t try to say everything. It just gets the right person to say, “Tell me more.”
38:17 – Your Homepage is Your Most Important Asset
The homepage isn’t just a lead gen tool—it’s the most visible alignment document your org has. Make it reflect your real strategy.
44:53 – Changing the Narrative at Scale
Anthony shares why embedding your positioning on the homepage is more powerful (and more visible) than internal decks ever will be.
46:35 – How to Structure a Homepage That Converts
Barry and Anthony unpack how to use messaging anchors, problem framing, and customer-centric storytelling to guide your homepage narrative.
Useful ResourcesFletchPMM WebsiteAnthony Pierri on LinkedInApril Dunford – Obviously AwesomeWynter – Message Testing
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