Leadership in Change with AI - Podcast

TL;DR - Dave Edelman has been working on personalization since 1986, back when databases were the new thing in marketing, and he watched it grow into what he and his co-author call a $2 trillion prize. Then last week he published a warning that we’re about to drown our customers in a tidal wave of hyper-personalized garbage. We got into the piece of junk mail that made him buy solar panels without ever looking at a competitor, the cheapest move almost nobody makes, and what separates personalization that earns trust from personalization that just makes somebody feel watched.What You Can Expect* A test you can run on your own next campaign: are you orchestrating what reaches a customer, or letting four departments hit the same person independently?* The one question Dave asks every company he walks into, and why most of us can’t answer it honestly.🎥 Catch all future interviews, subscribe!🎧 Prefer audio? Listen on Apple PodcastsOutline(00:35) – Marketing since 1986, and riding every wave since(03:55) – Why he wrote the book: slop was the danger(07:35) – The solar mailer: Google Earth, Zillow, and 21.3%(11:55) – Test and learn, and how Sungevity actually got there(13:52) – Zero-party data, and the companies that never just ask(17:15) – The front desk secretary who tested every new tool(18:28) – Morgan Stanley, and ten hours a week back(22:31) – One customer, four departments, all bombarding(25:45) – Where trust turns into feeling watched(28:26) – Why this is a strategy decision before it’s a marketing one(31:15) – Call center transcripts, and catching a bug in fifteen minutes(32:11) – The one thing: the high roadMy TakeawaysThe junk mail that worked. Dave’s town offered a property tax discount for solar panels, which set off an avalanche of mail. One envelope did something the others didn’t. He typed in a personalized URL and got a Google Earth image of his own roof with panels drawn onto it, sized to his roof’s orientation and latitude, with his likely annual usage estimated from the square footage on Zillow.“So they had the numerator from Google Earth, the denominator from Zillow. It came to 21.3%. They said they would guarantee 20%.” — Dave EdelmanHe bought without looking at a competitor, stayed seven years, and cleared 20% every year but one, when they sent a rebate check instead. And you don’t get there without 25 iterations, but it started with thinking, how can we truly delight our customers?Delight is where almost everyone stops. The book runs on five promises: empower me, know me, reach me, show me, delight me. I don’t think we normally get to the delight area, it usually stops way before that, and the delight-me ones are exactly the ones that hold customer trust for years. What I hadn’t thought about is that AI is what finally makes that last promise affordable, because the testing that gets you there also feeds the thing doing the testing.“It also feeds your AI. You get more data from the tests that make that AI smarter.” — Dave EdelmanOrchestrate, or bombard. One retailer ran every department on its own marketing budget, and the best customers of one category turned out to be the best customers of most of the others, so the same people got hit from every direction at once. Response rates fell.“The customer isn’t a customer of a category, a department. Customer is a customer of our brand overall.” — Dave EdelmanThey pooled the data, used AI to rank the top three things any given person would actually care about, and governed every message down to those three. Loyalty memberships up, sales up over 20% a year, cited at their investor day. To me that tells the customer we value your attention, which is the same line I’ve drawn before on when personalization crosses it.It’s a strategy decision before it’s a marketing one.“The first step is, this is a strategy decision. This is about how you want to compete. And that’s a real strategic decision, to restrain yourself in order to get a higher response rate.” — Dave EdelmanI coach CEOs on AI strategy, and time and time again I see the left hand of an organization with no idea what the right hand is doing, both of them touching the same customer, sometimes to the detriment of the other. And the customers just don’t feel known. Now, every company Dave named is enormous, so the fair question for the rest of us is what this looks like at forty people. His cheapest fix scales all the way down: poll your own employees first. Which reminded me of a CEO I worked with who had his front desk secretary, about 55 and not remotely techie, walk every new sign-up flow before launch and report back to marketing. It’s not hard, but it’s so rare. Same gap I keep running into when AI initiatives stall.One Question Before You GoDave’s own test is the one I’d carry out of this hour. “What is your intent? Is your intent to add value to the customer and be the brand that’s known for that, or are you just manipulating them?” He calls the first one the high road, and he’s watched it build brands since 1986.So put yourself in the shoes of your customer, of your audience. Would they like what you’re doing, would they trust you, and would they be delighted?Watch the full conversation above, and go follow Dave on LinkedIn, where he publishes on this constantly.About David EdelmanDavid C. Edelman teaches marketing at Harvard Business School and advises CEOs and CMOs through Edelman Advisory Services. He was Chief Marketing Officer at Aetna, co-led McKinsey’s global digital marketing and sales practice for eight years, and was an EVP at Digitas and a partner at BCG before that. Personalized: Customer Strategy in the Age of AI, co-authored with BCG’s Mark Abraham, came out from Harvard Business Review Press in October 2024. More than a million people follow his writing on LinkedIn.About meJoel Salinas is an AI Strategy Coach for founders and leaders, from solopreneurs to teams. AI is everywhere; judgment is scarce. Joel helps leaders adopt AI without outsourcing their judgment to it, through the AI Judgment Workshop and the 90-Day Judgment Engagement. Creator of the AI Leadership Triad. He writes Leadership in Change.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

TL;DR - Nir Eyal wrote Hooked, the book a generation of product teams used to build habit-forming apps, and then wrote Indistractable to hand the rest of us the counter-move. In this Substack Live, he made a case I wasn’t expecting: only about 10% of our distraction comes from pings and notifications, the other 90% comes from inside us, and the fix isn’t more willpower but a calendar. We got into why to-do lists are broken, why checking email is the most dangerous distraction there is, and why he thinks self-regulation is the skill of the century.What to Remember* The one-sentence test Nir uses to tell traction from distraction, which has nothing to do with what the activity actually is* Why he calls the to-do list a broken tool, and the timeboxing move he replaced it with🎥 Catch all future interviews, subscribe!🎧 Prefer audio? Listen on Apple PodcastsOutline(1:19) – Hooked and Indistractable are complements, not opposites(5:07) – Internal triggers, and the month I deleted every news app(6:24) – The book about focus Nir can’t stand(7:22) – Only 10% of distraction comes from the pings(8:56) – Traction, distraction, and the Latin root of both(10:49) – The email trap: work that isn’t the work(12:27) – Name one product built to help you use it less(14:20) – Effort pacts, and Viktor Frankl’s space(15:43) – Why to-do lists are broken(17:22) – Timeboxing, and the real metric of success(22:30) – Self-regulation is the skill of the century(28:36) – Persistence, belief, and Beyond BeliefMy TakeawaysNinety percent of it is coming from inside the houseSo this is the number I had to go back and check twice. We blame the pings, the dings, and the rings, and Nir puts those at roughly 10% of the problem. The other 90% is an internal trigger, which is really just a feeling: “Loneliness, boredom, fatigue, uncertainty, anxiety.” Then he closes the escape hatch. “It’s not your fault. You didn’t create these digital technologies. But it is your responsibility because who else is responsible?”Traction and distraction are the same wordHere’s the reframe I’ll actually use. Both come from the Latin root trahere, to pull, and both end in the same six letters, action. So the test is simple: “anything that is not what you said you were going to do in advance is by definition a distraction.” Watching football isn’t a distraction if you planned it, and answering email is one if you didn’t. That second half is what got me, because Nir says the work-shaped distractions are the worst kind, “because you don’t even realize you’re distracted.” I said on the recording that this was hitting close to home, and I meant it.The to-do list is a register of things you failed to doHonestly, this is the part I didn’t want to hear because I tend to live by my to do list. A to-do list has no constraints, so you always add more and you always pick the easy item over the important one, and then you read back the leftovers night after night until you’ve built a fairly convincing case against yourself. “There’s nothing wrong with you. You’re not broken. It’s this stupid time management technique we call to-do list that’s broken.” His replacement is timeboxing, and it moves the finish line: success isn’t the checked box but “did I work on what I said I was going to work on for as long as I said I would without distractions?” Be stingy with your time and generous with your moneyThis is the line I’d put on a wall. We clip coupons, we split checks at lunch, we hunt for deals, and then we hand our hours to whoever asks. “You can’t make more time. I don’t care if you’re Bill Gates or Elon Musk.” He carries it into parenting, calls self-regulation “the skill of the century,” and describes sitting down with his six-year-old to build her calendar, video games included. My version is a Bloom card that locks my work apps at 8 p.m., so getting back in means walking to my bedroom and tapping my phone against it. That walk is the whole point.One Question to Sit WithWhat’s on your calendar this week that’s still only on your to-do list?Then watch the full conversation above, and go subscribe to Nir And Far, grab Indistractable, and pick up his new one, Beyond Belief.About Nir EyalNir Eyal is the author of Hooked, Indistractable, and Beyond Belief, which are built on his work in behavioral design and human motivation. Hooked and Indistractable have sold more than a million copies in over 30 languages, and Beyond Belief is an instant New York Times bestseller. He’s a former lecturer at the Stanford Graduate School of Business and the Hasso Plattner Institute of Design at Stanford, and his writing has appeared in The New York Times, Harvard Business Review, and The Atlantic. He writes Nir And Far on Substack and gives away a deep library of free tools at nirandfar.com, including a schedule maker and a habit tracker.About meJoel Salinas is an AI Strategy Coach for founders and leaders, from solopreneurs to teams. AI is everywhere; judgment is scarce. Joel helps leaders adopt AI without outsourcing their judgment to it, through the AI Judgment Workshop and the 90-Day Judgment Engagement. Creator of the AI Leadership Triad. He writes Leadership in Change.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

TL;DR: Charlene Li has been standing at the front of every big technology shift since newspapers went online in the early nineties, and she just published Winning with AI with Dr. Katia Walsh. We spent most of this conversation on the thing most of us won’t say out loud, which is the fear that we already missed it. Her answer is that we are all absurdly early, that fluency is the whole game, and that the only way to get it is to be bad at this in public for a while. Watch this one if you’ve been measuring yourself against everybody on LinkedIn who looks like they have AI figured out already.🎥 Catch all future interviews, subscribe!🎧 Prefer audio? Listen on Apple PodcastsOutline(00:25) – Who Charlene Li is, and why it’s never about the technology(01:39) – From the newsroom to Forrester to Altimeter Group(03:41) – Electricity, steam-powered factories, and why AI moves faster(06:24) – The biggest misconception, and “you’re not even close to beginning”(08:44) – Fluency vs. literacy, and why the only way through is through(11:36) – The trust wall, and how a leader destigmatizes AI in one meeting(13:48) – Why write a book on AI when everything keeps changing(16:42) – Step one, and the one line to add to the end of every prompt(19:27) – Pick your lane, and the board member who owned ethical AI(25:35) – “You’re not behind. You’re just getting started.”(33:09) – Curiosity, imagination, and using AI to find your blind spotsMy TakeawaysYou’re not behind. So this is the piece I keep coming back to, because I hear that fear from almost every leader I sit with and I’ve felt it in myself. Charlene has been in this since she helped a newspaper go online in 1993, she wrote the book on it, and she still took three weeks off in January to care for loved ones, came back to Claude Cowork, and had no idea what had happened while she was gone. She felt behind too. Then she took a breath and turned it around on the rest of us.“You’re not behind. Just look around you. How many people haven’t even started yet? So if you start today and just do one thing, you’ll be ahead of the vast majority of people.”One of my clients is a CEO with over 45 years of practice who started sending me links to artifacts he’d built in Claude, and he could not believe he made them himself with nobody helping him. That’s what starting looks like.Fluency is a practice, and practice is the only door. Honestly, this is where most AI advice falls apart, because it tells you what the thing is and then leaves you standing there. Charlene splits AI literacy, knowing what it is, from AI fluency, which is what happens once you’ve used it enough that you stop thinking about it. There’s one way to get there and she doesn’t pretend otherwise.“It will feel messy. It will feel like you don’t know what you’re doing... But there is no way around it. You have to go through it. The only way through it is through it.”I said something close to this on the live about electricity, that plugging AI into an organization nobody wired for it does nothing, but hers is the harder version, because wiring a house is a project you finish and this is a thing you only get by being bad at it for a while. She also gave the best beginner tip of the night: add “before you start, ask me any clarifying questions you may have” to the end of your prompt, and the whole thing turns from a vending machine into a conversation.Mindset comes before tools, and before governance. Look, most of us hand AI to the CIO, buy everyone a license, and call that a rollout, and I keep watching it play out the same way. Her line on it was the sharpest thing she said all evening.“This is not something you delegate. And what I’ve seen now is that leaders are abdicating this role.”The fix she gave is almost embarrassingly small. Use AI to prep for your next meeting, tell the room you did it, then ask them how they used it, which sets the expectation and takes the shame out of it in the same breath. If your people think using AI counts as cheating, no tool budget on earth saves the rollout. That’s the same wall I wrote about in the empathy gap in AI implementation.The thing I’m stealing from her. Here’s the part I hadn’t thought of, and I said so on air. Charlene feeds her own meeting recordings to AI and asks it what went wrong in the room.“Take a transcript of my last meeting because something in it didn’t feel right. Something went off the rails and I’m not sure what’s happening. Diagnose that and give me suggestions.”It comes back and tells her she never set an agenda, or that she talked for 70% of a call she should have been listening through. I’ve fed transcripts into Claude plenty of times to build a post out of them, and it never once occurred to me to point that back at myself and ask where I got in my own way. I use Granola to capture the calls, so the raw material has been sitting there the whole time, which is really the argument for why none of us is behind. The thing that moves you forward this week is probably already open on your screen, and you just haven’t pointed it at anything that matters yet.The mindset work Charlene is describing, getting your own hands dirty before you ask your team to, is exactly what I walk leaders through in the AI Judgment Workshop, which is open for registration now. If you’d rather go deeper inside your organization, that’s the 90-Day Judgment Engagement.One Question to Sit WithCharlene left this one hanging and I haven’t been able to put it down: What could you actually do if everybody in your company was fluent with AI, not licensed, fluent? What would you build that you’ve already talked yourself out of?Watch the full conversation above for her answer, and for the line I keep repeating to myself, that you’ve never been in control anyway. When you’re done, go subscribe to Charlene Li on Substack.About Charlene LiCharlene Li is a New York Times bestselling author whose books include Groundswell, Open Leadership, and The Disruption Mindset. Her latest, Winning with AI: The 90-Day Blueprint for Success, is co-written with Dr. Katia Walsh, one of the world’s first chief AI officers, and it’s a leadership and strategy book rather than a technology book. She founded Altimeter Group in 2008, spent years as a Principal Analyst at Forrester Research covering the rise of social media, served as Chief Research Officer at PA Consulting, and now leads her own firm, Quantum Networks Group. She’s just moved her newsletter to Substack, and the book is at winningwithaibook.com.About meJoel Salinas is an AI Strategy Coach for leaders at small and mid-sized businesses and nonprofits. AI is everywhere; judgment is scarce. Joel helps leaders adopt AI without outsourcing their judgment to it, through a monthly live workshop and 90-day engagements. Creator of the AI Leadership Triad. He writes Leadership in Change.Affiliate links included.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

TL;DR: Phil Powis ❤️⚡️ and I have been going back and forth on Substack for over a year, and his writing lands in my feed like a breath of fresh air, so this one felt less like an interview and more like two friends comparing notes. We got into why AI is nobody’s goal, why your team’s trust matters more than the tool, and the one question he keeps coming back to that can reorganize a whole business. Worth the watch if work has started to feel hollow.🎥 Catch all future interviews, subscribe!🎧 Prefer audio? Listen on Apple PodcastsOutline(00:30) – Friends across Substack, a breath of fresh air(01:23) – Burnout, a tumor, and the business he walked away from(07:35) – Quality of life vs. lifestyle(09:07) – Sacred business vs. opportunistic business(11:15) – Why AI is nobody’s goal(16:48) – The AI Judgment Workshop and reading your team(19:18) – The Harmony Map, and slowing down in the AI era(27:40) – The eco rat race: old identity, new context(29:46) – We’re all toddlers with AI(31:48) – “What do you truly want?”(35:39) – The Golden Sequence: connection, growth, belongingMy TakeawaysSacred business vs. opportunistic business. So Phil opened with the story I keep thinking about. He built a boutique advertising business doing over $100,000 a month with basically him and a virtual assistant, and it nearly cost him everything, autoimmune problems, a health scare, time essentially bedridden. He walked away because his heart was never in it, and out of that came the distinction the whole conversation runs on.“When we talk about sacred business, it’s honoring all of who you are, your gifts, your talents, your failures, your victories, and it’s tied to service. The opportunistic business is chasing the trend. It’s not really looking at who am I and what wants to come through.”When you chase the trend, you spend your life playing catch-up on somebody else’s dream. I’ve watched leaders do it with AI too, grab the shiny thing because everyone else did, and then wonder why it drains them.AI is nobody’s goal. Here’s where I jumped in, because I see the same thing coaching leaders on AI. I’ll ask why they’re bringing it in, and a lot of the time the honest answer is “we just want to be an AI-forward business.” That’s the trap Phil is describing, and it’s why I keep saying AI is nobody’s goal.“So much of what I’m doing is just following my own threads of curiosity and wonder, and asking the questions I’m looking to answer for myself, and then allowing people a window into that.”AI is the means to whatever your goal always was. Marry that goal to something you actually care about and the work stops feeling like burnout, which is the whole discipline behind the AI Leadership Triad. The tool moves you toward what you wanted, it doesn’t get to become the thing you want.The eco rat race. Phil lived in Costa Rica for three years, and he had the funniest, truest line of the whole talk, about the founders and VCs who burn out, move there to build a wellness center, and change absolutely nothing.“They bring the same New York energy to the picture. They’re sitting in the most beautiful locations in the world and they’re still the most stressed out people you’ll ever meet. They’re bringing that old identity to a new context.”Carolina Wilke nailed it in the chat, you can build a new business with an old identity and hit the same walls.You can’t relocate your way out of who you are, and you can’t AI your way out of it either.We’re all toddlers with AI. The thing I keep coming back to is how humble Phil is about all of this. He refuses to look down on anyone’s messy AI use, and he put the reason plainly.“With AI specifically, we’re all kind of like toddlers. And I include myself in that, and even you, because how far are we really into this? We’re a couple years into this journey.”I study this for a living and I still bring in a new expert every Thursday, because none of us has it figured out. Phil’s antidote to the noise is one question he and Carolina ask their clients: what do you truly want. Ask it enough times and it gets dangerous in the best way, because it’ll take you down a rabbit hole if you let it. That question is the human work AI can’t do for you, and it’s the same reason I keep telling leaders not to outsource their thinking to it.Reading your team before you buy the tool is exactly what I run leaders through in my AI Judgment Workshop, which is open for registration now. If you’d rather go deeper one-on-one or with your organization, just let me know! One Question to Sit WithPhil ended on the question I want to leave you with too: what’s the why behind where you’re putting your hours, and does it marry where your passions lie?Watch the full conversation above for how Phil and Carolina help people sit with that. And when you’re done, go subscribe to Sacred Business Flow.About Phil PowisPhil Powis is the creator of Sacred Business Flow, a Substack with more than 33,000 subscribers that he writes with his partner Carolina. He teaches founders and creators to build what he calls a sacred business, one that honors who you are and stays profitable, instead of an opportunistic business that just chases the trend. His work pairs business and marketing strategy with inner work, including the Harmony Map assessment, which reads what he calls your nine fundamental frequencies and points you to the one “breakthrough frequency” worth building around. Subscribe to his writing at Sacred Business Flow, and take the free Harmony Map assessment at sacredbusiness.com.About meJoel Salinas is an AI Strategy Coach for leaders at small and mid-sized businesses and nonprofits. AI is everywhere; judgment is scarce. Joel helps leaders adopt AI without outsourcing their judgment to it, through a monthly live workshop and 90-day engagements. Creator of the AI Leadership Triad. He writes Leadership in Change.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

Polina Pompliano has published a deeply reported profile of an extraordinary person every Sunday since 2017, and before that she ran a daily VC newsletter at Fortune. Her book, Hidden Genius, argues that the truly exceptional don’t run on morning routines or five daily habits, but on mental models that change how they see. We talked about how she gets past the polished version people hand her, why she thinks villains are freer than heroes, and the one thing she refuses to hand over to AI even though she uses it every day. If you write, lead, or read people for a living, this one is worth your half hour.🎥 Catch all future interviews, subscribe!🎧 Prefer audio? Listen on Apple PodcastsOutline(01:13) – A cold read: what ten minutes reveals(03:10) – We are how we move through the world(03:44) – The mask, access, and Logan Paul’s lollipop(04:45) – Kevin O’Leary and the villain he plays(10:54) – Why villains get to be human(11:21) – Scaramucci’s Superman, everyone’s Batman(17:42) – Understanding who you are not(19:48) – Long-form in a short-form, AI-flooded world(22:02) – “When I write, I think”(25:20) – Reinvention and the Martha Stewart comebackMy TakeawaysWe are how we move through the world. So the line of hers I opened with is the one I keep coming back to, because it flips how most of us try to know somebody. We listen to what people say about themselves and take it as the truth, when the real signal is in how they actually move. Polina puts an enormous emphasis on access for exactly this reason; she wants to shadow a person through their day and catch the moment the mask slips.“You just really have to observe. The mask, we know the mask. These are public figures, they’re very well media trained. My goal is to destabilize the talk track a little bit, or see a contradiction that everybody has.”She told a story about Logan Paul that made it concrete: in the car, he told her he likes anime and dinosaur documentaries. Then he admitted the loud persona is a performance he switches on the second he walks onto a set. That gap between the private person and the public character is the whole game.Villains are allowed to be human. Here’s the part of the conversation that really made me think. She was talking about Kevin O’Leary, Mr. Wonderful from Shark Tank, and how he actually likes being cast as the villain.“Heroes are very limited because they’re not free. They’re expected to be perfect. Villains are allowed to be human. They can have flaws, they can get angry, they can make mistakes. People are more forgiving.”I hadn’t thought about it that way, that the villain gets more room to be a full person than the hero does. For anyone leading, that’s a real trap worth naming. The more polished and heroic the image you protect, the less permission you leave yourself to be human in front of your team.The tell is the internal monologue. What she’s really hunting for is the story people tell themselves, not the polished one they tell her, and she gets at it by asking how they imagined their life would turn out versus how it actually did, then listening to how they bridge the gap.“You’re your life’s main character, you’re the protagonist, everybody else is a supporting character. So the way you tell that story tells me a lot.”She gave the example of Anthony Scaramucci and his six-foot Superman statue, where he told her Superman is who we strive to be, but realistically we’re all just Batman, flawed and human and able to break. How someone narrates their own life explains most of what they let themselves do.“When I write, I think.” This is the one that matters most for the leaders reading this. Polina is not anti-AI; she said it helped catch a misdiagnosis when she was pregnant, and she uses it to pressure-test her thinking constantly. But she draws a hard line at the writing itself.“When I write, I think. That’s how I think. So if I just offload everything to AI, then I’m not thinking at all. It’s thinking for me, and that’s really dangerous.”She uses AI the way I’d argue every leader should, as a brainstorming partner and a sparring partner. Feed it a draft and ask what you’re missing; tell it your position and ask it to argue the other side. What she won’t do is let it do the thinking for her, which is the whole discipline behind the AI Leadership Triad. The tool sharpens your judgment; it doesn’t get to replace it.One Question to Sit WithIf AI can now imitate almost anyone’s output, the writing, the style, the answer, what’s the part of your work that only you can actually do?Polina’s bet is that it’s the human things, the noticing, the taste, the paying attention that took her years to sharpen. Watch the full conversation above for how she gets there, and then go subscribe to The Profile.About Polina PomplianoPolina Pompliano is the founder of The Profile, a newsletter of deeply reported profiles of the world’s most extraordinary people, published every Sunday since 2017. She previously ran the daily VC newsletter Term Sheet at Fortune, where she wrote more than 1,300 articles. She’s the author of Hidden Genius, a book about the mental models the world’s most successful people actually use. Subscribe to her work at The Profile.About meJoel Salinas is an AI Strategy Coach for leaders at small and mid-sized businesses and nonprofits. AI is everywhere; judgment is scarce. Joel helps leaders adopt AI without outsourcing their judgment to it, through a monthly live workshop and 90-day engagements. Creator of the AI Leadership Triad. He writes Leadership in Change.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

TL;DR - Michael Bungay Stanier has spent a decade teaching leaders to be more coach-like, and the core of it, “ask more, tell less,” matters more now than when he wrote The Coaching Habit ten years ago. In this Substack Live, he gave me four principles for leading in the age of AI: clarity over certainty, context over content, connection over cocooning, and courage over collusion. We got into why AI’s confidence is a trap, why the real work of a leader is helping people find the right question instead of handing them the answer, and the three coaching questions that still hold up in 2026. Watch the full conversation above.🎥 Catch all future interviews, subscribe on YouTube🎧 Prefer audio? Listen on Apple Podcasts🤝 Want to chat one-on-one? Book a free intro call.Outline(0:43) – Leadership WTF: what it even means to lead now(1:34) – Does coaching still matter when everyone has ChatGPT(3:12) – Ask more, tell less, and why it’s harder than it sounds(5:44) – Daniel Goleman’s six styles and the one leaders skip(8:35) – The four Cs, laid out(9:05) – Clarity over certainty(11:08) – Courage over collusion(12:45) – The sycophancy trap: six months chasing a fake theorem(14:31) – Connection, and why humans rubbing up together still matters(19:01) – Why big change plans fail: capacity and agency(23:11) – The productivity fear: save 25%, produce 25% more?(26:09) – Coaching a team in 2026: the three questions(30:27) – Three books Michael recommendsMy TakeawaysThe four Cs. This was the spine of the whole conversation, and it’s the thing I’m still going over. Michael has been sitting with a simple question, what do we actually need to do as leaders in a time of AI, and he came back with four moves. “Clarity over certainty, context over content, connection over cocooning, and then courage over collusion.” I made a chart of it because I want to keep it in front of me, and honestly, once you hear all four together, you can’t unsee the tension in each one. Every C is a choice between the easy thing AI is great at and the harder thing that’s still ours to do.Clarity over certainty. So here’s where it got real for me. Michael’s point is that AI is fantastic at sounding sure, and that confidence is exactly the trap. “AI is brilliant at being certain,” he said, and then he told a story from a conversation with Dan Ariely (the behavioral economist behind Predictably Irrational) about a researcher who wasted six months chasing a new math theorem that ChatGPT told him he’d found, and that turned out to be complete nonsense. Certainty is cheap now. The leader’s job is clarity, which is the slower work of asking what the real problem even is before you go solve the confident-sounding one.Connection over cocooning. This is the one I keep chewing on. Michael admitted something I think a lot of us feel and don’t say out loud, that one of the strangest things about AI is he almost doesn’t need to talk to other human beings anymore, because it’s just him and his agent going back and forth. “It feels like it’s human, but it’s not human.” And I sat with that, because I could open Claude right now and ask it how Michael would answer a question and get a close approximation, which is exactly the thing that should scare us a little. His answer is that leaders create more than the sum of their parts when there’s real connection, and there’s something about humans rubbing up together that no agent replaces.Capacity before change. The most practical thing he said is that big change plans almost always fail, because leaders keep pouring water into a full glass. If your people are already at capacity, a shiny new AI rollout has nowhere to land. And this landed against a real moment for me, when someone on my team heard “AI will save you 25% of your time” and asked me straight up whether that meant I’d now require 25% more output. That fear is the whole game. Michael’s take is that the promise of AI isn’t just doing more stuff, it’s creating the capacity and the agency for people to run small experiments and actually manage the change instead of drowning in it.The three questions that still workSo if you take one thing you can use Monday morning, take these. Near the end I asked Michael what coaching a team actually looks like in 2026, and he gave me three questions from The Coaching Habit that still hold up when AI can answer almost anything. The strategic question, “what are we going to say yes to, and if we say yes to this, what must we say no to?” The real-challenge question, “what’s the real challenge here?” And the learning question he closes every conversation with, “what was most useful or valuable here?” I’ve started using that last one, because it makes sure everyone walks away a little smarter, including me. I made a second card of these so you can keep them in front of you.If AI can generate every answer in your organization, what’s the one thing your people still need a human leader for? Sit with that, then watch the full conversation above, and if you want the real depth on any of this, go grab The Coaching Habit and subscribe to Michael’s Change Signal podcast.About Michael Bungay StanierMichael Bungay Stanier is the author of The Coaching Habit, one of the best-selling coaching books of all time, now celebrating its ten-year anniversary. He also wrote How to Work with Almost Anyone and hosts the Change Signal podcast, where he cuts through the blather to find what actually works in change. His whole mission is helping leaders be more coach-like: stay curious a little longer, rush to advice a little more slowly. Find his books and free resources at thecoachinghabit.com.About meJoel Salinas is an AI Strategy Coach for leaders at small and mid-sized businesses and nonprofits. AI is everywhere; judgment is scarce. Joel helps leaders adopt AI without outsourcing their judgment to it, through a monthly live workshop and 90-day engagements. Creator of the AI Leadership Triad. He writes Leadership in Change.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

Things have changed. The bar used to be produce content, produce content, produce content, and most people didn’t have the time or the persistence to keep going, so just showing up was the whole game. That bar is gone now. Anybody can type a prompt and get ten decent posts before lunch. Which means the thing that actually keeps a reader with you is the part AI can’t fake. David McIlroy has built a solopreneur business coaching creative entrepreneurs, with 34,000+ subscribers on Substack, and we spent this conversation on exactly that tension: how you grow when the tools that used to separate you from everybody else are now free to everybody else. We got into the 1:5 engagement ratio, why community became the whole point after the pandemic, and where he draws the line on letting AI touch his fiction. Watch the full thing above.🎥 Catch all future interviews, subscribe on YouTube🎧 Prefer audio? Listen on Apple Podcasts🤝 Want to chat one-on-one? Book a free intro call.Outline(1:25) – From Medium to Substack, and starting with one publication(3:37) – Youth worker to hiking blog to solopreneur(5:36) – Why the digital-course boom cooled and community took over(9:18) – Finding your why and your message(10:49) – The 1:5 ratio: using other people’s audiences(13:34) – The content bar collapsed with AI(18:07) – AI should amplify your strengths, not replace your expertise(22:27) – Using AI as an editor for fiction(23:28) – The sensitivity check: AI on a humanitarian content team(26:57) – David’s new group coaching program(29:17) – Who should reach out to DavidMy TakeawaysThe content bar hit zero. David and I got to the same place from different sides. The old advantage was volume, and volume is now free. So the question flips. If a post can come out 100% AI-created, what actually separates you from the hundred other people running the same prompt? David put it this way: “You can create. It’s the kind of content, it’s the depth that now you can go to, which makes the difference.” The depth is yours. The prompt isn’t.Borrow other people’s audiences. When your own list is small, David’s move is a rough 1:5 ratio, one thing you post, five thoughtful comments on bigger creators’ work. And he was firm that the comment has to earn its place. “It needs to be something thoughtful that adds to the conversation and demonstrates that you have some level of expertise to share as well.” Not “great idea, happy for you.” That’s the version an AI bot posts, and readers can smell it. (I get those on LinkedIn constantly, three perfectly structured paragraphs from someone who clearly never read the post.)Share the messy stuff. This is the one I’d underline for any leader building a presence online. David’s point was that people don’t connect with polished text, they connect with a real person behind it. “You’ve got to share some of the messy stuff as well, the struggles, the good times, the family stuff, the pets, the nature.” AI can generate the frameworks. It can’t hand you your kid’s drawing or your dog running through the grass, and that’s the part a reader actually stays for. It’s the same reason I keep coming back to community as the thing that carries you.AI as editor, not author. David keeps AI completely out of his fiction as a writer, but he runs finished manuscripts through it to catch plot holes and inconsistencies. “It’s working like an editor on some level. It doesn’t produce any ideas or guide the story in any way, but it helps keep me right if I’m making mistakes.” That’s exactly how I use it too. On the humanitarian side, my content team of about 25 people runs work through Claude to check whether a message written by a non-Latino would read wrong to a Latino audience. Not to write it. To catch what a human would miss and then keep going. The line David draws is the right one: the moment AI starts replacing what makes you you, you’ve stopped growing.One Question to Sit WithWhere do you draw the line, what do you let AI do, and what stays yours? The bar for producing content just hit zero, and the part that’s actually worth following is the part AI can’t fake. About David McIlroyDavid McIlroy is a strategy coach for creative entrepreneurs, a solopreneur, fiction author, and podcaster based in Northern Ireland, with 34,000+ subscribers across his Substack publications. He helps creators build a personal brand, strategy, and system for clarity and growth. His new weekly group coaching program opens Tuesday, July 28, 2026. Subscribe and reach out to him on Substack.About meJoel Salinas is an Executive AI Coach for leaders at small and mid-sized businesses and nonprofits. 1:1 coaching, team workshops, and AI strategy work built around amplifying what your team is already good at. Creator of the AI Leadership Triad. He writes Leadership in Change. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

Travis Rosser co-founded Kajabi, the platform creators have used to sell more than $10 billion in courses, coaching, and knowledge, and he joined me on Substack Live to trace the whole arc. We went from a Shark Lagoon PDF he sold as a kid to a company that put publishing tools in everyone’s hands. Along the way he unpacked why he tells builders to fall in love with their customer’s pain instead of their idea, his Four P’s of knowledge capital, and why AI is turning all of us from creators into builders. If you’re sitting on expertise and wondering what to do with it, this is the one to watch.🎥 Catch all future interviews, subscribe on YouTube🎧 Prefer audio? Listen on Apple Podcasts🤝 Want to chat one-on-one? Book a free intro call. Outline(00:04) – Welcome, and going live on Substack(00:53) – A sprinkler toy, a taco, and a lifelong side-hustle habit(02:39) – Shark Lagoon: the first thing he ever sold online(04:36) – Kajabi’s first customer(05:28) – Launch day, and a million dollars in 24 hours(08:44) – The Saturday the support tickets caught fire(09:56) – The survey that revealed what Kajabi really was(10:32) – From $10 billion to “we’re all becoming builders”(12:13) – “Fall in love with your customer’s pain, not your idea”(15:24) – Knowledge capital and the Four P’s(22:57) – Skills as the new digital product, and taste as the new edge(36:43) – What Travis is building now: Wazi and PageSumoMy TakeawaysFall in love with your customer’s pain, not your idea. Here’s the line I keep coming back to from the whole conversation. Travis has been building things his entire life, and the thing he kept circling back to is that being good at creating stuff is exactly what makes you fall in love with the wrong part of it. “When you’re good at creating things, you fall in love with the idea too much,” he said. “But if you’re not helping someone, if you don’t provide value to them, it doesn’t matter.” What I pushed on with him is how much sharper that line cuts right now, because once anyone can build almost anything over a weekend, a lot of us are going to mistake “I can make this” for “someone actually needs this,” and those two things were never the same.Everybody is sitting on knowledge capital, and most of us take it for granted. So here’s the framing from his book You, Inc. that I want more leaders to steal. Travis calls it the Four P’s: Profession, Passion, Pain, and Problems. His claim is that all four are knowledge somebody else would pay for, and we discount them because they come easy to us. “Everybody is an expert in their own life,” he said, and the example that got me was his kids yelling across the house about how to beat a level in Minecraft. In that one small section of life, his oldest son was the expert. So the thing he leaves you with is simple and a little uncomfortable: you already have something worth teaching, and the only real work is looking back at your own trail long enough to notice what it is.We’re shifting from a creator economy to a builder economy. This is the part I was leaning in for, because it’s exactly what I’ve been living. Travis’s take is that AI has handed everyone the capacity to build, not just to make content. “AI has given us the capacity to build, where anybody can build software, anybody can build agents, workflows,” he said, “and I really encourage anybody that watches this to go start doing that just for fun on the side.” I told him about the workout app my wife and I both wanted but couldn’t find, so one weekend I sat down in Claude Code (Anthropic’s coding tool you run by talking to it), took screenshots of the two apps we were each paying fifteen dollars a month for, listed the features we actually wanted, and built our own. I’ve used it almost every day for six months. That used to take a team and a budget, and now it takes a curious Saturday.In the age of infinite output, taste is the edge. So if anybody can build anything, what’s actually scarce now? Travis’s answer is taste, and taste comes from being an expert who knows what to leave out. He pointed to In-N-Out here in Southern California, how the whole brand is a curated menu, a few things done well instead of a wall of options. “It’s really good at producing a lot of stuff quickly,” he said about AI, “but how do you have taste? How do you curate the good? That’s the next real expert, the person who knows how to navigate that and still produce high-quality stuff.” His advice for getting started is to build in a vacuum for a while and be your own first customer, because the fastest way to develop taste is to make something you’d actually use. That’s the same thread of adaptability and creativity I keep writing about in the AI Leadership Triad. The tools got cheap, so judgment is the job now.One Question to Sit WithWhat’s the one pain, yours or a customer’s, that you’d build for first now that the tools aren’t the hard part anymore?Watch the full conversation above, and then go follow Travis Rosser and check out what he’s building at Wazi and PageSumo.About Travis RosserTravis Rosser is the co-founder of Kajabi, the platform creators have used to sell more than $10 billion in courses, coaching, and digital products. He’s the author of You, Inc., a book about turning your own knowledge into a business through what he calls the Four P’s. These days he’s building two new tools with AI: Wazi (wazi.ai) and PageSumo (pagesumo.com). Follow his work on LinkedIn.About meJoel Salinas is an Executive AI Coach for leaders at small and mid-sized businesses and nonprofits. 1:1 coaching, team workshops, and AI strategy work built around amplifying what your team is already good at. Creator of the AI Leadership Triad. He writes Leadership in Change. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans.Thank you Colette Molteni, Claire Machado, Duncan The Sage, Tiffany Farley, Chris Winter, and many others for tuning into my live video with Travis Rosser! Join me for my next live video in the app. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

Most of us start a business to get our time back, and somehow end up the one person it can’t run without. In this Substack Live I sat down with Cory Blumenfeld, a five-time founder who built a virtual assistant company called BlueMoso, on how to stop being the bottleneck in your own company. We get into why the system usually only exists in the founder’s head, how to hire for the match instead of just the skill, and the line I keep coming back to: AI is for tasks, people are for outcomes. Watch the full conversation above.Also, click below to subscribe on Apple Podcasts! 👇Outline(00:00) – Intro: who Cory is and how he got to Substack(01:20) – Why human content is becoming a premium tier(01:56) – Five businesses, zero experience, and learning by building(08:42) – The founder bottleneck: leading from the backseat(10:06) – If you got sick tomorrow, would the business survive?(14:28) – Type-A founders, trust, and hiring for the match(16:46) – The hiring framework: skill, work style, communication, personality(20:03) – VAs are for outcomes, AI is for tasks(22:10) – Humans with AI, not AI versus humans(23:25) – Everyone is starting at zero with AI(33:49) – Why he named it Taking My Time BackMy TakeawaysThe founder is the bottleneck. So the whole conversation really starts here. The minute a company can’t survive without the founder in every decision, the founder has stopped leading and started blocking. Cory said it about as bluntly as it gets:“Any founder, any CEO trying to lead from the backseat drives the car off the road.”I’ve watched this one up close, and the test I keep coming back to is simpler than people want it to be. If it’s all hinging on you, you’re not leading well, you’re just busy.The system only exists in your head. Here’s the part founders hate to hear. When delegation fails, we blame the hire. Cory’s take is that the real problem is upstream, because the playbook never left your head. He fixed it by writing his whole content process down so completely that his assistant couldn’t fail.“I documented my strategy, made it super clear so they couldn’t fail. I set them up for success, and it started working.”That reframed it for me. The bottleneck usually isn’t your team’s ability, it’s the stuff you’ve never bothered to get out of your own head.Hire for the match, not just the skill. When I asked Cory how he actually trusts people enough to step back, he didn’t start with skill. He started with fit, work style, communication style, personality, and then skill.“Hiring someone is not just skill alone. What’s their work style? What’s their communication style? The match is everything.”And he was honest about why most of us struggle with it. A lot of founders are type-A with trust issues, me included on some days. If you hired someone for a skill you don’t have, the worst thing you can do is hover. Give them the room to be good at the thing you brought them in for.AI is for tasks, people are for outcomes. This is the line I’ll be repeating for a while. Cory draws a clean line between what you hand a person and what you hand a machine.“You don’t bring in a virtual assistant to work on a task. You bring them on to deal with an outcome. You bring on AI to deal with individual tasks.”I told him on the spot that’s a quote CEOs could put on their walls, and I meant it. It also points at where this is going. When everyone has AI doing the repetitive work, the human part, the judgment, the relationship, the actual experience, stops being the cheap part and becomes the premium one.Figuring out where AI fits and where your people have to stay is most of what I work on with the leaders I coach. If you want to talk it through, my calendar is here.One Question to Sit WithIf you got sick tomorrow and unplugged for two weeks, would your business still be standing when you got back? Sit with the honest answer.Watch the full conversation above, and go subscribe to Taking My Time Back, Cory’s Substack on helping founders win their time back.About Cory BlumenfeldCory Blumenfeld is the Founder and CEO of BlueMoso, a managed virtual assistant service for founders, executives, and agencies, with a vetted talent pool of more than 70 assistants and specialists. He’s a five-time founder with two exits across health tech, fintech, and outsourcing, and he runs his companies remotely from Playa del Carmen. He writes Taking My Time Back on Substack.About meJoel Salinas is an Executive AI Coach for leaders at small and mid-sized businesses and nonprofits. 1:1 coaching, team workshops, and AI strategy work built around amplifying what your team is already good at. Creator of the AI Leadership Triad. He writes Leadership in Change. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans.Thank you Ankita Chatrath, Janet Macaluso, and many others for tuning into my live video with Cory Blumenfeld! Join me for my next live video in the app. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

Much of the AI conversation in the business world, for those who have not used AI much, is some version of: kick your feet up, drink the piña colada, watch your revenue shoot up. I’ve seen that promise up close on the fundraising side of the humanitarian work I do, and on a lot of teams AI is the enemy in the room before it’s anything else. Mallory Erickson started exactly where most of her sector started, nervous, protective, sure AI was going to hollow out the most human work there is, and then she built something that does the opposite. She’s spent her whole career on connection, she’s trained over 100,000 fundraisers, and instead of letting AI replace the fundraiser, she flipped the entire thing and made the donor the robot so the human gets to practice. Watch the full conversation above.Also, click below to subscribe on Apple Podcasts! 👇Outline(0:31) – Bringing AI into deeply human work without hollowing it out(1:03) – From accidental fundraiser to founder of Practivated(2:30) – Why she avoided tech, and the fear that started it(4:16) – Personalization at scale, but for fundraisers(9:26) – The rise of “robot fundraisers” and why it broke her(10:28) – The flip: what if the donor is the robot?(15:50) – Start with the problem, not the AI(21:55) – Rolling AI out to a hesitant team: validate the fear(25:26) – Give your team a stipend to play(31:42) – The results: 280% more human donor touchpoints(32:39) – The LeBron test: the best still put in the reps(38:11) – A charge to practitioners: build what you needMy TakeawaysThe flip. Most AI products aimed at fundraisers are built to replace the fundraiser, the autonomous “robot fundraiser” that writes the appeals and works the donors so you don’t have to. Mallory watched that trend and reacted the way I wish more people would, by refusing it: “If our answer to fundraiser burnout is to replace human fundraisers with robots, we can do so much better than that.” So she flipped it. “What if the fundraiser isn’t the robot? What if the donor is?” Inside Practivated the AI plays the donor, the human role plays the hard conversation, gets scored, and builds the muscle memory before the real ask. I keep coming back to that flip, because it’s the same move every leader should be making, which is to point AI at the practice and the reps instead of at the people doing the work. It’s the version of AI I argued for in Can AI Make You a More Human Leader?, and she actually built it.Start with the problem, not the AI. This is the part of the conversation I keep coming back to, because it’s exactly what I tell the executives I coach. Mallory has closed deals lost on purpose, walked away from organizations that came to her wanting “more AI” with no real problem behind it. Her test is simple: what have you been trying to solve that you’ve thrown everything at and still can’t crack, and is there an emerging tool that could finally move it? As she put it, “AI is not the point. The goal is to solve your challenges.” Validate the fear before you roll anything out. I asked her how she’d introduce AI to a team that’s all over the map on it, and her first move surprised me, because it had nothing to do with the tool. She said there shouldn’t be AI adoption without first being ready to acknowledge and validate people’s fear, not to agree that AI is scary, just to give the fear a place to exist before it hardens into resistance. “It’s really important that we’re acknowledging and validating how people feel.”Then she does something I love, she gives her whole team a monthly stipend to just play, with two rules: have a hypothesis going in, and come back and tell the team what you learned. The reps don’t stop because you’re good. The skeptic line Mallory hears most is “I’ve been fundraising for twenty years, I don’t need to practice.” Her answer is the one I’m going to start stealing in my own coaching: “Can you imagine if we said LeBron James is such a good basketball player, he doesn’t need to practice anymore? Simone Biles? Absolutely not. The people at the top of their game are putting in the reps.” And the numbers are backing her up, a 280% increase in human-driven donor touchpoints, onboarding cut from eight weeks to two, ask effectiveness up 33% in the first 30 days. AI didn’t replace the human in any of that, it gave the human a place to practice so they could show up more present when it actually counted.One Question to Sit WithWhere in your own work are you reaching for AI before you’ve named the problem it’s actually supposed to solve? Mallory’s whole practice is built on refusing to skip that question, and I haven’t stopped chewing on how often the rest of us do.Watch the full conversation above, and then go follow Mallory’s work at Practivated and her What the Fundraising podcast.About Mallory EricksonMallory Erickson is an executive coach, fundraising consultant, and the host of the What the Fundraising podcast. She has trained over 100,000 fundraisers, co-founded the Fundraising AI initiative, and is the founder of Practivated, an AI practice platform where fundraisers role play donor conversations and get coached on what to do differently next time. Her North Star, in her own words, is improving the lives of fundraisers. You can find her work at practivated.com.About meJoel Salinas is an Executive AI Coach for leaders at small and mid-sized businesses and nonprofits. 1:1 coaching, team workshops, and AI strategy work built around amplifying what your team is already good at. Creator of the AI Leadership Triad. He writes Leadership in Change. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans.Sidenote… do you write on Substack? Build smarter, not just harder, with NewsletterCompass.com. As a co-founder, I’m giving you 50% off for life… 👇 This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

If you’ve spent any time trying to make sense of where AI is actually going, not the headlines but the structure underneath all of it, you’ve probably run into Gennaro Cuofano’s work without knowing it was his. He built The Business Engineer (spun off from FourWeekMBA) into a research hub more than 90,000 people follow, and he just launched something new called The AI Supercycle. I wanted to sit down with him because he maps this stuff for a living, and his read on it is different from almost everyone else’s. His core claim is that we keep comparing AI to the internet when the better comparison is the 1950s, the moment we built the computer for the first time. That one reframe changes where you look for advantage, who you watch, and how far ahead you’re allowed to plan. Watch the full conversation above.Also, click below to subscribe on Apple Podcasts! 👇Outline(1:10) – From FourWeekMBA to The Business Engineer(4:34) – Why launch The AI Supercycle now(8:18) – The semiconductor moment, not the internet(14:43) – The nine-layer map and why governance sits on top(17:41) – Spinning hundreds of agents to run a business(19:45) – Governance, government, and the Palantir layer(24:01) – Why human conversations beat the AI content flood(26:35) – The Builder PM and the role that split in two(31:25) – Orchestrating agents in real disaster response(38:24) – From SaaS to Agent-as-a-Service(40:02) – Audience question: what happens to SaaS?My TakeawaysThe semiconductor moment. Gennaro’s whole thesis hangs on a historical analogy, and it’s the thing I keep coming back to. Everyone wants this to be the internet, a 20 or 25 year cycle. He thinks that’s the wrong map. As he put it: “We’re building the computer. It’s not the web. It’s the 50s, 60s, 70s, when we built the computer for the first time. This is a 30 to 50 year cycle.” What got me is that most analysts I talk to are afraid to forecast past three years right now, and here’s someone calmly drawing a map for the next three decades.Governance on top. I told him I loved his nine-layer map of AI, because he does something nobody else does, he puts governance at the very top, above the models, above the chips, above everything. His reason is blunt: the frontier now answers to government, and there’s no getting around it. “That’s why the governance layer is going to become one of the most important for the top of the frontier. There’s no way out.” He pointed to Palantir already routing different AI models through everything the government does. If you only read the tech headlines, you miss the layer that actually decides what ships.The Builder PM. Gennaro’s been a filter between clients and technical teams for years, so this one is lived, not theoretical. Building got easy. Everything around the build, the integration, the deployment, the org politics, got harder. So the product role split. The new version turns a client’s specs into something testable in six months instead of three years, which makes the PM a hybrid of builder and orchestrator. I see the same thing in my World Relief work, where we now run a team of agents for disaster response and a human has to sit at the center coordinating the writers, the researchers, the photographers. You stop being the doer and become the architect.From SaaS to Agent-as-a-Service. His prediction for the next 18 months is that per-seat, per-human pricing breaks, because your biggest customer stops being a person and becomes a fleet of agents consuming your software millions of times over. “There will be many SaaS companies worth 100x more, because now with the agents you get a level of consumption you didn’t have before.” The way I said it back to him: the pie went from being this big to unlimited.Sidenote… do you write on Substack? Build smarter, not just harder, with NewsletterCompass.com. As a co-founder, I’m giving you 50% off for life… 👇One Question to Sit WithWhen everyone has the same frontier models for twenty dollars a month, where does your advantage actually move to? Gennaro’s answer is “down the stack, toward governance and infrastructure,” and I haven’t stopped chewing on it since.Watch the full conversation above, and then go subscribe to The AI Supercycle. It’s the clearest map of this moment I’ve found.About Gennaro CuofanoGennaro Cuofano is the creator of The Business Engineer, a deep-tech research hub spun off from FourWeekMBA, the business-model-strategy blog he started in 2015 and grew past 90,000 subscribers. A tech executive by day, he writes about the structural shifts reshaping business in the AI era and just launched The AI Supercycle, a newsletter and podcast decoding where the next 30 years are heading. Subscribe at supercycle.ai.About meJoel Salinas is an Executive AI Coach for leaders at small and mid-sized businesses and nonprofits. 1:1 coaching, team workshops, and AI strategy work built around amplifying what your team is already good at. Creator of the AI Leadership Triad. He writes Leadership in Change. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

AI keeps getting better, so why aren’t your results getting better? Bryan Cassady’s answer: Most people are getting more output, not better work, because they skip the thinking and go straight to the tool. In this Substack Live we get into his Type 3 error (doing the wrong thing, fast), why objectives have to come before any tool, the real $11,000-a-year cost of AI that most leaders never count, and what a generative organization actually is. If your team has AI and still isn’t getting results, this is the conversation to watch.Also, click below to subscribe on Apple Podcasts! 👇Outline(00:00) – Bryan’s mission: a million people getting results from AI by 2027(01:02) – Better models, worse results: the human half of the equation(03:16) – How Bryan started: “six months ahead of everyone else”(05:16) – Objectives first, tools second(07:33) – The Type 3 error: doing the wrong thing, but doing it right(09:57) – The Dan Ariely story: six months on a hallucinated theorem(11:28) – Think first: Einstein’s 55 minutes on the problem(15:26) – From an answer economy to a question economy(16:20) – Strategic clarity and the $11,000 cost of AI(18:48) – What a generative organization actually is(24:00) – The 3% AI can’t do, and why it sets you apart(31:00) – Bryan’s giveaways: free books, tools, and a beta courseMy TakeawaysThe Type 3 error. So here’s the frame I keep coming back to from this whole conversation. Bryan put it like this: a Type 3 error is when “you’re doing the wrong thing, but you do it right.” And the problem with AI is you can now do the wrong thing really fast and feel great about it the whole time. I’ve had people hand me a polished 25-page deliverable that nailed every step of a question nobody actually needed answered.Objectives first, tools second. Bryan’s line on this is the one I’d put on the wall: “AI first is silly. It’s like being a carpenter who wants to be a hammer-first carpenter. A hammer can do cool things, but it doesn’t do everything.” Most leaders are out shopping the 75,000 listings on a site like There’s an AI for That (a directory of AI tools) when the real first move is naming the objective and then picking the tool that serves it. Get that order wrong and you just bought a faster way to drift.The $11,000 nobody budgets for. Here’s the part that should stop every leader who thinks AI is a $20-a-month decision. Bryan cited a Gartner study putting the time people spend controlling, revising, and re-editing AI output at around five hours a week, which works out to roughly $11,000 a year for a typical US knowledge worker. “Do you get $11,000 more benefit from using AI? Of course you can, but only if you do it smart.” Most don’t. And that’s before you count what poorly rolled-out AI does to a team’s trust in their own leadership.The 3% AI can’t touch. This is where it got good. Bryan's argument, borrowed from an innovation method called TRIZ, is that about 97% of what we call innovation is really recombining things that already exist, and AI does that better than almost any human. But the last 3%, the genuinely new, the thing that doesn't exist yet, that's still you.“Humans have an ability to look forward. AI has an ability to look backward.” That 3% is the creativity and judgment no model hands you, which is exactly what the AI Leadership Triad is built around. Pair it with his bigger shift, that we’ve moved “from an answer economy to a question economy,” and the job gets clearer: stop racing the machine on answers and get very good at the question.Two things Bryan is giving Leadership in Change readers:* Both of his books, free, plus his PDF innovation tools — books.genorg.ai* A free, private check on how you actually use AI: paste his assessment into ChatGPT or Claude, and it scores you 0 to 10 from your own chat history — get the assessment* A free spot as a beta tester for his new AI course (10 lessons, 10 minutes a day, with a before-and-after read on how you actually use AI) — grab a beta seat hereOne Question to Sit WithWhen’s the last time you spent five whole minutes on the problem before you opened the AI? Bryan says when he asks a room that, almost every hand goes down. Watch the full conversation above, and then go grab Bryan’s free books and tools at books.genorg.ai.About Bryan CassadyBryan Cassady is the founder of GenOrg and the author of The Generative Organization. He’s an AI keynote speaker who has trained more than 40,000 people, and says he’s now helped around 90,000 toward his goal of a million people getting real results from AI by 2027. He also sits on the board of the US association for TRIZ, the structured innovation method he teaches. Get both of his books and his innovation tools free at books.genorg.ai.About meJoel Salinas is an Executive AI Coach for leaders at small and mid-sized businesses and nonprofits. 1:1 coaching, team workshops, and AI strategy work built around amplifying what your team is already good at. Creator of the AI Leadership Triad. He writes Leadership in Change. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans.Thank you Farida Khalaf, Claire Machado, Duncan The Sage, and many others for tuning into my live video with Bryan Cassady! Join me for my next live video in the app. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

This one got into the part of AI adoption nobody really wants to talk about. Ryan Deeds runs AI at ALKEME, an insurance company that bought its way from seven agencies to ninety-three in about four years, and his whole argument is that the technology was never the hard part. The hard part is getting fifteen hundred people to actually trust a tool and use it. We talked about the golden path, why every rollout fails for the same reason, the eighteen months it really takes to hit adoption, and the bot pipeline that lets anyone at the company build their own software. Watch the full conversation above.📩 Subscribe to Leadership in ChangeOutline(00:11) – Scaling without breaking culture(00:49) – Seven agencies to ninety-three in four years(02:07) – From data guy to Head of AI(03:41) – The golden path across 150 workflows(05:32) – “AI is a bunch of hype” and the cultural work underneath(08:17) – Why every rollout fails for the same reason(12:54) – The 85% that fail, and what they all skipped(14:21) – Fear, mistakes, and fifteen dead initiatives(15:05) – Eighteen months to 70% adoption(19:43) – Why the model wars are wasted noise(21:14) – There’s no easy button(24:05) – The bot pipeline that lets anyone build(27:19) – Scaling AI without it blowing up in your face(29:23) – The most overrated AI adviceMy TakeawaysThe failure is always culture. Ryan has built nine CRMs and implemented seven more, and he says the result never changes. “Got nothing to do with technology. It’s culture.” I brought up the stat that 85% of AI implementations fail, and his read matched what I see all the time: people get handed a tool, get told to use it, and decide not to, either because they think it’s there to replace them or they don’t trust the people who bought it.There’s no easy button. Ryan’s least patient moment was about the model wars. “You cannot judge current state AI in current state,” he said, and the people arguing over which model beat which this week are usually the ones not actually building anything. What matters to him is boring on purpose: how many people used it, how many minutes did it save. “If I was judging what I created, I’d be freaking Elon.” That’s the line I keep coming back to, because most of us are measuring the wrong thing.Eighteen months to seventy percent. I appreciated how honest he was about the timeline. He told his CEO up front it would take about eighteen months to reach full adoption, and that full adoption, in his world, is 70%. The pushback he plans for doesn’t come from the technology. It comes from moving people out of a culture where nobody was accountable and into one where everybody can see your numbers.Closest to the work is clean. This was the part that genuinely surprised me. ALKEME has fifteen hundred employees and a build team of nine, so Ryan built a pipeline instead. An employee emails an idea, a bot pins down the narrowest version of success, another bot builds the MVP on the company’s own infrastructure and sends back a working link to iterate on. “I would way rather empower you, employee E, to bring your concept to fruition.” The person closest to the problem builds the fix, inside the guardrails.Don’t pour a bucket of AI water on everything. For an insurance company, a broken tool isn’t a small thing, so I asked how he moves this fast without it blowing up. His answer was discipline about scope. “It’s not just pour a bucket of AI water on everything and see where it hits.” They ran fifty thousand historical submissions through one tool before they trusted it, locked permissions to each user, and pushed everything through a pipeline that gets checked. “We’re just very careful about where it touches.” It’s the same discipline ALKEME brings to the coverage side, where a single missed risk like a cyber attack is exactly what their clients are paying to be protected against. If your business carries that exposure, their team handles cyber insurance directly.If you’re the person inside your company trying to get AI actually adopted and not just installed, that’s most of what I work through with teams. You can start at jsalinas.org and book a free call with me.If you rolled out an AI tool tomorrow and nobody used it, would you call that a technology problem or a culture problem? Sit with which one you’d actually fix first.Watch the full conversation above, and go connect with Ryan Deeds on LinkedIn and see what ALKEME is building.About Ryan DeedsRyan Deeds is Head of AI & Enablement at ALKEME, an insurance company that has grown to around 93 agencies and 1,500 employees in roughly four years. He spent 30 years in the insurance agency space, hosted The Digital Broker podcast from 2017 to 2019, and now builds the internal tools and adoption systems that let ALKEME scale AI without losing its culture. Connect with him on LinkedIn.About ALKEMEALKEME is a national insurance company built from more than 90 independent agencies, serving clients across commercial, personal, and specialty lines. One of those lines is cyber insurance, coverage that protects businesses against cyber attacks, data breaches, and the operational fallout that follows. If your organization needs to think seriously about cyber exposure, talk to ALKEME.About meJoel Salinas is an Executive AI Coach for leaders at small and mid-sized businesses and nonprofits. 1:1 coaching, team workshops, and AI strategy work built around amplifying what your team is already good at. Creator of the AI Leadership Triad. He writes Leadership in Change. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

I keep running into the same thing when I talk to leaders about AI. They’re excited and they’re exhausted… at the same time. They see how capable the models have gotten, and in the same breath they tell me they’re starting to feel a little obsolete. Curious and anxious, sitting in one person, at the same desk. I wanted to talk to Liz Fosslien and Mollie West Duffy about exactly that, because they’ve spent their whole careers on emotions at work, and now almost all of that work is affected by AI. What you get in this one is the part of the AI conversation almost nobody is running: the feelings underneath the rollout, and what a leader actually does about them. Watch the full piece above.Subscribe on Apple Podcasts for FreeOutline(00:00) – Welcome(00:38) – Excited and exhausted: the leader’s double bind(01:48) – Where emotions at work began(04:01) – The full mix: amazing and existential, in one person(06:03) – What a team really asked me about AI(07:42) – The “AI optimists only” trap(08:08) – Why emotions block learning(11:49) – The stoic-leader shift(17:33) – The change curve: anger to energy(22:32) – Build trust before you measure adoption(25:13) – Mandates fail, agency works(27:13) – Inside their AI workshops, and where to find themMain TakeawaysThe full mix is the normal state. The thing I want every leader to hear is that excitement and dread aren’t two different camps of people, they’re the same person sitting in one chair, which is exactly why this is so hard to manage. Liz put it like this: “Every single person contains this complete mix of emotion. At some level they say, oh, it’s amazing, it’s way better than Google, it can help me so much. But then of course, what does this mean for my job, for who I am?” The leader who pretends only the excited half is real is usually the one whose rollout starts going sideways three months in, because the other half doesn’t disappear, it just stops getting said out loud.You can’t learn while you’re scared. This is the line I’m still going over. Mollie walked through the neuroscience of it: “When you are feeling anxious, when you are feeling scared, when you are feeling angry, you’re not in an optimal place to learn a new tool.” Then she made it concrete. “I’m here for the training on how to use ChatGPT, but I’m really worried about what it’s going to do to my job, and I’m angry about what it’s doing to the environment. I’m not really going to be giving 100% of my attention to how to click around the tool.” I had a chat recently coaching a marketing group at a nonprofit, and within two minutes I realized they didn’t care about prompts or tokens. They were asking how they could use AI when it’s doing what it’s doing to the climate, and how a writer uses a tool trained on copyrighted work. There’s a whole foundational layer most of us skip, and the training slides right off when you do.We don’t get to skip the steps. Mollie’s change curve is the frame I keep coming back to. “We all have to go through anger, apathy, frustration, and your productivity drops. And that’s normal. Then when we move through that, we can begin to get engaged and excited and have energy around that. We don’t get to skip these steps as humans.”The part that reframed it for me is that most leaders are already further along that curve than their own team, so they’re standing on the far side wondering why everyone won’t just cross. People hit the dip at different moments, especially on a big team, which means a leader is managing a dozen different curves at once, not one.It’s okay to give some of the time back. This is where I admitted my own fear on the call, the one I think a lot of people are holding. If I start using AI and suddenly I’m producing two or three times as much, I’m afraid that just becomes my new minimum, and now I have to hold that pace forever. Liz met it head on: “It’s actually okay if some of the time saved your team takes back for themselves. It doesn’t all have to be reinvested in work. Workforces are so burnt out. The average person, our nervous system, is completely fried.” Saying that out loud, as the leader, is part of what makes adoption possible in the first place.The play I’d actually run this weekBecause this slot runs a little longer than my usual live recap, I want to leave you with something you can use on Monday, pulled straight from what Liz and Mollie laid out.* Name the mix out loud, briefly. Nothing elaborate. A short, honest recognition like “I’m feeling some of this too, and here’s the plan moving forward.” Mollie called it a brief recognition followed by the path, and it’s the tightrope between spewing every emotion and pretending you have none.* Pair a quick win with one real limitation. Liz’s most practical move. Help your team get a fast, obvious win with AI, then show them one place it falls flat. That combination lets people lean into the excitement and lower the anxiety at the same time, because now they trust both the upside and their own judgment about where it doesn’t belong.* Say the change is big, in public. In an all-hands or your enablement session, recognize out loud that this is a real change and that people are moving through real emotions at different speeds. That one sentence gives people permission to be where they actually are.* Build the trust before you measure. Liz was blunt about this. If you haven’t invested in trust up front, your survey just comes back “I feel great, it’s amazing,” and then weeks later you find out people aren’t using it, or they’re actively sabotaging it. Trust first, honest data second.* Give agency, not a tracker. Enablement, training, and time to learn, yes. Surveillance of daily usage, no. Let some of the time saved go back to people, and ask whether they’re using the right tool for the right job rather than how many tokens they burned.Where are you on the change curve right now, and have you actually let yourself name it out loud, or are you the leader who’s been pretending only the excited half is real? Watch the full conversation above, and then go subscribe to Liz and Mollie. It’s one of the few places putting the human side of this moment first.About Liz Fosslien and Mollie West DuffyLiz Fosslien and Mollie West Duffy are the authors and illustrators behind No Hard Feelings and Big Feelings, two books on the emotional reality of work and life. Liz draws every illustration by hand, leads content work at Atlassian, and is deep in research on AI transformation. Mollie works in org and leadership development at Lattice. Together they publish the Liz and Mollie newsletter and run AI workshops for leaders and for whole teams, built around the change curve and grounded in research people can use the next day. You can follow them on Instagram and subscribe to their newsletter here.About meJoel Salinas is an Executive AI Coach for leaders at small and mid-sized businesses and nonprofits. 1:1 coaching, team workshops, and AI strategy work built around amplifying what your team is already good at. Creator of the AI Leadership Triad. He writes Leadership in Change. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

So this one is about trust, and why it might be the only thing left that AI can’t manufacture for you. I sat down with Dr. Christopher Chou, the CEO of The Christian Post. We got into why people don’t adopt AI when they don’t trust the leaders handing it to them, what it cost his team to stand by a story when the platforms told them to apologize, and the one thing a human brings to the table that a model never will. If you lead anything right now, this is the conversation I’d point you to.Outline(00:00) – The value of trust(01:07) – Saying yes, and praying for the newsroom(03:03) – Translating trust from relief work to a newsroom(07:42) – Adoption is a trust problem, not a tool problem(08:53) – The team member who heard “AI” and felt fear(10:53) – Why it’s a brutal moment to run a newsroom(12:48) – Not negotiable, not adjustable, not for sale(16:39) – Op-eds from both sides, and nine months off Twitter(20:46) – When AI summaries took 20% of search traffic(23:07) – What a human brings that AI can’t(29:46) – Journalists who are Christians, not Christian journalists(32:50) – Three books worth your timeMy TakeawaysAdoption is a trust problem before it’s a tools problem. When I talk to CEOs trying to bring AI into their organizations, the biggest misconception I see is that people will adopt a tool just because it’s good. They won’t. If your team thinks you brought in a new tool to replace them in six months, it doesn’t matter how good it is; they’re never going to touch it. Chris kept the human piece at the center of the whole thing: “Even when we’re talking about AI, it still has to be about people.”Trust gets built brick by brick, and it comes apart fast. Chris said there’s no shortcut: “It’s day by day, story by story, brick by brick, you have to build.” Then he told me what that actually costs. The Christian Post got suspended from Twitter for nine months over a post they believed was true, with 180,000 followers on the line, because they refused to apologize and call it wrong and hateful. “Those are the moments you need to stand by your convictions.” They ate the loss. That’s what a track record looks like when nobody’s watching.The fear in the room is real, so name it. Chris told me about encouraging one of his team members to use AI more, and the immediate reaction was fear that it would replace them. His read was that you can’t skip past that. “You have to address the worries. You can’t just force it.” You meet people where they are, or you don’t get to the next step at all. I’ve watched leaders try to sell their way past that fear, and it never works.The thing a human brings is the thing AI can’t. Chris framed it as a question his team keeps asking: “What is it that a human person brings to the table that AI is not going to be able to bring?” Lived experience. Relationships. Knowing what’s going to matter tomorrow. He put it in a line I’m still going over: “The Bible tells us birds don’t worry about tomorrow. But people do.” That worry, that human stake, is exactly what AI doesn’t have. It’s also the easiest way to tell whether something was written by a person.If you’re a leader trying to bring AI into your team without breaking the trust you’ve spent years building, that’s most of what I do in my coaching work. You can start here.One Question to Sit WithIf anybody can now produce infinite content for almost nothing, what are you putting out that someone would actually choose to trust?Watch the full conversation above, and go subscribe to TCP Leaders, Chris’s Substack for Christian leaders. And check out The Christian Post, free to read, because they believe news is a public service. About Dr. Christopher ChouDr. Christopher Chou is the CEO of The Christian Post, one of the largest Christian news outlets in the country, where he has led since 2018. He writes TCP Leaders on Substack, built to help Christian leaders navigate the work of leading. His newsroom defines itself by a simple line: journalists who are Christians, not Christian journalists, with a first duty to the facts and the truth. Subscribe to follow his work.About meJoel Salinas is an Executive AI Coach for leaders at small and mid-sized businesses and nonprofits. 1:1 coaching, team workshops, and AI strategy work built around amplifying what your team is already good at. Creator of the AI Leadership Triad. He writes Leadership in Change. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

TL;DR. So this is the question I keep circling in 2026: if AI can spin up an infinite amount of content from basically nothing, what’s still worth anything? I brought on Michael Schreiber to answer it, because he’s spent years inside the rooms that set the standard, New York Times, HBO, ABC, NBC, and now runs MediaFeed, a content syndication company, plus a local podcast in his New Jersey town. We got into the slop problem, why the smartest move is teaching people to do the thing you sell, what trust actually looks like now, and the moment his co-host read his AI-written draft and told him to knock it off. Watch the full conversation above.Outline(00:13) – Welcome(01:05) – From newspapers to MediaFeed(05:26) – The content funnel, top to bottom(07:23) – Why you resist the urge to sell(10:08) – Teach them to fish, they still pay you(13:43) – What trust looks like in 2026(14:17) – Lazy AI versus strategic AI(18:33) – The tidal wave of slop(21:23) – Canonical tags and being known for something(30:06) – “This is s**t. You’re a good writer.”(43:52) – Denial of DeathSubscribe to get all future episodes and articles.My TakeawaysResist the sell, or lose the trust. Michael’s whole model runs on real editorial content, and the hardest discipline in it is refusing to sell inside the piece, even when the piece only exists because you have something to sell. His reasoning landed for me because it cuts both ways. “People are smart enough to figure that out and will undermine your brand ultimately. And it also probably won’t help your sales.” So you lose the trust and you don’t even get the conversion. That’s the worst trade in content, and most people make it without noticing.Teach people to fish. Here’s the counterintuitive one. Michael talked about creating content that shows people how to do, on their own, the exact thing his client’s service provides. Sounds insane until you hear him out. “You can teach people how to fish. They’re still going to want you to go fishing for them sometimes.” A small slice does it themselves, a much larger slice reads it and goes, that sounds like a lot of work, I’ll just pay you. You become the encyclopedia Britannica of whatever it is you do, and the trust comes with it.“This is s**t. You’re a good writer.” This is the moment I’ll be telling people about. Michael tried handing his podcast write-ups to AI, fed it samples of his own writing, the whole thing. His co-host read it and said, pardon the French, “this is s**t, you’re a good writer, what the hell are you doing?” So he stopped and went back to writing them himself. I felt that one, because it’s exactly why I still write my own Monday and Thursday pieces by hand and only bring AI in afterward to check whether I’m rambling.The tool gets you efficiency, but the voice is still yours to bring.If anyone can generate the content, the only scarce thing left is the reason it’s worth trusting. What’s yours?About Michael SchreiberMichael Schreiber is the CEO of MediaFeed, a content syndication company that helps brands, nonprofits, and journalists develop and distribute real editorial work. A longtime journalist whose path ran through newspapers, documentaries, and financial outlets including TheStreet and Credit.com, he also hosts a local podcast covering his New Jersey town. Find his work at mediafeed.co, on Instagram, and on LinkedIn.About meJoel Salinas is an Executive AI Coach for leaders at small and mid-sized businesses and nonprofits. 1:1 coaching, team workshops, and AI strategy work built around amplifying what your team is already good at. Creator of the AI Leadership Triad. He writes Leadership in Change. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

Christopher Chin started out as a coder, one of the jobs you’d think needs the least human communication, and somehow ended up on a TEDx stage teaching people how to speak. This conversation is about how he made that jump, and what he thinks communication actually is once you stop treating it as moving information from one head to another. The frame that I’m still going over is that communication is music. It has melody, rhythm, and silence, and once you hear it that way you start sounding like a person instead of a content machine. We also got into why authenticity is the thing that survives the age of AI slop, and the dead-simple framework he uses to never ramble again. Watch the full conversation above.Outline(00:00) – Meet Christopher Chin(02:13) – The composer who became a coder(04:25) – Head down vs. speak up(06:17) – Communication is music(08:22) – Mindset over technique(13:02) – Why silence does the work(17:37) – Standing out in the age of AI slop(20:06) – Where AI actually belongs(28:33) – Bring out your hidden speaker(32:16) – Three steps for when you freezeA Few Things That Stuck With MeCommunication is music. The line I keep coming back to is when Chris stopped describing communication as information and started describing it as something you compose. He grew up wanting to write music for films, and when he finally pulled that side of himself back into how he talks, his whole delivery changed.“Music has melody and rhythm and tonality, and the voice does the same thing. By not viewing communication as just information, but as an experience you create, that’s how you engage.”I felt that one personally. I grew up speaking Spanish, my mom’s from Argentina, and there’s so much emotion baked right into the words, and I’d never really clocked that the lilt and the pacing were doing half the work.Mindset over technique. Here’s the thing most communication advice gets wrong. Chris said you can Google “three steps to executive presence” all day, and if you just copy the hand gestures and the posture, none of it lands.“The real way to achieve authentic, effortless communication is to work on your mindset and your understanding of why these things work. If I teach you the core of executive presence is coming in with a calm, steady, grounded presence, knowing that no matter what’s thrown your way you can handle it, that changes how you communicate.”It reframes the whole thing, because you stop trying to perform confidence and start building the kind of steadiness that makes the performance unnecessary.The fast-food test for AI. We got into AI slop, the wave of generic content flooding every feed, and Chris had the cleanest way of explaining why it bounces right off you. He compared it to McDonald’s fries: the same everywhere, engineered to be fine, forgotten the second you finish.“It could be saying the most brilliant things in the world, but I want to hear that from an actual person. If I sense there’s no human behind that screen, I don’t want to hear it. I want lived experience.”Honestly, this is the whole reason I run these as live conversations instead of just publishing a guest article. You’d never get Chris, the actual person, from a block of text.Nerves are the flip side of excitement. For anyone who freezes the second they have to speak, this was the reframe of the episode. Chris pointed out that the butterflies before a talk and the butterflies before a trip you’ve been dying to take are the same physical thing.“The physical sensation you experience when you’re nervous, the butterflies in the stomach, is the same exact sensation when you’re excited. The thing that differentiates them is your perception.”So you don’t actually have to calm down, you just have to decide the feeling means you’re about to do something that matters.(Quick aside: a lot of my 1:1 coaching work is exactly this, helping leaders close the gap between how good their thinking is and how clearly it lands in the room. If that’s you, here’s where to start.)One Question to Sit WithWhere are you underselling yourself at work, not because your thinking isn’t strong, but because you’ve never put in the reps on saying it out loud where it counts?Watch the full conversation above, and then go subscribe to The Hidden Speaker.About Christopher ChenChristopher Chen is a TEDx and international keynote speaker who coaches leaders and teams on communication, and he writes The Hidden Speaker on Substack. He started out shy, introverted, and behind a screen as a coder before building his practice around helping people speak with confidence. He’s posted around 180 videos on his YouTube channel and releases weekly previews from his upcoming book on communicating in the age of AI. Subscribe to The Hidden Speaker.About meJoel Salinas is an Executive AI Coach for leaders at small and mid-sized businesses and nonprofits. 1:1 coaching, team workshops, and AI strategy work built around amplifying what your team is already good at. Creator of the AI Leadership Triad. He writes Leadership in Change. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

Here’s where this conversation started. I keep hearing the same thing from the leaders I coach, and what they’re asking about on the surface is strategy or tools or timing, but the thing underneath it, almost every time, is fear. Here’s where this conversation started. I keep hearing the same thing from the leaders I coach, and what they’re asking about on the surface is strategy or tools or timing, but the thing underneath it, almost every time, is fear. Fear of not adapting to what’s coming, fear of getting left behind, fear of letting their team down when they’re not sure how to prepare them. I brought Janice Burt on because she’s spent the last fourteen years walking straight into fear on purpose, one a year. She’s a two-time TEDx speaker, author of Kicking the People-Pleasing Habit, and host of the One Fear Per Year podcast. What I didn’t expect was how cleanly her work maps onto what AI leaders are actually wrestling with right now.Outline(00:00) – Why this conversation is different(01:55) – Janice’s origin and the prison of fear(03:00) – Year one was a marathon(07:00) – What 14 years inside fear taught her(08:30) – Fear of not being good enough(12:30) – Writing Kicking the People-Pleasing Habit(14:50) – The through-line for AI leaders(19:25) – Caring vs. people-pleasing(21:30) – Awareness, choice, community(32:00) – Dropping to her knees on stage(34:00) – One fear per year, your turnA Few Things That Stuck With MeThe through-line nobody names. About fifteen minutes into the conversation, I realized the leaders I coach almost never use the word “afraid.” They talk about strategy, vendor selection, team readiness, timing. But the avoidance pattern is the same one Janice has been studying for fourteen years. Here’s how she said it:“I would say an underlying thing is just the fear of not being good enough. And then there’s the fear of change. Or the fear of the unknown. None of us know what’s going to happen.”That’s why a CEO keeps deferring the AI conversation with their team, and why a director quietly pushes the rollout one more quarter. The tool is the easy thing to talk about. The harder thing is sitting in the room and saying out loud that the team isn’t ready, or that the leader isn’t sure they’re ready either.Fear lives in the future. Janice made a point that stopped me in the middle of the live. Fear is always anticipatory, which means you can only fight it from a place you’re not actually standing in. Her words:“Fear is always this anticipated thing in the future. What’s going to happen? Worst case scenario. To lay in bed last night worrying about this conversation, that’s the fear. Coming back to the present moment is taking your power back.”Read it again with AI in mind. Most of the AI anxiety I see in coaching is about an imagined version of next year, which is also why it’s almost impossible to act on. You can’t fix a future you haven’t reached yet.Year one was a marathon. I want to come back to this part. Janice went straight at the one thing she was certain she couldn’t do, ran 26.2 miles, and learned the lesson that turned the whole project into a fourteen-year practice:“Accountability is where it’s at. Community is where it’s at. We can do so many things and go so many places with the right people around us.”That’s a leadership lesson dressed up as a running story. You don’t walk through fear alone, and you don’t push your team through AI adoption alone either.The on-stage moment. A couple of years ago, in front of a room of CEOs and professional speakers, Janice had a physical fear reaction mid-talk and dropped to her knees on stage to keep from running off. Afterward, she described it as a spiritual experience, a moment of surrender where the facade dropped and the audience saw the actual Janice for the first time. Her line right after has been in my head since the live ended:“There’s nothing worse than being held back by your fear. Not even this.”I told her on the live it was the strongest line of the conversation. I still think so.(If you’re a leader sitting with one of these fears right now and the AI piece is the surface story, this is exactly the conversation I have in 1:1 executive coaching. Sometimes the strategy work starts with naming what you’ve been avoiding.)One Question to Sit WithWhat’s the one fear you’d walk through this year, on purpose, if you knew you had three hundred and sixty-five days to figure it out?Watch the full conversation above. Then go subscribe to Janice at janiceburt.com and grab her book Kicking the People-Pleasing Habit.If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

TL;DR — I just spent 49 minutes on Substack Live with David Allen, the guy who has shaped how I think about my own work for the last 25 years. Getting Things Done turns 25 in 2026, and the question I had walking in was simple: does the framework still hold up in a world full of AI agents? David’s answer was sharper than I expected. AI didn’t really change the underlying principle, it just raised the cost of ignoring it so fast that you can feel it now in a way you couldn’t ten years ago.Outline(00:00) – Welcome David Allen and the one-paragraph version of GTD(02:00) – Mind like water and the strategic case for a clear head(05:00) – The accidental career and how the five steps came together(09:00) – Why AI didn’t change the principles, just the volume(12:20) – Channel creep and the new pressure on knowledge workers(15:00) – Decision support, not decision making(19:00) – The Tesla farmer-strike story and AI already inside your life(22:00) – Critical thinking as a muscle AI quietly atrophies(26:00) – Pen and paper still wins, because your phone is a black hole(33:00) – Addiction to ambient anxiety and why GTD doesn’t stick(38:00) – Journaling as creative capture(40:00) – One integrated system, no home/work split(44:00) – Moral Ambition by Rutger BregmanA Few Things That Stuck With MeDecision support, not decision making. Honestly, this is the cleanest mental model I’ve heard yet for what AI actually is in a leader’s workflow. David put it this way: “I use ChatGPT three or four times a day. Where’s the local place to buy the best old cheese here in Amsterdam? It’ll give me a lot of good data.” That’s decision support. Then he turned the screw: “Trusting it to be able to make the decision about what to buy for mom’s birthday might be the inappropriate thing to do.” That line between the two is where most leaders quietly get into trouble, because they start treating decision support like decision making and forget that they still have to be the one who chooses. (If your AI never disagrees with you, you’re using it wrong.)Channel creep. Look, this is the one I’m still chewing on, and David coined the term live. The volume of work hasn’t really changed that much in the last 25 years, but the channels have multiplied so fast that most leaders are now checking five or six different places just to make sure they’re not missing something that matters. Slack. Outlook. Asana. Google Meets. Two phone notification streams. He asked me on camera how many things I actually have to check to feel like I’m seeing the right stuff, and I rattled them off without thinking. That’s the diagnosis. (Start 2026 with an AI tool detox.)Your phone is a black hole. Here’s the thing. David has been doing this for 40 years and he still uses pen and paper for capture, and his reasoning lands the second you hear it: “For most people, their phones are black holes. They throw stuff in there and they don’t process it. They don’t deal with it.” I caught myself agreeing with him out loud. My own setup is a double-tap on the back of my phone that fires dictation into my email, because the second I open the screen for any other reason, I’m gone, and so is the thought I was trying to keep. The phone is genuinely the worst place to put the thing you most need to think about later. (The complete Second Brain blueprint.)Addiction to ambient anxiety. Honestly, this was the answer to a question I didn’t know I was carrying into the conversation, which was why so many leaders read Getting Things Done, get clear for a weekend, and then quietly fall off. David’s line: “Be aware of your addiction to ambient anxiety. Your comfort zone is a lot more comfortable than being out of your comfort zone, which is having absolutely nothing on your mind.” Read that twice. What looks like a discipline problem from the outside is almost always your nervous system getting bored of feeling calm and going hunting for something to worry about, which is a much harder thing to coach somebody through than a missing checklist. (Don’t outsource your thinking, even to AI.)If you’re a leader running on adrenaline and you can feel it showing up in your decisions, that’s the work I do one-on-one. Start the conversation here.When you check your phone right now, is it because something actually needs you, or because you’ve gotten too comfortable being needed?Watch the full conversation above. If anything from David landed for you, go subscribe to David Allen on Substack and read Getting Things Done. 49 minutes with David is the cheapest leadership coaching you’ll find this year, and the book is the next one on top of it.Written by a human, for humans.Thank you Lynn Jericho, Claire Machado, Stephen V. Smith, Duncan The Sage, Erika Legara, and many others for tuning into my live video with David Allen! Join me for my next live video in the app. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

TL;DR — Dan Ariely is one of the most cited behavioral economists alive, the author behind Predictably Irrational and Misbelief, and we spent thirty minutes on Substack Live walking through what AI is actually doing to the way leaders make decisions. The headline isn’t that AI is dumb, it’s that AI is engineered to give us what we want, and what we want is almost never what we need long-term, which means the smarter the model gets, the more dangerous that mismatch becomes. Outline(00:00) – Welcome and Dan’s AI journey(02:00) – Where AI shines vs. where it falls flat(04:14) – Three studies that should worry every leader(09:30) – What AI does to risk-taking(12:11) – The romantic-love risk that surprised the data(15:33) – The friend who lost six weeks to ChatGPT(18:00) – The two-spouses thought experiment(20:50) – Why I write 15 drafts on purpose(24:14) – Why algorithms get less forgiveness than humans(28:00) – The trust problem inside companies(30:46) – Dan’s diagnostic question for leadersA Few Things That Stuck With MeThe comfort trap. Honestly, this was the part that landed hardest. Dan walked through three studies. One: AI was more concerned with our feelings than with the ethics. Two: the MIT paper showing people who lean on AI don’t just stagnate, they actively deteriorate. Three: AI was more convincing than another human on conspiracy theories, because, as Dan put it, “we don’t have the same confrontational model. You say, this is a tool. It’s for me. It’s always on my side.” That’s the trap. We trained it to comfort us, then forgot to ask whether comfort is what we need.Six weeks lost to compliments. A friend of Dan, a brilliant computer scientist, spent six weeks designing a chip with ChatGPT. The AI complimented him the whole way. At week six, on a hunch, he ran the output through Claude. Claude told him plainly the whole thing was nonsense. ChatGPT eventually admitted it had been hallucinating the entire time. Six weeks. AI has obviously figured out we love compliments, which means you’re now asking a tool trained to keep you happy whether your strategy is working or not. I keep coming back to that as a leadership problem more than a tool problem.Build your own contract with AI. Honestly, this was Dan’s answer to the part I worry about most: AI quietly takes over the thinking that used to make leaders sharper. He cited a study on couples and finances, where the partner who handles the money keeps getting better, and the other gets worse, not because they got dumber, but because they stopped using that muscle for fifteen years. Same thing happens to leaders. Dan’s answer wasn’t to ban AI, which would be the obvious overcorrection. It was to write himself a contract for each part of his process: where he’ll use it, where he won’t, where he’ll force himself to do the messy version first. One Question to Sit WithWhen you ask AI for advice, does it leave you sharper than you were a year ago, or quietly less sharp than you realize?Look, if you’re a leader making real decisions with AI in the room, watch the full conversation above. And if Dan’s research lands for you the way it landed for me, do three things. Subscribe to Dan Ariely Looks at Life, where he’s thinking out loud about the human side of all of this. Read Predictably Irrational — the foundational book on why smart people make systematically bad decisions and the one I keep recommending to leaders trying to sharpen their judgment. Then read Misbelief, his most recent, which examines how reasonable people fall into irrational beliefs. Dan is one of the most cited behavioral economists alive, and giving him forty minutes of your attention is the cheapest version of a graduate-level behavioral economics class you’re going to find.About Dan ArielyDan Ariely is a professor of psychology and behavioral economics at Duke University and one of the most cited behavioral economists alive. He’s the author of Predictably Irrational, The (Honest) Truth About Dishonesty, and most recently Misbelief, his examination of how reasonable people fall into irrational beliefs. He writes Dan Ariely Looks at Life on Substack, where he applies behavioral science to the everyday decisions most of us make on autopilot. Subscribe at danariely.substack.com.About meJoel Salinas is an AI Strategy Coach for small and mid-sized businesses and nonprofits. Strategy, hands-on builds, and change management. He writes Leadership in Change and offers 1:1 coaching for individual leaders. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

TL;DR — Compound With AI is a Substack newsletter teaching 50,000 long-term investors how to compress six hours of stock research into about sixty minutes using AI prompts, Claude skills, and deep research workflows. We sat down on Substack Live this week and unpacked the actual mechanics, the prompt library, the multi-agent setup, the break-my-thesis move, the way he turns deep-research reports into NotebookLM podcasts to listen to while he’s training. Outline(00:00) – Welcome and how I found Compound With AI(02:30) – The deep research “cheat code”: six hours becomes sixty minutes(06:30) – Index funds for 99% of people, individual stocks for the rest(08:50) – Why retail investors now have the same tools as the best hedge funds(12:30) – The multi-agent setup: industry, earnings, risk, stock analyst(14:00) – The coffee shop walkthrough: thinking like an owner, not a buyer(17:30) – Reading ten years of management track record in minutes(22:00) – The professional learner edge(24:50) – Pen and paper before the prompt: why one prompt takes an hour(29:30) – Walking through Exxon from zero(32:30) – Turning deep research into a training-podcast with NotebookLM(34:00) – The “break my thesis” agent(43:30) – Where AI in investing is heading nextA Few Things That Stuck With MeThe deep research cheat code. So Compound With AI said something I want every leader to hear, because it lines up with what I’ve been seeing across coaching engagements all year. He said deep research changed everything for him about a year ago. Before that, getting to a real understanding of a new business took five or six hours of reading reports, and getting to a new industry from zero could take weeks. Now he runs the right prompt against deep research in Gemini or Claude or ChatGPT, walks away, and comes back to a structured ten-page report he can actually act on. “When this started working for me, I said, okay, this is a game changer. I used to do this and it would take five, six hours. And if you don’t know the industry, it would take weeks because you’re starting from zero.” The leaders I keep watching get unstuck are the ones who finally let AI do the part of the work that was burning their hours, the part that was always research disguised as judgment.The coffee shop walkthrough. This was the cleanest explanation of what real stock analysis is that I’ve heard live. He said, look, if you and I were going to open a coffee shop together, the first thing we’d do is walk down the street and count how many other coffee shops are already there. Then we’d think about what makes people walk into one shop instead of another, branding, margins, location, the way the staff smiles. He treats every stock the same way, and his prompts force AI to do the exact same exercise. “When people buy Starbucks the stock, they say, ‘Starbucks is a big brand, let’s buy it.’ They don’t do all the work because it’s kind of virtual money. And that’s the big issue for me.” This is the single most useful frame in the conversation. If you can explain out loud how a business actually makes money, you can prompt AI to dig into it, and if you can’t, no prompt in the world is going to rescue you, which is why I keep telling the leaders I coach that AI literacy starts with business literacy.Pen and paper before the prompt. Here’s the moment I most wanted to slow the conversation down on. He builds his prompts on paper first, by hand. He sits with a question, writes ten or fifteen sub-questions a smart human analyst would actually ask, and only then translates that to a typed prompt. One prompt takes him about an hour. Then he tests it on five or six stocks he already knows cold, so he can spot what the AI is missing. “To build one prompt I take one hour. I write pen and paper. Not everybody is willing to do the work.” Honestly, that admission was worth the whole hour for me. The hype industry sells AI as effortless, and the people I see getting real results are doing the slowest, boring part of the work, the part nobody puts in the demo videos: writing down the questions a smart human would ask before they ever touch the tool.The “break my thesis” agent. Here’s the move that landed hardest for me. Once Compound With AI has built a real reason to invest in a stock, instead of running another agent to confirm the thesis, he runs one specifically built to argue against him, hands it the bull case, points it at his own frameworks, and tells it to break the thesis. “Tell me what are the problems. And sometimes, honestly, AI will point to things you didn’t think about. And that’s very interesting.” I love this move because it flips the default way most leaders touch AI. Most people are quietly using AI to confirm what they already think, which is the fastest way to get a worse decision than if you’d just asked nobody at all. The investors who actually outperform are pointing AI at their own conclusions and asking it to break them, which is closer to how Buffett and Munger have always operated together, with Charlie’s whole job being to find the holes in Warren’s reasoning.(If you’re a leader thinking about where AI actually belongs in your own work and you’d like another set of eyes on it, this is the kind of thinking I do every week with the leaders I coach. You can start here if it would help to talk one through together.)One Question to Sit WithWhat’s one domain in your own work where you’ve been prompting AI generically, when you could be sitting down for an hour and building a prompt library you’d use for the next ten years?Honestly, the floor is rising for everyone with AI in their hands now, the ceiling moved up with it, and the only thing left to decide is whether you choose to be a professional learner.Look, if you invest your own money, watch the full conversation above. And honestly, go subscribe to Compound With AI. Fifty thousand long-term investors are already inside, and the prompt library and weekly workflows are some of the most rigorous AI-for-investing material I’ve found anywhere on Substack.About meJoel Salinas is a Fractional Chief AI Officer for small and mid-sized businesses and nonprofits. Strategy, hands-on builds, and change management. He writes Leadership in Change and offers 1:1 coaching for individual leaders. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

TL;DR — AI made content production almost free, which means producing it is no longer what separates the creators who grow from the ones who stall. Trust, voice, and the depth of your actual expertise are. Call it the trust premium. In a Substack Live with Philip Hofmacher, cofounder of Write × Build × Scale, we walked through the litmus test that tells you whether AI is amplifying you or quietly replacing you, and why the creators winning the next 12 months are the ones loading their context, not their prompts.Outline(00:00) – Welcome and how I found Write × Build × Scale(02:00) – Building a business and a marriage with your cofounder(03:35) – From tennis to Skillshare to Substack: the platform-pivot lesson(09:30) – The value of community and masterminds(13:34) – How AI changed content creation in two years(17:25) – The sameness problem and the trust premium(22:00) – Lazy AI vs. strategic AI(24:54) – The litmus test: are you more of an expert than a year ago?(28:54) – Philip’s ChatGPT workflow and my Claude workflow(32:18) – Personal brand: stories beat lists(39:42) – Advice for creators stuck at 200-500 subscribers(45:46) – Philip’s billboard: AI amplifies you, or replaces youA Few Things That Stuck With MeThe trust premium. So Philip Hofmacher said something on the live that just landed for me. “It got so easy to create products compared to how hard it is to sell something.” Ten years ago, when he was selling Skillshare courses on Instagram growth, the work was eighty percent making the course and twenty percent selling it. Now he says it’s the inverse. Building the product is the cheap part. Earning the trust to get somebody to actually consume it, that’s the expensive part. Honestly, the whole conversation lives in that one sentence. Call it the trust premium. When AI made production almost free, trust became the thing people are actually paying for.The research-assistant analogy. I used this on the live because it’s the analogy I keep coming back to with the leaders I coach. Look, if you hire a research assistant and you tell them, “find me information on Write × Build × Scale,” they’re going to go out and pull whatever’s public. They don’t know your angle. They don’t know what you’re actually trying to do, who your readers are, or what your point of view is on the topic. So they bring back the most generic version of what’s out there. That’s not on the research assistant though, that’s on you, because you sent them out empty-handed. AI is the exact same thing. The creators who use AI well aren’t smarter than everybody else. They figured out one boring thing earlier than most people, which is that AI on its own gives you the same average answer it gives everybody, and unless you take the time to load up the context first, the version you publish is going to look exactly like the version everybody else publishes.The litmus test. Here’s the question I tell every leader I coach to ask themselves, and I asked it on the live. Look at yourself a year ago. Are you more of an expert at what you do than you were twelve months ago? If yes, you’re using AI right. It’s compounding you, freeing the time you used to spend on grunt work and routing it back into the work that actually grows your craft, and you can feel it because you’re sharper than you were. If no, AI isn’t actually amplifying you, even if it feels like it is. What’s happening is slower and quieter than that. It’s doing the thinking that used to make you better, and the longer that goes on, the more your expertise quietly hollows out, until one day somebody notices you don’t actually know more than the model does. Philip closed the loop on the live, after I floated the idea. He said, “Basically using AI to become a better version of yourself, a better operator, a better business owner.” Same thing.Stories beat lists. Here’s the part of the conversation I keep coming back to. Philip mentioned his cofounder Jari’s dog, who apparently shows up in their community so often that when they announced an in-person event, the first question people asked was whether the dog would be there. He talked about his wife Sinem, who’s also his cofounder. I mentioned my seven-year-old, who’s been campaigning for a dog all month. None of that was strategy talk or monetization advice, just two real people talking shop on a Monday morning, occasionally laughing about their kids and their dogs. That’s the part AI can’t reproduce yet, and honestly probably never will. That’s the moat.I work with leaders on exactly this, executives, marketing VPs, nonprofit CEOs trying to figure out how to show up in the AI era without sounding like every other person on Substack. If it would help to talk this through, here’s my calendar.Let us know in the comments…Are you better at your craft than you were a year ago? If the answer’s no, what’s AI actually doing for you?Look, if you write or build anything online, watch the full conversation above. And honestly, go subscribe to Write × Build × Scale. Philip Hofmacher, Sinem Günel, and Jari Roomer are running the most useful creator-economy publication I’ve found, and most of what I’ve actually figured out about Substack in the last six months traces back to their work.Joel Salinas is a Fractional Chief AI Officer for small and mid-sized businesses and nonprofits. Strategy, hands-on builds, and change management. He writes Leadership in Change and offers 1:1 coaching for individual leaders. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

TL;DR - LinkedIn locked Melanie Goodman out of the platform she had built a business on for ten years. She got back in, but the 12-week gap taught her something most leaders still refuse to learn: every social platform is rented land. In the AI era, where feeds are flooded with auto-generated content, the leaders who win are the ones who own their audience, sound unmistakably human, and run LinkedIn and Substack together as one system instead of betting on either alone.Outline(00:00) – Introduction and Mel’s background(02:48) – The LinkedIn ban story(08:49) – The LinkedIn + Substack flywheel(10:48) – AI and the death of the generic post(13:36) – Start your posts with “I”(14:45) – The LinkedIn Services page(18:58) – Lazy AI vs. strategic AI(21:05) – The research stack(27:25) – The headline problem(31:33) – Using AI without losing your voice(37:01) – The 6-to-12-month forecast(39:07) – Where to startA Few Things That Stuck With MeThe “rented land” frame. LinkedIn can ban you with no warning and no explanation. Mel went through it for 12 weeks after a decade on the platform. If your entire professional presence lives on someone else’s servers, one notification can wipe it out. Mel’s line on this is the one I keep repeating: “On LinkedIn, you’re on rented land.”The 360 Brew test. LinkedIn’s current algorithm samples every post against a small audience before pushing it wider. The single biggest signal it looks for in that first round: does this sound like a real person writing about real experience? Mel’s tactical fix is so specific it borders on mechanical. Start your first two lines with the word “I.” Not “Here are 5 tips.” Not “As a leader...” Just “I.” Then move to the informative content. The word changes your reach.The Services page nobody sets up. Five minutes. One-time. Mel’s words: “If you don’t do anything else, please do that, because you will immediately rank above everybody else.” Almost no senior leader I know has done this. The broader case for search discoverability is in How to Be Seen in the AI Search Era.Lazy AI versus strategic AI. I used this frame on the live and it landed the way it tends to. Lazy AI replaces your thinking. Strategic AI amplifies it. In a feed flooded with auto-generated content, the premium on lived experience goes up, not down. Mel put it this way: “It’s these lived experiences that will propel your content above the next thought leaders or make somebody hire you and not the next person.” I wrote the full case for the strategic side in Stop Delegating Your Brain to AI.(I work with leaders on exactly this, health CEOs, marketing VPs, founders rebuilding how they show up online in the AI era. If it would help to talk it through, my calendar is here.)One Question to Sit WithIf your LinkedIn account disappeared tomorrow, what would you still have?If the answer is “not much,” watch the full conversation above. Mel’s 12-week gap is everyone else’s warning, and the three fixes she walks through take minutes, not months.About Mel GoodmanMel Goodman is the founder of The Link Tank and one of the most sought-after LinkedIn consultants working with senior leaders today. A former real estate lawyer, she has spent more than a decade helping executives turn LinkedIn connections into clients and now teaches the LinkedIn + Substack flywheel to her Substack audience. Subscribe to her work at melaniegoodmanlinkedinconsultant.substack.com.About meJoel Salinas is a Fractional Chief AI Officer for small and mid-sized businesses and nonprofits. Strategy, hands-on builds, and change management. He writes Leadership in Change and also offers 1:1 coaching for individual leaders. If you want help thinking through your own AI strategy or online presence, start here.Written by a human, for humans. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

What happens when a 136-year-old Swiss watch brand meets the age of AI?I sat down with Jacque O., executive at Doxa USA & Caribbean, to talk about one of the hardest questions leaders face right now: how do you stay true to your craft when everyone around you is automating everything?Jacqueline brought 16 years of luxury retail experience and some of the sharpest thinking I’ve heard on balancing heritage with innovation. Here are the highlights:Key Moments* 1:21 — Jacqueline’s background: 16 years in luxury retail, PADI-certified diver, built an aquaculture business* 3:57 — Doxa’s origin: founded in 1889 by George Ducamon, who started watchmaking at age 12* 5:16 — How watch movements work and why Doxa keeps prices at 1/4 to 1/5 of competitors with the same quality movements* 7:05 — Why Doxa dug in on heritage: no AI in the watches, staying about watchmaking* 8:48 — The leadership tension: how do you meet a new generation’s demand for efficiency without losing what makes you valuable?* 11:02 — The stat: maybe 5% of Doxa watches actually make it to the ocean for scuba diving. Most buyers choose it for the craft, not the function* 11:56 — What Doxa clients actually love about AI: making their own content, building community, not automating the product* 13:05 — “There’s no replacement for what is real and tangible and human”* 14:55 — “It loses its magic” — what happens when you automate the thing people love about you* 15:53 — The Navy SEAL story: how Jacqueline used ChatGPT as a collaborator (not a replacement) to craft deeper interview questions* 18:28 — The grocery store self-checkout example: voting with your money* 22:08 — AI isn’t the Bible: the dangers of trusting AI output without critical thinking* 23:20 — How to use AI smart so it complements you instead of replacing you* 24:22 — The prediction: we’ll soon see a “100% human-made” seal on content and products, and people will pay a premium for it* 32:04 — The “Missed Sales List”: the report that changed an entire company’s strategy by tracking what didn’t sell* 33:49 — Why your KPIs might be lying to you: measuring what sold vs. what you missed* 34:34 — Retail psychology debunked: how Jacqueline proved the conventional wisdom wrong by testing rack placement* 37:50 — “I’m not a salesperson. I’m a human first.” Why 4-hour conversations outsell pressure tactics* 39:26 — Telling a customer to buy the competitor’s watch instead, and why that builds loyalty* 41:58 — The core takeaway: focus on the people you want to serve, not their wallets. The sales will come.* 45:15 — Book recommendations: Mind Hacking by Sir John Hargrave + The Body Ecology DietThe Big Takeaways* Know what to protect. Your craft is your craft. Automate the things around it, not the thing itself.* AI is a collaborator, not a replacement. Use it to push your thinking deeper, then rewrite in your own voice.* AI isn’t always right. It’s a prediction engine built largely on Reddit. Verify everything.* Measure what you’re missing, not just what you’re hitting. The biggest opportunities hide in what you never tracked.* We’re still people dealing with people. That hasn’t changed and won’t. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

Thank you Karo (Product with Attitude), Tina Williams, Jón Sveinsson, and many others for tuning into my live video with Paul the Human! Join me for my next live video in the app. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

This is a free preview of a paid episode. To hear more, visit leadershipinchange.comA live walkthrough of the full Claude Projects workflow — from NotebookLM research to branded thumbnails. See how I build every newsletter in 12 steps. For content creators and leaders using AI.

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

What a fun chat with Exploring ChatGPT! We touched on…* Leor’s journey into Substack and leading a publication with tens of thousands of subscribers* AI in 2026 and our outlook as AI Explorers* Our AI tech stack* What we worry about and what we get excited about with AI use in 2026* AI and the importance of communityImportant links:Our AI Community - CozoraMy one indispensable tool - Wispr FlorThank you Kevin E Beasley, Juan Salas-Romer, Rodney Daut, Jag Alexeyev, Paul k, and many others for tuning into my live video with Exploring ChatGPT! Join me for my next live video in the app. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe

The most common question I get from leaders: “Joel, how do I actually keep up with AI?”It’s a fair question. AI is moving fast, information is everywhere, and even those of us working on this full-time struggle to stay current. You can spend hours every week trying different tools, watching tutorials, reading articles—and still feel like you’re getting nowhere.That’s exactly why my cofounders Michael Simmons and Claudia Faith and I built Cozora.Subscribe for free and get 30% off Cozora - Holiday offerWhat Cozora Actually IsCozora is a live AI show-and-tell community. Instead of reading about how someone uses AI, you watch them do it, live, on their screen, with the actual prompts they use.Every session runs 60-90 minutes. You can ask questions, pause the creator, and walk away with prompts you can use Monday morning. No theory. No generic tips. Just real workflows from people who’ve spent thousands of hours perfecting specific AI skills.Why We’re Doing This DifferentlyMost AI education treats every tool the same way. You try ChatGPT for five minutes, Claude for ten, then move to the next shiny thing. It’s like going to a gym and doing one rep on every machine… you never actually build strength anywhere.Cozora focuses on depth over breadth. We’re building specialized cohorts around specific use cases: AI for marketing, AI for content creation, AI for strategy, AI for sales. You pick your area, go deep with experts in that niche, and actually master the skills that matter for your work.The AI landscape is moving toward specialization. Skills like prompt engineering and context engineering are getting more complex. You need focused learning, not endless surface-level exposure.The Collaboration AdvantageHere’s what surprised us most: AI rewards collaboration more than any technology we’ve seen before.Someone great at writing can partner with someone great at image generation. A subject matter expert can team up with a prompt engineer. Right now, while AI is still new, industry experts are unusually open to collaboration. That window won’t last forever.Your Discount OfferBecause you’re part of this community, you get early access with significant savings:Free Subscribers: 30% off Cozora for 12 months (Offer ends Jan 15)Premium Members: 50% off Cozora (save $360 annually) Subscribe for free and get 30% off Cozora - Holiday offerWatch the video above to hear directly from the three of us about why we built this and what makes it different. Then, if it resonates, grab your discount before the deadline.Thank you Exploring ChatGPT, Corie Feiner, The Black Line, Hodman Murad, ila Dawn, and many others for tuning into my live video with Michael Simmons and Claudia Faith!Ready to go deeper? Sign up at Cozora.org and use your Leadership in Change discount at checkout.Have questions about Cozora or how it fits your specific leadership context? Drop them in the comments—I’ll answer every one. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit leadershipinchange.com/subscribe