AI Ready Podcast with Harrison Painter

Your customers used to find you on Google. Now they ask ChatGPT, Claude, or Perplexity who to buy from, and the answer decides whether you exist. Harrison Painter sits down with Krisztián Király, who runs international partnerships at OptiMonk, a Hungarian conversion optimization platform used by more than 30,000 websites across 150+ countries.Recorded days after the EU AI Act's transparency rules took effect, the conversation covers what those rules could mean for AI-generated product photos, the pushback against AI imagery in advertising, ads arriving inside ChatGPT, and how product copy now gets written for the AI that answers your customer, not just the customer alone.The surprising stretch comes when Király names the situations where AI is not needed at all, including his own company's rule that its AI features are not worth switching on until a store sees about 15,000 visitors a month. A software vendor naming the floor where his product stops working is rare, and it makes the advice on either side of it easier to trust.Whether you run a store, advise companies that do, or just want to understand how buying decisions moved inside the AI assistant, this one gives you the operator's view from someone watching 30,000 storefronts adjust in real time.----OptiMonk: https://www.optimonk.comKrisztián Király on LinkedIn: https://www.linkedin.com/in/christian-kiraly

Getting good at AI does not take a degree, a tech background, or a year you do not have.Kathleen deLaski has spent a decade proving it. She founded the Education Design Lab, she advises the Harvard Project on the Workforce, she teaches AI at George Mason, and she wrote the book *Who Needs College Anymore?*She joined me on the AI Ready Podcast, and her message to anyone who feels behind was simple: if you know how to use the internet, you can figure this out.A few things she said worth holding onto:AI lets you isolate the exact skill a job needs, then hands you the shortest path to learn it.For the solo entrepreneur, AI is becoming the great equalizer. In her words, it gives them a staff, in effect.And to the professional over 50 who thinks the wave already passed: you do not need a degree, you need a push.If you have been waiting for permission or a prerequisite to start, this episode removes both.

A new AI model out of Japan, Sakana Fugu, does something we have not really seen before. Instead of answering you itself, it hires a team of the best AI models, gives each one a piece of the job, and merges their work into one answer. Harrison calls it a manager, or a conductor: you ask one question, and behind the scenes it quietly builds a team for you.In this episode, Harrison explains what model orchestration actually is in plain language, why he thinks this is where AI is heading, and then puts it to the test. He sends the same 8 questions to Fugu, to Claude Opus 4.8, and to GPT-5.5, and grades every answer. The result is honest, and the cost is the part that should give every builder pause.What you'll learn:- What "orchestration" means, explained simply- Why the future may be teams of models, not one genius model- What happened when a team of models went head to head with single models- The real speed and cost tradeoff, with actual numbers- The hidden tokens you pay for but never see- When an orchestrator is worth it, and when one good model is plenty- A heads-up on AI pricing and subsidies most people are not thinking aboutCHAPTERS0:00 A glimpse into the future0:19 What is Sakana Fugu?1:55 Not a smarter model, a manager3:30 The test: 8 questions, three models4:50 Speed: about 10x slower5:30 Cost: about 49x more expensive6:07 The hidden tokens you pay for7:20 Inside the console8:30 The questions, and why they're tricky9:06 Is a team of models worth it?9:27 When a team earns its place10:09 The verdict10:57 The subsidy nobody is talking about11:18 Where this goes next12:04 Wrap upMentioned: Sakana Fugu — https://sakana.ai/fugu/If you got something out of this, follow the show and send it to someone who's working to keep up with AI.

Chris Hutchins spent more than 25 years inside some of the largest health systems in the country, including running enterprise analytics at Northwell Health, where he rebuilt the entire data warehouse. Today he advises boards, investors, and CEOs on how to deploy AI that holds up when a regulator, auditor, or attorney asks them to defend it.In this episode, Chris and Harrison Painter get into the unglamorous work most companies skip: the data underneath the AI. Chris explains why healthcare's data problem is a byproduct of growth by acquisition, why the "if you build it, they will come" approach keeps producing tools nobody asked for, and the single test he now applies to any AI project: does it give time back to the patient and the provider?Then they take on the word everyone uses and few can define. What makes an AI decision defensible? Chris's answer is simple and hard. If a decision gets made by a system and someone calls you, can you say what the decision was, who made it, and how, easily and quickly? Most leaders today cannot.You will also hear why "human in the loop" should be "human IS the loop," what the trolley problem reveals about AI and judgment, and the one question every CEO should ask their team about AI before a regulator does. Practical, honest, and grounded in real operating reps.

Anthropic just released Claude Opus 4.8, and the headline improvement is unusual: the model is built to flag its own uncertainty and say "I'm not sure." Anthropic says it's roughly four times less likely to let a flaw pass without catching it. When a company's flagship upgrade is honesty, that tells you something about where we are.Here is the other side of it. Harrison asked Google's Gemini one simple factual question for an article he was writing: did Jeff Dunham use AI to create the opening visuals for his 2024 comedy special? Gemini said yes, confidently, and cited a source. When Harrison pushed on that source, the tool did not check itself. It invented a new one. Then another. By the end it had manufactured four separate references, including a word-for-word on-screen quote that does not exist, before finally admitting the only real source was a single unsourced blog post.This episode walks the whole chain step by step. You will learn:- The exact failure mode: when an AI hits a popular but unverified claim, it gets confident instead of careful, and every round of pushback produces a fresh citation instead of a fresh doubt.- Why the Vectara Hallucination Leaderboard shows roughly one in ten outputs is wrong on a task as simple as summarizing a document.- A five-step, 30-minute verification process you can run on almost any claim before you repeat it.- Where source verification sits in The 7 Levels of AI Proficiency (it defines Level 3, the Critical Thinker) and why that is the level every working professional should be reaching for in 2026.- Three things to do this week to protect your own credibility.This is not an anti-AI episode. Harrison uses these tools every day. It is about the difference between trusting a tool blindly and trusting it after you have checked. That second posture is what separates an amateur from a professional whose name is on the line.Want to know where you stand? The 7 Levels of AI Proficiency assessment is free and takes 10 minutes: assess.launchready.aiHarrison PainterExecutive AI AdvisorLaunchReady.ai. Further. Faster.

A new paper from RAND-affiliated complexity researcher Kyle A. Kilian and Future of Life Institute risk analyst Richard Mallah, published May 20 through the Center for AI Risk Management and Alignment (CARMA), gives executives something that has been missing from enterprise AI governance until now: a six-test diagnostic for evaluating whether the AI committee you stood up actually governs, or whether it just looks like it does.The paper's load-bearing concept is performative adaptivity. Governance that meets monthly, ratifies charters, and updates risk registers without the structural properties to detect a new AI risk in time to respond. The authors argue this failure mode is more dangerous than no oversight at all, because it consumes the organizational energy that would otherwise build real protective capacity.In this episode, Harrison walks through:Who CARMA is and why the RAND + Future of Life Institute pedigree mattersThe four continuous governance functions every AI committee needs (Sensing, Evaluation, Response, Learning)All six diagnostic tests (Independence, Transparency, Durability, Accountability, Authority, Scope Adequacy)Where The 7 Levels of AI Proficiency comes in, because structurally sound governance fails when the operators are under-proficientThree things to do with this paper this weekFull article with citations: launchready.ai/insights/ai-governance/performative-ai-governance-six-tests-carma-2026Take the free 7 Levels of AI Proficiency assessment at assess.launchready.aiThank you for tuning in!Harrison PainterExecutive AI ConsultantSetting the Standard for AI Readiness

On May 25, 2026, the Vatican publicly presented Pope Leo XIV's first encyclical, Magnifica Humanitas. It is the first papal encyclical in history to address artificial intelligence directly. The Pope signed it on May 15, 2026, the 135th anniversary of Rerum Novarum, the document that founded modern Catholic Social Doctrine on labor and capital. The choice of date is the citation. This is a 135-year-old institution speaking to the question every CEO is now sitting with.You do not need to be Catholic to get value from this episode. You do not need to be a Christian. The encyclical was written for "all men and women of goodwill," which is the Vatican's long-standing way of saying anyone willing to think seriously about the question.In this 25-minute episode, Harrison walks the four ideas every CEO needs in their head this week:1. The Babel-or-Jerusalem move that reorganizes the entire public AI conversation2. Why technology is never neutral, and what that means for vendor selection and procurement3. The dignity-of-worker question that cuts directly at the language most companies use to justify an AI investment case4. The technocratic critique, the concentration question, and where this converges with secular AI governance research from RAND and the Future of Life InstituteThen three specific things to do with this letter this week before your next AI conversation on the calendar.Full article version with citations and direct quotes at launchready.ai/insights/faith. Take the free 7 Levels of AI Proficiency assessment at assess.launchready.ai.Harrison PainterExecutive AI ConsultantLaunchReady.ai. Further. Faster.

Eighty percent of manufacturing leaders say they are behind their peers on AI. The math says that is impossible. So why does almost every CEO walk into a room believing the rest of the industry has already figured this out?Bryce Carpenter, COO at Conexus Indiana, sits on top of the data that explains it. Conexus runs the Advanced Industries Council, the state's primary convening body for the 9,700 manufacturing and logistics companies that produce 37 percent of Indiana's GDP. Bryce founded the AIC in 2019 and has watched 120-plus member companies move through the AI experimentation phase in real time.In this conversation with Harrison Painter, Bryce walks through what he is actually seeing. Why Indiana's $29 billion in 2024 manufacturing investment paired with a 1 percent drop in employment is a retirement story, not an AI displacement story. Why the average tenure inside Indiana manufacturing collapsed from 30 years to 3. How a 52-person Northeast Indiana shop grew to 106 after a single equipment investment. Why the 9,700 companies running their own boutique soft-skill development programs is the most expensive inefficiency in the state. And why he gives Indiana an A-minus on AI progress when most operators inside the state would say B at best.If you run a 100-to-5,000-person company and you are trying to figure out where your team actually is on AI, start with the free 7 Levels of AI Proficiency assessment at assess.launchready.ai. It takes under ten minutes and tells you exactly which level your team operates at today.Thanks for supporting the AI Ready Podcast!Further. Faster. Harrison Painter

Jay Samit has held senior roles at Sony, Universal Studios, EMI, LinkedIn, and Deloitte Digital. He has raised hundreds of millions for startups and been called on by the Pope and the President. His book "Disrupt You!" has been published in 14 languages across 140 countries.His new book, "The Second Act Advantage," comes out May 5th. In this episode, Jay explains why entrepreneurs over 50 are three times more likely to succeed, how AI is eliminating entry-level jobs faster than anyone expected, and why purpose is the single biggest predictor of a long and healthy life.Jay also introduces Digital J, a free AI companion that ships with the book. The first book to come with its own AI mentor.This was a personal conversation. Jay mentioned me in "Disrupt You!" and wrote the foreword to my first book.The Second Act Advantage is available for pre-order now https://jaysamit.com/Take the free AI Proficiency Assessment: https://assess.launchready.aiLearn more: https://launchready.aiAI Ready Podcast with Harrison Painter. Further. Faster.

For the first time ever, AI skills are the hardest to find globally — beating engineering, IT, and everything else. ManpowerGroup's 2026 Talent Shortage Survey of 39,063 employers across 41 countries just made it official.In this episode, Harrison breaks down what the data actually says, what most coverage missed, and what leaders need to do right now.What we cover:Why 72% of employers worldwide can't fill rolesAI literacy vs. AI engineering — and why both are scarceWhat Germany (83%), France (74%), and the US (69%) tell us about the global gapThe stat almost no headline covered: human skills still top the list3 lessons leaders need to act on todaySources:ManpowerGroup 2026 Talent Shortage SurveyManpowerGroup Press Release, Feb 26 2026HR Dive, March 2 2026Subscribe and leave a review if this helped you think differently about AI and your organization.