Podcasts about powerpoints

In this candid and surprisingly funny host episode of Uncover the Human, Cristina and Alex tackle a big question hiding inside a very real 2026 reality: what is leadership actually for? As AI hype grows and organizations rush to replace people with bots, they challenge the assumption that strategy decks, frameworks, and PowerPoints are the real job of leaders. If AI can create the plan faster and better, what's left? The answer: the human work. Leadership isn't announcing decisions or reorganizing every 18 months—it's creating psychological safety, listening deeply, understanding the system you're operating in, and supporting people through change.They unpack why middle managers feel stuck in the “sandwich generation” of organizations, why so-called “listening tours” often aren't listening at all, and why true leaders are the ones people speak to, not the ones who speak the most. Drawing on Stafford Beer's idea that “the purpose of a system is what it does,” they explore how outcomes reveal the real system at play—no matter the stated strategy. If you've ever wondered why your big ideas don't stick, why friction keeps resurfacing, or what leadership really means in an AI-powered world, this episode is both a reality check and a hopeful reframe: leadership is influence, safety, and support—not title, noise, or control.

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss why most Q1 plans stall and how hidden fear holds teams back. You’ll learn simple ways to turn a big roadmap into tiny actions you can start. You’ll discover how generative AI can suggest low‑risk steps that keep momentum without a big budget. You’ll explore how to break the blame cycle and build real progress even in risk‑averse companies. Watch the episode to start moving your plan forward. Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-gap-between-planning-execution.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week's In-Ear-Insights—welcome from Snowmageddon. For folks listening later, it is the week of the big blizzard in the Northeast U.S., so we are all shoveling, but we're not talking about shoveling today. Well, we kind of are. We are talking about planning and execution. Mike Tyson famously said no plan survives getting punched in the mouth. And Katie, you recently asked in the Analytics for Marketer Slack group—join at Trust-Insights, AI analytics for marketers—how Q1 planning was going, and everyone said it isn't. You had thoughts about where that gap is between doing the plan and executing it. The character Leonard from *Legends-Tomorrow* has been quoted: “Make the plan, execute the plan, watch the play go off the rails, throw away the plan,” because that's how things go. So talk to me about why planning and reality don't match up so often. Katie Robbert: I started this question tongue‑in‑cheek: “How are all those fancy Q1 roadmap PowerPoints you spent weeks on in meetings doing?” I didn't expect the response—most are still sitting in SharePoint or largely untouched. The bottom line is that no one's really done anything. That's a trend across any industry, any vertical, any department, because making the plan is the easy part. Executing the plan feels risky, unsafe, unknown. I saw a post last week from our friend Paul Rotzer at Smarter-X, where he outlined eight stages companies go through when evaluating and adopting AI; most are stuck at one or two. My comment was that this is because of an unacknowledged fear from leadership—fear that by doing something they become irrelevant or that they'll get it wrong and be exposed. When we ask why we do all this planning and nothing happens, it comes down to unacknowledged fear. My hypothesis: I can get the best running shoes, put together a sophisticated training plan for a couch‑to‑5K, tighten my nutrition, get plenty of rest—yet that's just a plan. I still have to do it, to put one foot in front of the other. The scary part is, what if I fail? What if the plan doesn't work? What if I hurt myself, look silly, embarrass myself? Those thoughts creep up. In a larger, publicly traded organization with many eyes on every move, that fear is real. We can make plans, set goals, have expectations—but what if we act and it doesn't work? What if the wrong move is noticed? Christopher S. Penn: I like that analogy because there are externalities, too. We made the plan, got the running shoes, and now there are two feet of snow outside. “Okay, I guess I'm not going running”—a convenient excuse unless you own a treadmill. One of the things that seems true today is that planning requires some predictability to say, “Here's the plan.” Even with scenario plans—best case, worst case, middle—you still get wacky curveballs, like a sudden tariff wheel spin. As much as there are internal fears—afraid of failing, reluctant to stick your neck out—there are externalities: crazy events that render the plan obsolete. Let's flip this. You have the plan; maybe it's still valid, maybe it isn't. What does someone do to say, “Okay, I need to do at least one thing in the plan because I have ideas,” while hearing your perspective? Katie Robbert: Before we get into that, I want to acknowledge those externalities. In the running example, saying “the snow is a convenient excuse” takes accountability off you, so you're no longer at fault. Humans love to pass accountability to someone or something else—“It wasn't my fault; I couldn't run because it was snowing.” Then we ask, “Did you stretch? Did you do anything else?” The same pattern shows up in larger organizations: “The economy,” “the wind changed,” “someone said something weird,” “I'm superstitious.” Those become blanket excuses that shift blame. That's why doing the first thing is the biggest hurdle. Companies often set the bar too high—“I need to increase revenue by 20%.” They look for one magical thing to achieve that goal, but it isn't how it works. The real path is cumulative—task after task, every task, that gets you to the finish line. If you can't run because of two feet of snow, ask yourself, “Is running the only thing that gets me to a couch‑to‑5K?” Probably not. Dig deeper for smaller milestones—bite‑sized actions you can take. People often resist because they've already made a plan and don't want to redo it. Christopher S. Penn: My solution, which removes excuses, is to put the plan into your AI of choice and ask, “What's the first step I can take today toward this plan?” Acknowledge how the plan should adapt, but focus on the immediate action. For example, if you can't safely run, you might do leg squats to start strengthening muscles, so when you can run you'll be in better condition. That pushes accountability back onto you and gives you a bite‑size start. Planning has always been about agility—agile versus waterfall. Today's AI tools let you pivot on a dime. You can say, “Here's the Q4 with the Q1 plan, here's everything that has changed,” and then dictate new directions. Ask the AI for three to seven ideas for pivoting so you can still hit the 20% revenue increase target. These tools can suggest alternatives when, say, social media burns to the ground but you still have an email list, or when you haven't tried text messaging yet. Katie Robbert: At Trust-Insights we have an open, transparent culture. I'm all for experimentation as long as it's acknowledged. “I'm going to try this thing, here's the cost.” Not everyone has that luxury. Imagine a VP of marketing tasked with increasing website traffic by 30% and generating enough new MQLs to keep the sales team happy. Social media isn't the answer; email is exhausted. You look at higher‑cost options—paid ads, SMS texting. Those require software, time to find opted‑in phone numbers, and budget. That's where the fear comes in: a long list of options, but you have to justify the budget and risk failure. Christopher S. Penn: In scenario planning, you say, “The goal is a 20% revenue increase. This is what it will cost to get there. Stakeholder, is this still the goal?” If the stakeholder can't give you the budget, you can't achieve the plan. You might say, “With $500 I can get you 4% of the goal,” but the full goal requires more. You've done due diligence: the company's goal is set, but the reality is limited resources. It's like wanting to drive 500 miles with only a gallon of gas—you can't make the car use less gas to cover that distance. Katie Robbert: I'll challenge you to imagine you have no authority to push back on stakeholders. You can't simply say, “I can't do this.” You have to have the conversation—no excuses. In many organizations, the response is, “I don't want to hear excuses; we have to hit our numbers.” Christopher S. Penn: I've been in that situation. The typical response is to shift blame quickly, document everything, and blame the stakeholder to their boss. That's the solution that worked at AT&T, Lucent, and other large corporations. It goes back to why plans aren't executed: if you have no role, authority, or relationship power to change the plan, your best bet to keep your job is to deflect blame to someone else, ideally the stakeholder, as fast as possible. Katie Robbert: That's one of the worst answers you've ever given me. Christopher S. Penn: Putting myself in that position—I've been there, and that's exactly what you do to survive in big corporate America. Katie Robbert: If you get receipts but still have to do something, you can't just sit at your desk twiddling your thumbs. What do you actually do? Christopher S. Penn: Do you really want the answer? You call as many meetings as possible throughout the quarter so it looks like you're doing something. You send lots of emails, create fake activity that's considered acceptable in corporate America—“We're having a meeting to plan about the plan,” “We're having a pre‑meeting for the meeting.” That's why so little gets done, especially in risk‑averse organizations: everyone's energy is spent covering their own backs, so no one takes a real step forward. You cover your butt by saying, “I'm calling meetings, we're looking busy, we're talking about the plan for the plan.” Do you get anything done? No. Do you make progress toward your plan? No. Do you have something for your annual review that looks good? Yes. That's why many organizations are stuck on rung one of the AI ladder. In a place like Trust-Insights, I can say, “I'm going to do this thing.” It might spectacularly implode, but as long as it doesn't financially endanger the company or cause reputational harm, it's fine. That's why startups can challenge incumbents—they don't have the calcified bureaucracy of blame deflection. You can try something that might not work, but you'll try it anyway because you can. In risk‑averse, fear‑driven organizations, that never happens. That's why many talk about side hustles. When we started Trust-Insights, we had a side hustle because the corporate side fired people at the first sign of a 1% goal decline. With Trust-Insights now, I don't need a side hustle. Everything we do redirects back to Trust-Insights. We don't have a culture of fear that stops us from trying things. If I'm in a gray cubicle, my goal is to survive another day until the next paycheck. That's fair, and many people find themselves in that position. Katie Robbert: Back to AI tools: there is a way to at least try. We put a plan together and ask, “Who's going to execute it?” We're a four‑person team with big dreams and expectations, but the reality is we're still underwater. I open a chat in Gemini or Claude and say, “Here are my restrictions—zero budget. What can I do that's low risk, won't damage our reputation, and won't take a million hours?” These tools excel at pattern recognition, finding that tiny piece of information the human is blind to because they're too close. For example, we might be over‑indexed on our email list. Is there anything else we haven't done with email? That channel is still under our control. Could we draft copy for ads we can't run yet? Could we draft newsletter outreach even if we can't send it today? Is our newsletter list clean and ready? Those are low‑risk steps that keep the plan moving forward without exposing us to investors for a failed experiment. Christopher S. Penn: Exactly. For folks who feel stuck with no role power or relationship power, generative AI can help. If you can find $20 a month for a paid tool, great. It's never been easier to start a side hustle—no need to learn programming. If you have a good idea and are willing to invest time outside of work on your own hardware, now is the best time to try creating something. It may not work, but it's better than feeling stuck and powerless. If your plan feels like it's moving at 900-mph off a cliff, the tools are out there. If you have the willingness to take a little risk outside your day job, give it a shot. Katie Robbert: I keep trying to pull people back into their day jobs and help them find solutions because not everyone has time for a side hustle. Many are working parents or have a second job. This morning I asked, “What is one thing I can do today that won't take much time or budget but helps me keep moving forward?” One suggestion was to update CRM records. Marketing plans often require good, clean data. If you can't afford paid ads, are you ready to run them when you can? Look internally: do we have the best possible data? Is it clean? Is it ready? Can I draft copy for ads or newsletters even if we can't launch them yet? Those are low‑risk actions that keep momentum. Christopher S. Penn: The other thing to consider for those with no role or relationship power is that generative AI can be a low‑cost ally. If you can spend $20 a month on a paid tool, you have a new avenue to create value. Katie Robbert: My challenge to anyone stuck in Q1 plans—or any quarter—is to dig deep and ask, “What is one low‑risk, low‑resource thing I can do?” Is the data hygiene ready? If you were granted all the budget today, would you be ready to execute? Find those things, and you'll keep moving forward. Once you start that momentum—one foot in front of the other—it's easier to keep going. Christopher S. Penn: Absolutely. Christopher S. Penn: If you have thoughts on how you're getting unstuck, no matter the quarter, pop by our free Slack group—Trust-Insights-AI analysts for marketers—where over 4,500 marketers ask and answer each other's questions every day. You can also find us on the Trust-Insights-AI podcast, available wherever podcasts are served. Thanks for tuning in. We'll talk to you on the next one. Katie Robbert: Want to know more about Trust-Insights? Trust-Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher-S.-Penn, the firm is built on the principles of truth, acumen, and prosperity, helping organizations make better decisions and achieve measurable results through a data‑driven approach. Trust-Insights specializes in helping businesses leverage data, AI, and machine learning to drive measurable marketing ROI. Services span comprehensive data strategies, deep‑dive marketing analysis, predictive models using tools like TensorFlow and PyTorch, and optimizing content strategies. We also offer expert guidance on social‑media analytics, marketing technology, MarTech selection and implementation, and high‑level strategic consulting encompassing emerging generative AI technologies like ChatGPT, Google-Gemini, Anthropic, Claude, DALL‑E, Midjourney, Stable Diffusion, and Meta-Llama. Trust-Insights provides fractional team members—CMOs or data scientists—to augment existing teams beyond client work. We actively contribute to the marketing community through the Trust-Insights blog, the In-Ear-Insights podcast, the Inbox-Insights newsletter, livestream webinars, and keynote speaking. What distinguishes us is our focus on delivering actionable insights, not just raw data. We excel at leveraging cutting‑edge generative AI techniques while explaining complex concepts clearly through compelling narratives and visualizations. Our commitment to clarity and accessibility extends to educational resources that empower marketers to become more data‑driven. Trust-Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you're a Fortune-500 company, a mid‑size business, or a marketing agency seeking measurable results, we offer a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever‑evolving landscape of modern marketing and business in the age of generative AI. Trust-Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

Q1 Lesson 13 - Live Man Walking

In this episode, we sit down with Sean Paul Murray from the Irish Football Association (IFA) for a deep dive into the evolution of coach education, leadership, and the power of intentional learning design.Sean shares his journey from his earliest memories in football to shaping coach development structures that prioritize people over PowerPoints. This conversation explores what great environments look like, how emotional intelligence influences leadership, and what the future holds for coach education.Listen to find out more including;- How we should rethink coach education structures?- What learner centered and not content centered education looks like?- How environments shape behavior and decision making?- Self-awareness as a leadership foundation.- Advice for coaches and coach developers seeking long-term impact.Get in touch;Instagram: https://www.instagram.com/conorwalsh1995/YouTube; https://www.youtube.com/@TheLowdownPodEmail: cwalsh95@outlook.ie

Listen and Subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed Alicia Lyttle. SUMMARY OF THE ALICIA LYTTLE INTERVIEW From “Money Making Conversations Master Class” with Rushion McDonald [ 1. Purpose of the Interview The purpose of this interview was to: Showcase Alicia Lyttle, CEO and co‑founder of Air Innovations, known widely as the “Queen of AI.” [ Educate small business owners, entrepreneurs, and nonprofits on how to leverage AI for growth. Highlight her mission to empower the African American community to not only keep up with AI—but lead in it. [ Demonstrate how AI tools can transform operations, content creation, finances, and productivity in minutes instead of months. Inspire listeners through her entrepreneurial journey, professional pivots, and personal resilience. 2. High-Level Summary Alicia Lyttle returns to the show two years after her last appearance, now positioned at the forefront of the global AI movement. She explains how her work has shifted from annual summits to monthly AI Business Summits, teaching tens of thousands of entrepreneurs how to use AI hands‑on for content, marketing, operations, and scaling. She breaks down how simple tools—such as NotebookLM, ChatGPT, Jasper, Gemini, and HeyGen—can turn a single piece of content into newsletters, PowerPoints, videos, study guides, and more. She stresses that AI is now accessible, especially with free versions like ChatGPT. Alicia also shares her origin story in AI, beginning with a 15‑year‑old speaker at Walmart Tech Live describing IBM Watson. This sparked her fascination and ultimately led her to pivot her entire company toward full-time AI training and consulting by 2022—despite skepticism from her peers. She details the massive growth of her brand, including 21,000+ live summit attendees and explosive social media expansion. The interview also addresses AI’s role in finance, healthcare, government, job disruption, and how individuals can future‑proof themselves. Her personal story of overcoming a restrictive ex-husband who told her she would “never speak again” underscores her powerful message: no one should silence your gifts. Now she speaks to thousands, leads major events, and helps others build new careers in AI. 3. Key Takeaways A. AI Is Evolving Fast—and So Must We AI is changing so quickly that entrepreneurs cannot afford to wait for annual updates. This is why Alicia shifted to monthly training summits. People need ongoing education to stay competitive. B. Hands‑On AI Education Is the Key Alicia doesn’t just lecture—she walks participants through real demonstrations: Uploading YouTube links Creating summaries Generating emails, mind maps, PowerPoints, quizzes, videos, and more…all from a single input. Her approach eliminates fear and teaches entrepreneurs how to use AI immediately. C. Accessibility Has Changed the Game The release of ChatGPT, especially the free version, democratized AI. Before that, tools like IBM Watson were too complex and expensive. Now anyone with a laptop and internet connection can build websites, write content, or automate business flows in minutes. [ D. The African American Community Must Lead—Not Follow Alicia emphasizes that historically, Black communities have been “last in line” in tech innovation, but this AI era presents a once‑in‑a‑generation opportunity to jump ahead.She sees it as her mission to speak everywhere Black entrepreneurs are to ensure they seize this moment. E. AI Will Replace Tasks—But People Can Future‑Proof Themselves Jobs are already shifting. Companies are laying off non–AI‑literate employees.Alicia urges people to: Become AI‑fluent Join AI committees at work Pursue certification Use AI to become their company’s internal expert “There’s no maybe—you have to learn AI,” she warns. F. AI is Transforming Every Sector: Finance, Healthcare, Government She provides insights on… AI receptionists (“Monica” and “Leslie”) that boost customer interaction to 92% Financial analysis using secure ChatGPT setups AI mental health companions Government calls for national AI leadership G. Alicia Monetizes Through Education, Certification & Consulting Her business model includes: Free monthly summits Paid masterclasses Corporate consulting AI certifications Live Atlanta workshops She teaches others to become AI consultants too. H. Her Personal Triumph Story Inspires Thousands A powerful moment is when she recounts her ex-husband saying: “There’s only one quarterback on a team—and you will never speak again.”Yet today, 1,200+ people attend her live events, and tens of thousands join her virtual trainings. Her success proves resilience and purpose overcome adversity. 4. Key Quotes On AI Opportunity “Never has there been a better time in history to start, build, or scale a business than right now.” On Training Entrepreneurs “Open your laptops… use the same prompt I use. See what results you get.” On the Power of AI Tools “You can take one episode and repurpose it into all these different content ways.” On Pivoting Her Entire Company “In 2022, I said we’re closing this business and going all in on AI.” On Being Black in Tech “My mission is to make sure our community is not left behind—but ahead of the curve.” On Personal Resilience “You will be speaking on the best stages… people will come to see you.”(A friend’s response after she was told she’d “never speak again.”) On Future-Proofing Careers “Those using AI will replace you. You have to learn how to leverage AI.” On AI as a Human-First Technology “AI plus human intelligence—that’s what takes things to the next level.” #SHMS #STRAW #BESTSupport the show: https://www.steveharveyfm.com/See omnystudio.com/listener for privacy information.

Listen and Subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed Alicia Lyttle. SUMMARY OF THE ALICIA LYTTLE INTERVIEW From “Money Making Conversations Master Class” with Rushion McDonald [ 1. Purpose of the Interview The purpose of this interview was to: Showcase Alicia Lyttle, CEO and co‑founder of Air Innovations, known widely as the “Queen of AI.” [ Educate small business owners, entrepreneurs, and nonprofits on how to leverage AI for growth. Highlight her mission to empower the African American community to not only keep up with AI—but lead in it. [ Demonstrate how AI tools can transform operations, content creation, finances, and productivity in minutes instead of months. Inspire listeners through her entrepreneurial journey, professional pivots, and personal resilience. 2. High-Level Summary Alicia Lyttle returns to the show two years after her last appearance, now positioned at the forefront of the global AI movement. She explains how her work has shifted from annual summits to monthly AI Business Summits, teaching tens of thousands of entrepreneurs how to use AI hands‑on for content, marketing, operations, and scaling. She breaks down how simple tools—such as NotebookLM, ChatGPT, Jasper, Gemini, and HeyGen—can turn a single piece of content into newsletters, PowerPoints, videos, study guides, and more. She stresses that AI is now accessible, especially with free versions like ChatGPT. Alicia also shares her origin story in AI, beginning with a 15‑year‑old speaker at Walmart Tech Live describing IBM Watson. This sparked her fascination and ultimately led her to pivot her entire company toward full-time AI training and consulting by 2022—despite skepticism from her peers. She details the massive growth of her brand, including 21,000+ live summit attendees and explosive social media expansion. The interview also addresses AI’s role in finance, healthcare, government, job disruption, and how individuals can future‑proof themselves. Her personal story of overcoming a restrictive ex-husband who told her she would “never speak again” underscores her powerful message: no one should silence your gifts. Now she speaks to thousands, leads major events, and helps others build new careers in AI. 3. Key Takeaways A. AI Is Evolving Fast—and So Must We AI is changing so quickly that entrepreneurs cannot afford to wait for annual updates. This is why Alicia shifted to monthly training summits. People need ongoing education to stay competitive. B. Hands‑On AI Education Is the Key Alicia doesn’t just lecture—she walks participants through real demonstrations: Uploading YouTube links Creating summaries Generating emails, mind maps, PowerPoints, quizzes, videos, and more…all from a single input. Her approach eliminates fear and teaches entrepreneurs how to use AI immediately. C. Accessibility Has Changed the Game The release of ChatGPT, especially the free version, democratized AI. Before that, tools like IBM Watson were too complex and expensive. Now anyone with a laptop and internet connection can build websites, write content, or automate business flows in minutes. [ D. The African American Community Must Lead—Not Follow Alicia emphasizes that historically, Black communities have been “last in line” in tech innovation, but this AI era presents a once‑in‑a‑generation opportunity to jump ahead.She sees it as her mission to speak everywhere Black entrepreneurs are to ensure they seize this moment. E. AI Will Replace Tasks—But People Can Future‑Proof Themselves Jobs are already shifting. Companies are laying off non–AI‑literate employees.Alicia urges people to: Become AI‑fluent Join AI committees at work Pursue certification Use AI to become their company’s internal expert “There’s no maybe—you have to learn AI,” she warns. F. AI is Transforming Every Sector: Finance, Healthcare, Government She provides insights on… AI receptionists (“Monica” and “Leslie”) that boost customer interaction to 92% Financial analysis using secure ChatGPT setups AI mental health companions Government calls for national AI leadership G. Alicia Monetizes Through Education, Certification & Consulting Her business model includes: Free monthly summits Paid masterclasses Corporate consulting AI certifications Live Atlanta workshops She teaches others to become AI consultants too. H. Her Personal Triumph Story Inspires Thousands A powerful moment is when she recounts her ex-husband saying: “There’s only one quarterback on a team—and you will never speak again.”Yet today, 1,200+ people attend her live events, and tens of thousands join her virtual trainings. Her success proves resilience and purpose overcome adversity. 4. Key Quotes On AI Opportunity “Never has there been a better time in history to start, build, or scale a business than right now.” On Training Entrepreneurs “Open your laptops… use the same prompt I use. See what results you get.” On the Power of AI Tools “You can take one episode and repurpose it into all these different content ways.” On Pivoting Her Entire Company “In 2022, I said we’re closing this business and going all in on AI.” On Being Black in Tech “My mission is to make sure our community is not left behind—but ahead of the curve.” On Personal Resilience “You will be speaking on the best stages… people will come to see you.”(A friend’s response after she was told she’d “never speak again.”) On Future-Proofing Careers “Those using AI will replace you. You have to learn how to leverage AI.” On AI as a Human-First Technology “AI plus human intelligence—that’s what takes things to the next level.” #SHMS #STRAW #BESTSee omnystudio.com/listener for privacy information.

Listen and Subscribe to Money Making Conversations on iHeartRadio, Apple Podcasts, Spotify, or wherever you listen to podcasts. New Money Making Conversations episodes drop daily. I want to alert you, so you don’t miss out on expert analysis and insider perspectives from my guests who provide tips that can help you uplift the community, improve your financial planning, motivation, or advice on how to be a successful entrepreneur. Keep winning! Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed Alicia Lyttle. SUMMARY OF THE ALICIA LYTTLE INTERVIEW From “Money Making Conversations Master Class” with Rushion McDonald [ 1. Purpose of the Interview The purpose of this interview was to: Showcase Alicia Lyttle, CEO and co‑founder of Air Innovations, known widely as the “Queen of AI.” [ Educate small business owners, entrepreneurs, and nonprofits on how to leverage AI for growth. Highlight her mission to empower the African American community to not only keep up with AI—but lead in it. [ Demonstrate how AI tools can transform operations, content creation, finances, and productivity in minutes instead of months. Inspire listeners through her entrepreneurial journey, professional pivots, and personal resilience. 2. High-Level Summary Alicia Lyttle returns to the show two years after her last appearance, now positioned at the forefront of the global AI movement. She explains how her work has shifted from annual summits to monthly AI Business Summits, teaching tens of thousands of entrepreneurs how to use AI hands‑on for content, marketing, operations, and scaling. She breaks down how simple tools—such as NotebookLM, ChatGPT, Jasper, Gemini, and HeyGen—can turn a single piece of content into newsletters, PowerPoints, videos, study guides, and more. She stresses that AI is now accessible, especially with free versions like ChatGPT. Alicia also shares her origin story in AI, beginning with a 15‑year‑old speaker at Walmart Tech Live describing IBM Watson. This sparked her fascination and ultimately led her to pivot her entire company toward full-time AI training and consulting by 2022—despite skepticism from her peers. She details the massive growth of her brand, including 21,000+ live summit attendees and explosive social media expansion. The interview also addresses AI’s role in finance, healthcare, government, job disruption, and how individuals can future‑proof themselves. Her personal story of overcoming a restrictive ex-husband who told her she would “never speak again” underscores her powerful message: no one should silence your gifts. Now she speaks to thousands, leads major events, and helps others build new careers in AI. 3. Key Takeaways A. AI Is Evolving Fast—and So Must We AI is changing so quickly that entrepreneurs cannot afford to wait for annual updates. This is why Alicia shifted to monthly training summits. People need ongoing education to stay competitive. B. Hands‑On AI Education Is the Key Alicia doesn’t just lecture—she walks participants through real demonstrations: Uploading YouTube links Creating summaries Generating emails, mind maps, PowerPoints, quizzes, videos, and more…all from a single input. Her approach eliminates fear and teaches entrepreneurs how to use AI immediately. C. Accessibility Has Changed the Game The release of ChatGPT, especially the free version, democratized AI. Before that, tools like IBM Watson were too complex and expensive. Now anyone with a laptop and internet connection can build websites, write content, or automate business flows in minutes. [ D. The African American Community Must Lead—Not Follow Alicia emphasizes that historically, Black communities have been “last in line” in tech innovation, but this AI era presents a once‑in‑a‑generation opportunity to jump ahead.She sees it as her mission to speak everywhere Black entrepreneurs are to ensure they seize this moment. E. AI Will Replace Tasks—But People Can Future‑Proof Themselves Jobs are already shifting. Companies are laying off non–AI‑literate employees.Alicia urges people to: Become AI‑fluent Join AI committees at work Pursue certification Use AI to become their company’s internal expert “There’s no maybe—you have to learn AI,” she warns. F. AI is Transforming Every Sector: Finance, Healthcare, Government She provides insights on… AI receptionists (“Monica” and “Leslie”) that boost customer interaction to 92% Financial analysis using secure ChatGPT setups AI mental health companions Government calls for national AI leadership G. Alicia Monetizes Through Education, Certification & Consulting Her business model includes: Free monthly summits Paid masterclasses Corporate consulting AI certifications Live Atlanta workshops She teaches others to become AI consultants too. H. Her Personal Triumph Story Inspires Thousands A powerful moment is when she recounts her ex-husband saying: “There’s only one quarterback on a team—and you will never speak again.”Yet today, 1,200+ people attend her live events, and tens of thousands join her virtual trainings. Her success proves resilience and purpose overcome adversity. 4. Key Quotes On AI Opportunity “Never has there been a better time in history to start, build, or scale a business than right now.” On Training Entrepreneurs “Open your laptops… use the same prompt I use. See what results you get.” On the Power of AI Tools “You can take one episode and repurpose it into all these different content ways.” On Pivoting Her Entire Company “In 2022, I said we’re closing this business and going all in on AI.” On Being Black in Tech “My mission is to make sure our community is not left behind—but ahead of the curve.” On Personal Resilience “You will be speaking on the best stages… people will come to see you.”(A friend’s response after she was told she’d “never speak again.”) On Future-Proofing Careers “Those using AI will replace you. You have to learn how to leverage AI.” On AI as a Human-First Technology “AI plus human intelligence—that’s what takes things to the next level.” #SHMS #STRAW #BESTSteve Harvey Morning Show Online: http://www.steveharveyfm.com/See omnystudio.com/listener for privacy information.

Speaker -Derek Powell Thursday 12th February 2026 Find out more about our new Thursday Gathering - www.ebe.org.uk/thursdaygatherings. Also download PowerPoints, view songs that we used, etc..

How to Scale Faster with B2B Brand Strategy Here's a common scenario in B2B marketing: you launch campaigns, hit the deadlines, and fill the pipeline, but the results feel disconnected from your long-term goals. Internal messaging discussions resurface, campaigns feel shallow and reactive, and when you ask people what your brand stands for, you get 50 different answers. This inconsistent approach creates friction and impedes scalable growth. So what can B2B marketers do when their tactical execution is outpacing their brand strategy, and how to do you realign for lasting impact? That's why we're talking to JoAnne Gritter (COO, ddm marketing + communications), who shares her expertise and actionable insights on how to scale faster with B2B brand strategy. During our conversation, JoAnne underscored why a foundational strategy is crucial for building credibility and trust in competitive markets. She also discussed the role of AI in marketing, commenting that while it can support with idea generation and research, it shouldn't replace direct communication with customers and employees. JoAnne shared some common pitfalls such as messaging misalignment and inconsistent branding, which can lead to distrust and reduced credibility, She explained the importance of having a cohesive brand strategy that aligns values, messaging, and customer experiences across all company touchpoints through proactive brand management. https://youtu.be/_Alwkinhw-g Topics discussed in episode: [02:36] The “Soul vs. Body” framework: Why marketing is just the body in action, while brand strategy is the soul that provides direction and values.  [06:51] Red flags that your marketing has outpaced your strategy: When content feels fragmented and sales teams are telling completely different stories.  [08:52] Defining true brand strategy: Moving beyond logos and colors to include deep research, stakeholder analysis, and internal alignment.  [14:41] The critical differences between a brand refresh (auditing existing assets), a complete revamp (starting from scratch), and branding during a merger.  [24:10] Actionable steps you can take to realign your brand: – Audit your customer journey – Define messaging pillars – Ensure HR and onboarding match the brand promise  [29:37] Why “data-only” marketing fails: The importance of human emotion and psychology that performance data often misses.  Companies and links mentioned: JoAnne Gritter on LinkedIn  ddm marketing + communications  Transcript JoAnne Gritter, Christian Klepp JoAnne Gritter  00:00 AI can be used as a tool. It should not replace thinking and actually talking to your customers and your employees and your sales team. So you can use AI as a crutch to to like, ask it for ideas, idea generation. You can use it for deep research on your on your audience, and stuff like that. But nothing replaces the gold standard of talking to people. I see this in messaging misalignment or content misalignment. If content feels like it’s been written by four different people or completely different companies, that’s a red flag. Christian Klepp  00:37 This is a common scenario for B2B Marketers. You launch campaigns, hit the deadlines and fill the pipeline. It all looks great on paper, but something is still off internal messaging discussions resurface. Campaigns feel shallow and reactive, and when you ask people what the brand stands for, you get 50 different answers. So what can B2B Marketers do when their marketing is outpacing their brand strategy? Welcome to this episode of the B2B Marketers in the Mission podcast, and I’m your host, Christian Klepp, today, I’ll be talking to JoAnne Gritter, who will be answering this question. She’s a member of the leadership team at DDM Marketing Communications that provides integrated marketing solutions to drive business success. Tune in to find out more about what this B2B Marketers Mission is and here we go. JoAnne Gritter, welcome to the show. JoAnne Gritter  01:25 Hi Christian. Happy to be here. Christian Klepp  01:27 We you know, we had such a wonderful, like, pre-interview conversation. I almost feel like we’re neighbors or something, and something to that extent. But I’m, I’m really, like, happy to have you on the show, and I’m really looking forward to this conversation, because this topic is, I’m a little bit biased because I am in the branding space, so it’s a bit near and dear to my heart, but it’s also something that’s extremely important, because you’ll agree. I mean, you, I know you’ll agree because you wrote an article about it. JoAnne Gritter  01:54 Yeah Christian Klepp  01:55 It’s something that marketing teams tend to overlook. And good, goodness gracious me, I’m gonna, like, stop keeping people in suspense. We’ll just jump right in all right. JoAnne Gritter  02:04 Okay Christian Klepp  02:04 So JoAnne, you’re on a mission to provide integrated marketing solutions that drive B2B business success. So for this conversation, let’s focus on this topic, how brand strategy helps B2B organizations to realign for long term growth. So I’m going to kick off this conversation with the following question. In our previous conversation, our previous discussion, you talked about how marketing without a brand is a strategy without a soul. Could you please explain what you meant by that? JoAnne Gritter  02:36 So I just made the comparison kind of to the whole human, as in, like the brand is your soul, meaning like your values, what drives you, why you’re here, what differentiates you, what makes you different than the person standing next to you, whereas, like marketing is your body in action, or action in general, where you hopefully, if you if you’re a trustworthy person, what is, what are your values internally are matching your actions externally? And that is often where we see a divergent in companies, because they don’t think about those as like two sides of the same coin. It is really important that you make sure that you know the direction that you’re going as a company and what you stand for and who you’re there to support or serve, and what markets you’re there to do, and like your whole company, everybody that’s part of interfacing with customers understands that and is and is speaking the same language. Christian Klepp  03:37 Yeah, no, absolutely. And I suppose the the follow up question to that is like, where do you see a lot of, like, marketing teams go wrong. Because, like, you know, more often than not, a lot of teams are like, Okay, we’ve we’ve implemented the campaigns check. We’re generating results and driving pipeline or filling the pipeline, rather check. So where does it all go wrong? JoAnne Gritter  04:00 If you are not paying attention to your branding, you can have a lot of activity without a lot of traction. So or you can have a lot of different messages going out that seem not cohesive or fragmented. And so you can or more examples you can have, like your sales folks going out and telling different stories about about what your company stands for and what you do and how you’re different, that creates a lot of waste, because then you’re continuously trying to get more activity and more campaigns going more sales people out there, because you’re not getting the quality leads that you need, because nobody really knows what you stand for. Everybody says it a little bit differently, and that goes for customer service too. Branding. People think about branding as a marketing problem, or a marketing, you know, teams problem. But if, let’s say part of your brand is your brand identity or values is to put the customer. First, if you don’t really solidify that from your sales team and your customer support team, then there would be a mismatch there, right then you’re just putting out into the world that customers first, but that doesn’t match up with what the customer is experiencing. Christian Klepp  05:16 Yeah, there’s certainly some kind of misalignment there, and you touched on it, like, briefly. It’s interesting to me, like, even in my own experience, one of the telltale signs of that is when you ask people within the organization, well, what makes you different? And you get 50 different answers, and some of them are similar, and some of them are completely, like, different. And it’s like, okay, yep, okay, I see where this is going, or to your to your other point, when sales teams are having those discovery calls, and you listen back to some of those recordings, which I hope you marketing people out there are doing, and you listen to the way that the sales deal with objections, and maybe the procurement team or people like, you know, on the prospect side, they’re probably not phrasing it exactly the way I’m going to say it right now, but like, but they probably are asking something to the effect of, okay, what makes you different from vendor B, C and D, right? What is different about your solution? Like, why are you charging this guy? Why are your rates like, this high. JoAnne Gritter  05:16 Right. Absolutely. And if they have different answers, or if you go and you listen in on four different sales calls and they’re all a little bit different, then that tells you have a branding issue that people don’t fully understand your brand and how you’re different and who you support and serve. Christian Klepp  05:16 Yep, absolutely, absolutely. So you’ve touched on it a little bit, but like, tell us about some more of these. I’m going to call them red flags, right? That signal when marketing has outrun brand strategy. JoAnne Gritter  05:16 Sure, I see this in messaging misalignment or content misalignment. If content feels like it’s been written by four different people or completely different companies, that’s a red flag. If, like we mentioned, your sales team talks about your company completely differently, it’s okay that they put their own little spin on it, as long as you’re still hitting like the purpose of your company, why you’re here, how you serve whatever your target audience or audiences are what your values are. If that’s not coming through in in those different places, then you may have a brand issue, or your training issue, or your brand is not being carried out through the company. So when you have a solid brand, it should be, should be repeated in in like your onboarding process, in HR kind of things, in performance conversations, in obviously, your sales and marketing and your customer service, so that everybody is aligned to that brand, and so that there’s a common message, common theme, because repeatability is is super important. Consistency is super important in marketing. I’m sure a lot of people have heard that it takes multiple multi multiple times of hearing the same message for it to actually resonate, and if they’re hearing multiple different messages, it’s causes confusion and a lack of trust in whatever the company is offering. Christian Klepp  05:16 Yeah, that’s absolutely right. JoAnne, I’ve got a I just thought of another fall off question, and you’ll indulge me here. Um, you know it, I know it. But let’s, let’s clear the air here for a second. Because I’ve been hearing this like, and I’m sure you have as well, in the B2B world, it’s just been thrown around, like, very loosely. Let’s clear the air here. Like, what do you mean by brand strategy, because I’ve heard people, especially at senior level, say, like, Yeah, we don’t need branding. We’ve got a logo and we’ve got a website. We’re good, so maybe just clear the air on that one, please. JoAnne Gritter  05:16 Well, brand strategy is, let’s see, like, I think of strategy in like, four or three different tiers. Like, we have your business strategy, it’s how you win in the marketplace. Then you have your brand strategy, which is positions you in the market and in the minds of your consumers or your customers. And then your marketing strategy is how you take that and communicate it out and you deliver that message in multiple different channels. So if you have marketing running without, without laddering up to that business strategy and and brand strategy, then it’s just, it’s just running and putting stuff out there. So it’s just activity without, without purpose and strategy. So like a brand strategy is so much more than just a lot of people think about it as their logo, their identity suite, whatever, but there should be research that goes into it. They should be stakeholder analysis. They should talk to your customers and kind of understand what they value about about your company compared to another company. So then, using. Their language in some of your brand messaging is super helpful. So if you have like, customers that say, you know, like, I just love working with, you know, Company X, Y and Z, because the people are great. They’re super responsive. They they get me what I need, etc. Like, using some of that as part of your brand is going to be really important. So like, a strategy may may include, like, the focus, the brand, promise your your core values can be part of that. The naming can be part of that. Obviously, the the design part that a lot of folks actually think about and listen or think about and recall would be, like the visual identity that also needs to be consistent, from your logo to your fonts to your colors, and then like, multiple touch points on that, like, again, like repeating that consistency from like the stationary, the collateral, the assets, all that stuff, but then also making sure that the messaging and the voice carries throughout your company, past past your your marketing team, past your sales team. Christian Klepp  05:16 Yeah, that’s absolutely right. I mean, I like to tell people that all of these things that you mentioned, especially the visual aspect, the the sexy part of it, right, like the the visual identity, the logo, the web design and all that. It’s the end result. It’s one of the outcomes of right branding, right? JoAnne Gritter  05:16 That doesn’t come out of a vacuum, right? You don’t show a designer that’s like, I’m super excited about the color red, so we’re gonna do it’s what do our customers, current customers, feel about us, and what do we want our prospective customers to feel about us? And then there’s a lot of strategy behind that. Christian Klepp  05:16 That’s right, that’s right. I’m gonna move on to the topic of key pitfalls to avoid. So what are some of these key pitfalls that B2B Marketing Teams should avoid, and what should they do instead? JoAnne Gritter  05:16 So pitfalls that I see is companies teams that get really excited about certain trends. I’m just going to pick on Tiktok. There’s time and a place for Tiktok, but like, for B2B, they’re like, oh, man, everybody’s on Tiktok, or this latest, you know, social media platform, channel, we really got to get on there. It’s or we got to use AI in some specific way without, like, thinking about the strategy behind that and just like going forward, because you know that that’s the hottest trend right now. So always make sure it ladders up to where your customers are and what you want them to think about you. If you’re a B2B company, it’s likely that your customers are more on LinkedIn than they are on Tiktok. That’s just an example. I can’t say that across the board, but like picking picking things that are always centered on on your customer and your brand are super important. So that’s a pitfall, and then what to do about it? Also treating the brand as a one time exercise, like set it and forget it, kind of thing. A lot of people are just like, Okay, we did the brand. We got a great logo, we got stationery, we even got PowerPoints that are branded and then never think about it again, except for, like, just the, you know, the colors and the logo on all of your media assets, right? So, but the brand is so much more than that. The brand is so much about, like, how you want them to feel, what the differentiators are, what makes you different, what you deliver and like, how you talk about it, how you position yourself. So like, every bit, every asset that goes out the door, should be aligned to that there should be almost a hierarchy. Christian Klepp  05:16 Yeah, no, exactly, exactly. And I’m gonna throw another follow up question at you, only because I know you can handle you can handle it. You probably hear this a lot, and you hear this a lot, most likely also from marketing teams that perhaps don’t have as much experience in the branding space as you do, and they say things like, JoAnne, you know, we’re looking at our company, and we feel that, you know, the overall look and feel and the direction, it’s not really in line with what we aspire to be. So we’re looking for a revamp. And then, and then, as the conversation progresses, they say, Oh, actually, we want maybe, maybe just a refresh, right? And then you hear another prospect say, Well, you know, we just merged the two companies. So like, what do we do there? So maybe just, just to, again, clear the air, so people don’t throw around these terms so recklessly, what actually is the difference between a brand refresh, a brand revamp, and branding as a result of a merger, Speaker 1  06:02 like a brand like from scratch, is going to take a lot of different kind of research efforts than like a brand refresh. Like, if you’re doing a brand refresh, then you’re looking at assets that already exist, you know, and and you’re looking at reasons why they might change or are no longer working. So you’re doing more. Of an audit kind of thing, like, what’s different now than it was 20 years ago when we created this brand, and where are we going? Their new leadership? Are they focused on different parts of this like even even DDM, the marketing agency that I work with or that I work for. We, every once in a while, look at our brand, and not just the visuals, but like the things that make us unique. And we say, hey, those are still unique, but we’re talking about them slightly differently now. So we need to take a look at that and change the messaging a little bit. We’re heading in a slightly different direction lately with our creative so let’s, let’s make sure that we’re still in line, so that everything, everything matches. And if they see us on Instagram versus if they see us on LinkedIn or on our website, that it still looks like ABM, you know, and then a merger is slightly different, because you’re putting together two brands, and a lot of times they’re creating a new brand from that, or they might keep one of the brands and then just bring another like, you know, Company X is now a, you know, Company Y brand. And there might be, like a sub. There’s all kinds of different ways hierarchies of brands in that kind of scenario. But more recent one that we did, they created a new brand, which was a combination of the two names, and they completely they went through the whole exercise with the new leadership team. So it’s more similar to like starting from scratch, but also taking bits and pieces that they want to keep from both brands and what’s working. So you kind of look at what clients from both brands like about those brands, and make sure that you keep those and you preserve those, and make sure that it’s it’s heading in the direction that the company wants to go a lot of discovery and research and questions, Christian Klepp  06:16 Absolutely, absolutely. And I love that you keep bringing that up, though, because that is, again, one of these components that people tend to overlook, that this comes with a lot of research. It’s not, as you said, it’s not okay. Here’s the brief. Graphic designers or design team have at it. JoAnne Gritter  17:07 Right? Christian Klepp  17:07 Come up with something, something else, great, right? Yeah, my favorite briefs are always the ones that said we want something modern, clean, yet traditional and exciting. It’s like, JoAnne Gritter  17:17 Oh yes, creative. Make it creative, splashy mean to you? Christian Klepp  17:25 Yeah, yeah, open to interpretation, I suppose. Why do you believe that inconsistent messaging and internal misalignment cost organizations credibility and dollars? And you did touch on it earlier on the conversation. JoAnne Gritter  17:41 It’s a misalignment of what you say versus what you do. If you have on your website that you are there to serve X population and that you are like your mission and purpose in in this world is to support that population in in achieving whatever goal, whatever needs that that population needs, but then that customer or population that comes and interacts with your brand does not get that from the people or get that from their experience with your product. Then then that’s a misalignment, and that creates, you know, instant distrust, like you are not following through on, on what your brand promise was, or if you have multiple people saying they’re promising different things and they don’t get that, that’s a lack of trust. Christian Klepp  18:27 I’m kind of slightly grinning here, although I know that anyone who’s been in this situation probably will not see any humor in it, but like, I’m just thinking about anyone that’s experienced a flight delay, JoAnne Gritter  18:37 right, Christian Klepp  18:39 or been trapped at the airport, and whichever airline it is you’re flying with, and you have to deal with ground staff that are either unprofessional and rude or you just have zero transparency. And I’m sure, like, I’ve certainly gone through it like I’ve experienced a 10, 12 hour flight delay, right where I was at the airport until like, one or two in the morning, and then they finally come and say, well, the plane’s not coming. JoAnne Gritter  19:04 Yeah, that really rocks the brand reputation. I also see that in health care a lot, which, God bless everybody in health care, it’s hard, but like, if all those services are disjointed and the scheduling gives you a different feeling than the doctor gives and trying to do things online, it doesn’t match what your experience is in person. People don’t want to go to that provider anymore. You know, they’re like, this is confusing. I just want help. Just want to get what you’re promising. Christian Klepp  19:35 It’s a very for lack of a description of fragmented ecosystem. JoAnne Gritter  19:39 Yeah, absolutely. And that’s a bigger issue than we can solve here, but Christian Klepp  19:43 Yeah, no amount of branding is going to fix that. JoAnne Gritter  19:47 You got to follow through on it. Christian Klepp  19:49 That’s absolutely right. That’s absolutely right. Talk to us about how aligning, and you’ve touched on it briefly, how aligning soul and action will help to build. Trust, loyalty and resilience and please provide examples where relevant. JoAnne Gritter  20:04 Let me think of an example. We work with a very large medical device manufacturer, and we’ve worked with them for 15, probably close to 20 years now. And so 15 years ago, they were very product centric. They also grow by acquisition. So they have, like several different companies that came in under this master global brand. And even though they have the same logo, they still had their own kind of visual identity. They all talked about their stuff differently. And as a result of that, in those different teams, the customers were getting wildly different experiences from this company, even though they were all under the same master company. So they rebranded. We helped them rebrand seven years ago, maybe, and this is a global organization where they brought all their business units under the same brand. They have a very strict, robust brand now. And I’m not saying that everybody needs 100 page brand guidelines. They don’t, but, like they they went all in on branding, and they make all their new employees do their brand training. It’s worked in through their onboarding. It’s worked in through their like, performance conversations, and they have just really exploded and created this, this amazing reputation as a leader. Christian Klepp  21:25 I’m sorry you’re talking about, you’re talking about real branding, then JoAnne Gritter  21:27 Real branding. Yes, they are now a leader in their industry. I mean, they were big before, but they have just really exploded in the last seven years since rebranding, and it’s been really helpful for them, because now they still grow by acquisition, but they bring in a new company, and they know what the process is to get them on board, not just from a visual identity, like rebranding all the collateral, like the sales enablement and stuff like that, but bringing the internal teams up to speed about like, what what we stand for, what we hire, like, what kind of values we Look for, so that every customer gets the same experience Christian Klepp  22:04 from your experience. How did that exercise of helping them to re brand and take all of this because, you know, there’s that situation of taking all the business units and putting them under one roof, so to speak. How did that exercise help to improve them as an organization. JoAnne Gritter  22:22 It’s been a long time, like in multiple phases. So it improves their organization. It creates a lot of clarity for them. So they’re not like redoing each other’s work, and they’re not all creating the same or they’re they’re not all creating from scratch anymore. They have a they have a similar starting point on, like, the different messaging pillars that they need to hit, even for just their products, you know. So this goes into product messaging and product launch. So like, if they are medical device, they are they want to sell, you know, knee replacements or or stuff along those lines, they know that they need to hit on a couple core values, and they need to make sure that they are targeting the same audience, and that they need to make sure that they that what they’re saying out there aligns with the master brand. Of course, there’s they still need to do the differentiators on the product level, but they also have the full brand that that supports it. So it’s just a higher level like reputation. I like to, I like to compare like branding to your reputation. So that goes along with every product that they bring in. Christian Klepp  23:32 Yeah, no, absolutely, absolutely. Okay, we get to the part in the conversation. We’re talking about actionable tips. And you’ve, you’ve actually given us quite a bit already, but if we were to summarize it, okay, JoAnne, like, if there was somebody out if there was somebody out there that was listening to this conversation, and they were listening to what you were saying, and they were like, oh my goodness, this is exactly what we’re going through right now, right? I mean, besides contacting you, right, what are like three to five things that you would recommend they do right now to realign for long term growth using brand strategy, JoAnne Gritter  24:10 I would take a look at what brand strategy you already have, if you have one otherwise kind of creating at least the bones of that. Like, what are our values? What are we focused on? What is our purpose here and mission? And then, like, what are messaging pillars or groups that align with those values? And then once you have those making sure that you have a succinct narrative or story, or even, like an elevator pitch, that everybody is aligned on. Having that is kind of a simple, hopefully a simple thing for you to figure out and align on, and then auditing the customer journey for those promises and values. So like, if you have a customer journey, they’re going from, you know, awareness of you. Or a problem to consideration between you and your company, and, you know, multiple other companies, and then you’re they’re making a decision, then they’re purchasing, then they’re hopefully your customer experience, and your delivery teams are delivering on those promises, and then you’re creating loyalty. So that’s the customer journey. So of these phases are, they are the customers still experiencing the brand that you want them to experience. So that’s like a little audit that you can do. And then from there, also making sure that all of your content that’s out there, from your like your brochures, your website, your sales enablement kind of stuff, making sure that that’s still aligned to the brand and the message that that you want it to and then making sure that, of course, throughout the company, in your like, HR documentation, you’re, I’ve said onboarding a million times, but like, making sure that everybody that’s coming into your organization understands who you are and who you who you serve, and why? Christian Klepp  26:01 Absolutely, absolutely. And that’s a really good list. And I have to ask you this question, because you know, at the time of the recording, we’re at the end of 2025, and you did bring up AI, so I’m going to bring it up again. How, how has in your experience, from what you’re seeing out there, how has AI impacted brand strategy and all the work that comes along with that. JoAnne Gritter  26:24 Well, that’s a loaded question, right? So as far as brand strategy, I kind of see it. AI can be used as a tool. It should not replace thinking and actually talking to your customers and your employees and your sales team. So you can use AI as a crutch to to, like, ask it for ideas, idea generation. You can use it for deep research on your on your audience, and stuff like that. But nothing replaces the gold standard of talking to people. So like, the the best resources from that research perspective are your customers, or your prospective customers and your sales team, if you can’t get to those customers, will often hear those like, you know, positive and negatives about your products and services. So getting to those and aligning on stakeholders, AI can be used as you know, you can use it to help think of ideas for like, let me think if you were thinking of like values, like core values, like in and messaging pillars, you can say, hey, you know, I really want it to be something along these lines. We’re circling around on like, exactly right the what the right way to phrase this is. And it can give you 50 different ideas, and you can cross out 45 of them and then land on like the top five that you communicate with your team. Don’t ever take it for rate for like per vatum, sorry, exactly as chat GPT gives you, Christian Klepp  27:55 at face value. JoAnne Gritter  27:57 Thank you. I see that that is a lot harder for early career individuals because they don’t have that discernment yet. So they, they will, they will use it as a crutch, and then, like, oftentimes not have that same kind of editing expertise to see what actually works and what doesn’t. So like pairing AI as a tool with with human intelligence and empathy, for sure, Christian Klepp  28:23 Absolutely, absolutely. I mean, at least in from my observation, and this is where I think AI really falls flat, especially when you’re coming up with the verbal expression component of brand strategy. AI doesn’t really have any soul or character, like everything, it turns out, is very, for lack of a better description, lifeless, so, and that’s where the human element, or to your point, the human intervention, can then come into play, because then you can inject that story, you can inject that human emotion, which also is a very crucial component in B2B, right? As much as people like to say, oh, B2B is all factual, right? And I would, I would disagree with that, JoAnne Gritter  29:06 yeah, it’s, it’s quality over quantity. Now, you know people, people can spot, can spot the AI generated content, and there can be a whole bunch of it, and that can help you in a variety of ways. But if it’s not actually, if it doesn’t sound human speaking or human human sounding, then, then people reject it and they don’t trust it as much. Christian Klepp  29:28 Okay, get up on your soapbox a status quo that you passionately disagree with, and why? JoAnne Gritter  29:37 I passionately disagree with data only marketing. So the big push for data driven marketing, I am, I am on board with that at face value, but it still doesn’t tell the whole story, because you can still look at data from, let’s say you did like a. Um, a focus group about about what customers want from a like a beverage or something. I’m thinking of Coca Cola, and they and they say that they they want it to be healthy. They want it to be low sugar. They want it to taste amazing. They want it to make them, you know, feel great, and stuff like that that does not you’re gonna try to create like this Frankenstein kind of soda instead, instead of recognizing that, like, there’s more psychology to this. Like a Coca Cola has, like, a whole traditional, like branding kind of way that, or traditional and emotional way that they make people feel, and that doesn’t show up in the data, necessarily. That doesn’t show up in the performance data. You know that that is a totally different kind of research too. Christian Klepp  30:51 Yeah, yeah, JoAnne Gritter  30:55 You know, that’s performance, marketing and branding. Christian Klepp  30:58 I totally agree. I totally agree that, as much as there is a big camp out there that says the future is data driven now when it comes to B2B Marketing, and I’m like, Yeah, JoAnne Gritter  31:11 humans are tricky. Christian Klepp  31:13 We’re not robots. Absolutely, absolutely, okay, here comes the bonus question. So Rumor has it that you like to draw. JoAnne Gritter  31:23  I do. Christian Klepp  31:24 Yes, and from one enthusiastic sketcher to another, I thought, I thought deep and hard about this question. Tell us about one of the most well exciting, yes, but more importantly, one of the most challenging works that you’ve created to date. So what was the theme and subject? What made it so challenging to draw, and what did you learn from that experience when you when you completed it? JoAnne Gritter  31:50 I really like to find, like, kind of micro moments I have. I have three children at home, and I like to take pictures, or, like, capture, like small moments of, like one of them snuggling the cat, or like holding hands or doing something unexpected. And in, like, not a macro view, but in a micro view of like, the different connections that people have. And then, usually, I’ll take a picture, and then I will sketch those out after they go to sleep and stuff like that. And that’s just kind of my own personal way to, I don’t know it’s it’s therapeutic. It’s a way to see, see the beauty in the world, you know, and to slow down in the moment. Christian Klepp  32:37 100%. I like to call it Balsam for the soul. JoAnne Gritter  32:40 Yeah, Christian Klepp  32:40 all right, I don’t know about you, but like, I like to sketch in the in this very room where we’re doing the recording, and I usually play classical music. So like, show pen, so something like, with with piano. Like, no opera, because that can get a bit too dramatic. JoAnne Gritter  32:59 I like classical too, when, when I’m focused at classical music, and I also like binaural beats, or it’s more like meditation kind of music. So kind of zone, zone into the moment, instead of all the crazy thoughts that go through your head and all the things you have to do. Christian Klepp  33:17 Very nice, very nice. One of the things I learned about drawing is pretty much like certain aspects of our professional work, you know, like marketing and branding. It starts with a line, and then you just keep adding the layers, right? And it’s almost the same like when you’re implementing a campaign, you know, some especially nowadays, right? You try to start small first, and do a lot of testing to see if it works. And you scale from there. And I like to, I like to think of drawings that way too. You start, you start not by adding the details. You start like, you know, with a lighter pencil. And there’s a certain, there’s a certain way of holding the pencil tool, right, so you have lesser control. And just, it’s just a bit free flowing. And for me personally, it took me a long time to start drawing like that, because I’m like, No, then I don’t have control of the process. But that’s kind of the point, right? Let go of the perfectionism, right? JoAnne Gritter  34:18 You outline it first, and then you start filling in. You know that the shadows and the light marks, and then you slowly bring in the detail. I mean, that you’re totally right, that that is like a marketing or branding strategy. You got to outline it first before you go fully in on any specific detail. Otherwise, you’re you may be way off target. Christian Klepp  34:38 That’s it. That’s it. I mean, JoAnne like I think we just found our next podcast interview topic. But thank you so much for coming on and for sharing your expertise and experience with the listeners. So please a quick introduction to yourself and how people out they can get in touch with you. JoAnne Gritter  34:57 JoAnne Gritter, I’m at DDM Marketing and Communications headquartered in Grand Rapids, Michigan, USA. And I am COO, Vice President of our company. You can get a hold of me at joanneg@teamddm.com or you can just check us out at Teamddm.com Christian Klepp  35:18 Fantastic, fantastic. And we will be sure to like drop all those links in the show notes. So once again, JoAnne, thanks so much for your time. Take care, stay safe and talk to you soon. JoAnne Gritter  35:27 Thanks, Christian. Bye. Christian Klepp  35:29 Bye, for now you.

In this episode, I'm joined by Mandy Mooney — author, corporate communicator, and performer — for a wide-ranging conversation about mentorship, career growth, and how to show up authentically in both work and life.   We talk about her path from performing arts to corporate communications, and how those early experiences shaped the way she approaches relationships, leadership, and personal authenticity. That foundation carries through to her current role as VP of Internal Communications, where she focuses on building connections and fostering resilience across teams.   We explore the three pillars of career success Mandy highlights in her book Corporating: Three Ways to Win at Work — relationships, reputation, and resilience — and how they guide her approach to scaling mentorship and helping others grow. Mandy shares practical strategies for balancing professional responsibilities with personal passions, and why embracing technology thoughtfully can enhance, not replace, human connection.   The conversation also touches on parenting, building independence in children, and the lessons she's learned about optimism, preparation, and persistence — both in the workplace and at home.   If you're interested in scaling mentorship, developing your career with intention, or navigating work with authenticity, this episode is for you. And if you want to hear more on these topics, catch Mandy speaking at Snafu Conference 2026 on March 5th. 00:00 Start 02:26 Teaching Self-Belief and Independence Robin notes Mandy has young kids and a diverse career (performing arts → VP of a name-brand company → writing books). Robin asks: "What are the skills that you want your children to develop, to stay resilient in the world and the world of work that they're gonna grow up in?" Emphasis on meta-skills. Mandy's response: Core skills She loves the question, didn't expect it, finds it a "thrilling ride." Observes Robin tends to "put things out there before they exist" (e.g., talking about having children before actually having them). Skill 1: Envisioning possibilities "Envision the end, believe that it will happen and it is much more likely to happen." Teaching children to see limitless possibilities if they believe in them. Skill 2: Independence Examples: brushing their own hair, putting on clothes, asking strangers questions. One daughter in Girl Scouts: learning sales skills by approaching strangers to sell cookies. Independence builds confidence and problem-solving abilities for small and big life challenges. Skill 3: Self-belief / Self-worth Tied to independence. Helps children navigate life and career successfully. Robin asks about teaching self-belief Context: Mandy's kids are 6 and 9 years old (two girls). Mandy's approach to teaching self-belief Combination of: Words Mandy uses when speaking to them. Words encouraged for the children to use about themselves. Example of shifting praise from appearance to effort/creativity: Instead of "You look so pretty today" → "Wow, I love the creativity that you put into your outfit." Reason: "The voice that I use, the words that I choose, they're gonna receive that and internalize it." Corrective, supportive language when children doubt themselves: Example: Child says, "I'm so stupid, I can't figure out this math problem." Mandy responds: "Oh wow. That's something that we can figure out together. And the good news is I know that you are so smart and that you can figure this out, so let's work together to figure it out." Asking reflective questions to understand their inner thoughts: Example: "What's it like to be you? What's it like to be inside your head?" Child's response: "Well, you worry a lot," which Mandy found telling and insightful. Emphasizes coming from a place of curiosity to check in on a child's self-worth and self-identity journey. 04:30 Professional Journey and Role of VP of Internal Comms Robin sets up the question about professional development Notes Mandy has mentored lots of people. Wants to understand: Mandy's role as VP of Internal Communications (what that means). How she supports others professionally. How her own professional growth has been supported. Context: Robin just finished a workshop for professionals on selling themselves, asking for promotions, and stepping forward in their careers. Emphasizes that she doesn't consider herself an expert but learns from conversations with experienced people like Mandy. Mandy explains her role and path Career path has been "a winding road." Did not study internal communications; discovered it later. Finds her job fun, though sometimes stressful: "I often think I might have the most fun job in the world. I mean, it, it can be stressful and it can't, you know, there are days where you wanna bang your head against the wall, but by and large, I love my job. It is so fun." Internal communications responsibility: Translate company strategy into something employees understand and are excited about. Example: Translate business plan for 2026 to 2,800 employees. Team's work includes: Internal emails. PowerPoints for global town halls. Speaking points for leaders. Infusing fun into company culture via intranet stories (culture, customers, innovation). Quick turnaround on timely stories (example: employee running seven marathons on seven continents; story created within 24 hours). Storytelling and theater skills are key: Coaching leaders for presentations: hand gestures, voice projection, camera presence. Mandy notes shared theater background with Robin: "You and I are both thespian, so we come from theater backgrounds." Robin summarizes role Sounds like a mix of HR and sales: supporting employee development while "selling" them on the company. Mandy elaborates on impact and mentorship Loves making a difference in employees' lives by giving information and support. Works closely with HR (Human Resources) to: Provide learning and development opportunities. Give feedback. Help managers improve. Wrote a book to guide navigating internal careers and relationships. Mentorship importance: Mentors help accelerate careers in any organization. Mandy's career journey Started studying apparel merchandising at Indiana University (with Kelley School of Business minor). Shifted from pre-med → theater → journalism → apparel merchandising. Took full advantage of career fairs and recruiter networking at Kelley School of Business. "The way that I've gotten jobs is not through applying online, it's through knowing somebody, through having a relationship." First role at Gap Inc.: rotational Retail Management Training Program (RMP). Some roles enjoyable, some less so; realized she loved the company even if some jobs weren't ideal. Mentor influence: Met Bobby Stillton, president of Gap Foundation, who inspired her with work empowering women and girls. Took a 15-minute conversation with Bobby and got an entry-level communications role. Career growth happened through mentorship, internal networking, and alignment with company she loved. Advice for her daughters (Robin's question) Flash-forward perspective: post-college or early career. How to start a career in corporate / large organizations: Increase "luck surface area" (exposure to opportunities). Network in a savvy way. Ask at the right times. Build influence to get ahead. Mentorship and internal relationships are key, not just applying for jobs online. 12:15 Career Advice and Building Relationships Initial advice: "Well first I would say always call your mom. Ask for advice. I'm right here, honey, anytime." Three keys to success: Relationships Expand your network. "You say yes to everything, especially early in your career." Examples: sit in on meetings, observe special projects, help behind the scenes. Benefits: Increases credibility. Shows people you can do anything. Reputation Build a reputation as confident, qualified, and capable. Online presence: Example: LinkedIn profile—professional, up-to-date, connected to network. Be a sponsor/advocate for your company (school, office, etc.). Monthly posts suggested: team photos, events, showing responsibility and trust. Offline reputation: Deliver results better than expected. "Deliver on the things that you said you were gonna do and do a better job than people expected of you." Resilience Not taught from books—learned through experience. Build resilience through preparation, not "fake it till you make it." Preparation includes: practicing presentations, thinking through narratives, blocking time before/after to collect thoughts and connect with people. "Preparation is my headline … that's part of what creates resilience." Mandy turns the question to Robin: "I wanna ask you too, I mean, Robin, you, you live and breathe this every day too. What do you think are the keys to success?" Robin agrees with preparation as key. Value of service work: Suggests working in service (food, hospitality) teaches humility. "I've never met somebody I think even ever in my life who is super entitled and profoundly ungrateful, who has worked a service job for any length of time." Robin's personal experience with service work: First business: selling pumpkins at Robin's Pumpkin Patch (age 5). Key formative experience: running Robin's Cafe (2016, opened with no restaurant experience, on three weeks' notice). Ran the cafe for 3 years, sold it on Craigslist. Served multiple stakeholders: nonprofit, staff (~15 employees), investors ($40,000 raised from family/friends). Trial by fire: unprepared first days—no full menu, no recipes, huge rush events. Concept of MI Plus: "Everything in its place" as preparation principle. Connecting service experience to corporate storytelling: Current business: Zandr Media (videos, corporate storytelling). Preparation is critical: Know who's where, what will be captured, and what the final asset looks like. Limited fixes in post-production, even with AI tools. Reinforces importance of preparation through repeated experience. Advice for future children / young people: Robin would encourage service jobs for kids for months or a year. Teaches: Sleep management, personal presentation, confidence, energy. "Deciding that I'm going to show up professionally … well … energetically." Emphasizes relentless optimism: positivity is a superpower. Experience shows contrast between being prepared and unprepared—learning from both is crucial. 16:36 The Importance of Service Jobs and Resilience Service jobs as formative experience: Worked as a waitress early in her career (teenager). Describes it as "the hardest job of my life". Challenges included: Remembering orders (memory). Constant multitasking. Dealing with different personalities and attitudes. Maintaining positivity and optimism through long shifts (e.g., nine-hour shifts). Fully agrees with Robin: service jobs teach humility and preparation. Optimism as a superpower: "I totally agree too that optimism is a superpower. I think optimism is my superpower." Writes about this concept in her book. Believes everyone has at least one superpower, and successful careers involve identifying and leaning into that superpower. Robin asks about the book Why did Mandy write the book? Inspiration behind the book? Also wants a deep dive into the writing process for her own interest. Mandy's inspiration and purpose of the book Title: "Corporating: Three Ways to Win At Work" Primary goal: Scale mentorship. Realized as she reached VP level, people wanted career advice. Increased visibility through: Position as VP. Connection with alma mater (Indiana University). Active presence on LinkedIn. Result: Many young professionals seeking mentorship. Challenge: Not sustainable to mentor individually. Solution: Writing a book allows her to scale mentorship without minimizing impact. Secondary goals / personal motivations: Acts as a form of "corporate therapy": Reflects on first 10 years of her career. Acknowledges both successes and stumbles. Helps process trials and tribulations. Provides perspective and gratitude for lessons learned. Fun aspect: as a writer, enjoyed formatting and condensing experiences into a digestible form for readers. Legacy and contribution: "I had something that I could contribute meaningfully to the world … as part of my own legacy … I do wanna leave this world feeling like I contributed something positive. So this is one of my marks."   21:37 Writing a Book and Creative Pursuits Robin asks Mandy about the writing process: "What's writing been like for you? Just the, the process of distilling your thinking into something permanent." Mandy: Writing process and finding the "25th hour" Loves writing: "I love writing, so the writing has been first and foremost fun." Where she wrote the book: Mostly from the passenger seat of her car. She's a working mom and didn't have traditional writing time. Advice from mentor Gary Magenta: "Mandy, you're gonna have to find the 25th hour." She found that "25th hour" in her car. Practical examples: During birthday party drop-offs: "Oh good. It's a drop off party. Bye. Bye, honey. See you in two hours. I'll be in the driveway. In my car. If you need anything, please don't need anything." Would write for 1.5–2 hours. During Girl Scouts, swim, any activity. On airplanes: Finished the book on an eight-hour flight back from Germany. It was her 40th birthday (June 28). "Okay, I did it." Realization moment: "You chip away at it enough that you realize, oh, I have a book." Robin: On parents and prioritization Parents told him: "When you have kids, you just find a way." Children create: Stricter prioritization. A necessary forcing function. Mandy's self-reflection: "I believe that I am an inherently lazy person, to be totally honest with you." But she's driven by deadlines and deliverables. Kids eliminate "lazy days": No more slow Saturdays watching Netflix. "They get up. You get up, you have to feed these people like there's a human relying on you." Motherhood forces motivation: "My inherent laziness has been completely wiped away the past nine years." Writing happened in small windows of time. Importance of creative outlet: Having something for yourself fuels the rest of life. Examples: writing, crocheting, quilting, music. Creativity energizes other areas of life. Robin mentions The 4-Hour Workweek by Tim Ferriss. Advice from that book: Have something outside your day job that fuels you. For Robin: Physical practice (gym, handstands, gymnastics, ballet, capoeira, surfing). It's a place to: Celebrate. Feel progress. Win, even if work is struggling. Example: If tickets aren't selling. If newsletter flops. If client relationships are hard. Physical training becomes the "anchor win." Mandy's writing took over two years. Why? She got distracted writing a musical version of the book. There is now: "Corporating: The Book" "Corporating: The Musical" Three songs produced online. Collaboration with composer Eric Chaney. Inspiration from book: Time, Talent, Energy (recommended by former boss Sarah Miran). Concept: we have limited time, talent, and energy. Advice: Follow your energy when possible. If you're flowing creatively, go with it (unless there's an urgent deadline). You'll produce better work. She believes: The book is better because she created the musical. Musical helps during speaking engagements. Sometimes she sings during talks. Why music? Attention spans are short. Not just Gen Z — everyone is distracted. Music keeps people engaged. "I'm not just gonna tell you about the three ways to win at work. I'm gonna sing it for you too." Robin on capturing attention If you can hold attention of: Five-year-olds. Thirteen-year-olds. You can hold anyone's attention. Shares story: In Alabama filming for Department of Education. Interviewed Alabama Teacher of the Year (Katie). She has taught for 20 years (kindergarten through older students). Observed: High enthusiasm. High energy. Willingness to be ridiculous to capture attention. Key insight: Engagement requires energy and presence. 28:37 The Power of Music in Capturing Attention Mandy's part of a group called Mic Drop Workshop. Led by Lindsay (last name unclear in transcript) and Jess Tro. They meet once a month. Each session focuses on improving a different performance skill. The session she describes focused on facial expressions. Exercise they did: Tell a story with monotone voice and no facial expressions. Tell the story "over the top clown like, go really big, something that feels so ridiculous." Tell it the way you normally would. Result: Her group had four people. "Every single one of us liked number two better than one or three." Why version two worked best: When people are emotive and expressive: It's more fun to watch. It's more entertaining. It's more engaging. Connection to kids and storytelling: Think of how you tell stories to five-year-olds: Whisper. Get loud. Get soft. Use dynamic shifts. The same applies on stage. Musical integration: Music is another tool for keeping attention. Helps maintain engagement in a distracted world. Robin: Hiring for energy and presence Talks about hiring his colleague Zach Fish. Technical producer for: Responsive Conference. Snafu Conference. Freelancer Robin works with often. Why Robin hires Zach: Yes, he's technically excellent. But more importantly: "He's a ball of positive energy and delight and super capable and confident, but also just pleasant to be with." Robin's hiring insight: If he has a choice, he chooses Zach. Why? "I feel better." Energy and presence influence hiring decisions. Zach's background: Teaches weekly acrobatics classes for kids in Berkeley. He's used to engaging audiences. That translates into professional presence. Robin: Energy is learnable When thinking about: Who to hire. Who to promote. Who to give opportunities to. Traits that matter: Enthusiasm. Positivity. Big energy. Being "over the top" when needed. Important insight: This isn't necessarily a God-given gift. It can be learned. Like music or performance. Like anything else. 31:00 The Importance of Positive Work Relationships Mandy reflects on: The tension between loud voices and quiet voices. "Oftentimes the person who is the loudest is the one who gets to talk the most, but the person who's the quietest is the one who maybe has the best ideas." Core question: How do you exist in a world where both of those things are true? Parenting lens: One daughter is quieter than the other. Important to: Encourage authenticity. Teach the skill of using your voice loudly when needed. It's not about changing personality. It's about equipping someone to advocate for themselves when necessary Book is targeted at: Students about to enter the corporate world. Early-career professionals. Intentional writing decision: Exactly 100 pages. Purpose: "To the point, practical advice." Holds attention. Digestible. Designed for distracted readers. Emotional honesty: Excited but nervous to reconnect with students. Acknowledges: The world has changed. It's been a while since she was in college. Advice she's trying to live: Know your audience Core principle: "Get to know your audience. Like really get in there and figure out who they are." Pre-book launch tour purpose: Visiting universities (including her alma mater). Observing students. Understanding: Their learning environment. Their day-to-day experiences. The world they're stepping into. Communication principle: Knowing your audience is essential in communications. Also essential in career-building. If you have a vision of where you want to go: "Try to find a way to get there before you're there." Tactics: Meet people in those roles. Shake their hands. Have coffee. Sit in those seats. Walk those halls. See how it feels. Idea: Test the future before committing to it. Reduce uncertainty through proximity. What if you don't have a vision? Robin pushes back thoughtfully: What about people who: Don't know what they want to do? Aren't sure about staying at a company? Aren't sure about career vs. business vs. stay-at-home parent? Acknowledges: There's abundance in the world. Attention is fragmented. Implied tension: How do you move forward without clarity? 35:13 Mentorship and Career Guidance How to help someone figure out what's next Start with questions, not answers A mentor's primary job: ask questions from a place of curiosity Especially when someone is struggling with what they want to do or their career direction Key questions: What brings you joy? What gives you energy? What's the dream? Imagine retirement — what does that look like? Example: A financial advisor made Mandy and her husband define retirement vision; then work backwards (condo in New Zealand, annual family vacations) Clarify what actually matters Distinguish life priorities: Security → corporate job; Teamwork → corporate environment; Variety and daily interaction → specific roles Mentoring becomes a checklist: Joy, strengths, lifestyle, financial expectations, work environment preferences Then make connections: Introduce them to people in relevant environments, encourage informational interviews You don't know what you don't know Trial and error is inevitable Build network intentionally: Shadow people, observe, talk to parents' friends, friends of friends Even experienced professionals have untapped opportunities Stay curious and do the legwork Mixing personal and professional identity Confidence to bring personal interests into corporate work comes from strategy plus luck Example: Prologis 2021, senior leaders joked about forming a band; Mandy spoke up, became lead singer CEO took interest after first performance, supported book launch She didn't always feel this way Early corporate years: Feel like a "corporate robot," worrying about jargon, meetings, email etiquette, blending in Book explores blending in while standing out Advice for bringing full self to work Don't hide it, but don't force it; weave into casual conversation Find advocates: Amazing bosses vs terrible ones, learn from both Mentorship shaped her framework: Relationships, reputation, and resilience Resilience and rejection Theater as rejection bootcamp: Auditions, constant rejection Foundations of resilience: Surround yourself with supportive people, develop intrinsic self-worth, know you are worthy Creating conditions for success Age 11 audition story: Last-minute opportunity, director asked her to sing, she sang and got the part Why it worked: Connections (aunt in play), parent support, director willing to take a chance, she showed up Resilience is not just toughing it out: Have support systems, build self-worth, seek opportunity, create favorable conditions, step forward when luck opens a door 44:18 Overcoming Rejection and Building Resilience First show experiences Robin's first stage production is uncertain; she had to think carefully At 17, walked into a gymnastics gym after being a cross country runner for ten years, burnt out from running Cold-called gyms from the Yellow Pages; most rejected her for adult classes, one offered adult classes twice a week That led to juggling, circus, fencing, capa, rock climbing — a "Cambrian explosion" of movement opportunities About a year and a half later, walked into a ballet studio in corduroy and a button-up, no ballet shoes; first ballet teacher was Eric Skinner at Reed College, surrounded by former professional ballerinas First internal college production was his first show; ten years later performed as an acrobat with the San Francisco Opera in 2013, six acrobats among 200 people on stage, four-hour shows with multiple costume changes and backflips Relationship to AI and the evolving world of work Mandy never asks her daughters "What do you want to be?" because jobs today may not exist in the future Focus on interests: plants, how things are built, areas of curiosity for future generations Coaching her team: Highly capable, competent, invested in tools and technology for digital signage, webinars, emails, data-driven insights, videos Approach AI with cautious optimism: Adopt early, embrace technology, use it to enhance work rather than replace it Example: Uses a bot for scheduling efficiency, brainstorming; enhances job performance by integrating AI from day one Advice: Approach AI with curiosity, not fear; embrace tools to be smarter and more efficient, stay ahead in careers 53:05 Where to Find Mandy Mandy will be speaking at Snafu Conference on March 5, discussing rejection and overcoming it. Author and speaking information: mandymooney.com LinkedIn: Mandy Mooney Music available under her real name, Mandy Mooney, on streaming platforms.  

The Sean curse hits me in the wiener, funny bits from the Epstein files, a homeless man cons the hospital I'm at, white people's Power Points, cleaning up crime scenes, caste development at Microsoft, Black people in Minecraft, a sit-in at Target, and Vinnie's comedy club is attacked by a single protester; all this and more this week on The Dick Show!

Unser heutiger Gast ist Unternehmer, Ingenieur und Pionier – ein Mensch, der früh erkannt hat, dass Technologie nicht nur effizient, sondern auch regenerativ sein muss. Er hat Wirtschaftsingenieurwesen mit Schwerpunkt Maschinenbau, Logistik und Innovationsmanagement an den Technischen Universitäten in Kaiserslautern und Dresden studiert und begann seine Karriere als Berater und Managementtrainer. Doch eine Idee ließ ihn nicht mehr los: Was wäre, wenn wir den Wind dort nutzen könnten, wo er am stärksten und konstantesten weht, hoch oben am Himmel? 2001 gründete er SkySails mit dem Ziel, große Frachtschiffe per Zugdrachen anzutreiben. Die Vision war groß, die Technologie bahnbrechend, doch der Markt war zögerlich. Also pivotierte das Unternehmen. Heute entwickelt SkySails mit über 60 Expert:innen Systeme zur Stromgewinnung aus Höhenwinden an Land. Die Kraft der Atmosphäre, eingefangen durch autonome Zugdrachen, wird zu einer neuen Quelle sauberer Energie. Und damit zu einem echten Baustein für die Energiewende. Als „Ökomanager des Jahres“ und Träger des Roland Gutsch Awards hat er früh Anerkennung erhalten, doch geblieben ist er vor allem eines: ein begeisterter Segler, ein kreativer Ingenieur und ein Unternehmer, der lieber mit Prototypen arbeitet als mit PowerPoints. Seit mehr als acht Jahren beschäftigen wir uns in diesem Podcast mit der Frage, wie Arbeit den Menschen stärkt, statt ihn zu schwächen. Wir haben in über 500 Episoden mit fast 700 Persönlichkeiten darüber gesprochen, was sich bereits verändert hat und was sich weiter ändern muss. Wie hält man an einer Idee fest und lässt sie trotzdem los, wenn es nötig ist? Warum scheitert so viel klimafreundliche Innovation nicht an der Technik, sondern an politischen Rahmenbedingungen und Strukturen? Und was bedeutet unternehmerische Verantwortung, wenn man die Energieversorgung von morgen mitgestalten will? Fest steht: Für die Lösung unserer aktuellen Herausforderungen brauchen wir neue Impulse. Wir suchen weiter nach Methoden, Vorbildern, Erfahrungen, Tools und Ideen, die uns dem Kern von New Work näher bringen. Darüber hinaus beschäftigt uns von Anfang an die Frage, ob wirklich alle Menschen das finden und leben können, was sie im Innersten wirklich, wirklich wollen. Ihr seid bei On the Way to New Work, heute mit Stephan Wrage. [Hier](https://linktr.ee/onthewaytonewwork) findet ihr alle Links zum Podcast und unseren aktuellen Werbepartnern

Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed Alicia Lyttle. SUMMARY OF THE ALICIA LYTTLE INTERVIEW From “Money Making Conversations Master Class” with Rushion McDonald [ 1. Purpose of the Interview The purpose of this interview was to: Showcase Alicia Lyttle, CEO and co‑founder of Air Innovations, known widely as the “Queen of AI.” [ Educate small business owners, entrepreneurs, and nonprofits on how to leverage AI for growth. Highlight her mission to empower the African American community to not only keep up with AI—but lead in it. [ Demonstrate how AI tools can transform operations, content creation, finances, and productivity in minutes instead of months. Inspire listeners through her entrepreneurial journey, professional pivots, and personal resilience. 2. High-Level Summary Alicia Lyttle returns to the show two years after her last appearance, now positioned at the forefront of the global AI movement. She explains how her work has shifted from annual summits to monthly AI Business Summits, teaching tens of thousands of entrepreneurs how to use AI hands‑on for content, marketing, operations, and scaling. She breaks down how simple tools—such as NotebookLM, ChatGPT, Jasper, Gemini, and HeyGen—can turn a single piece of content into newsletters, PowerPoints, videos, study guides, and more. She stresses that AI is now accessible, especially with free versions like ChatGPT. Alicia also shares her origin story in AI, beginning with a 15‑year‑old speaker at Walmart Tech Live describing IBM Watson. This sparked her fascination and ultimately led her to pivot her entire company toward full-time AI training and consulting by 2022—despite skepticism from her peers. She details the massive growth of her brand, including 21,000+ live summit attendees and explosive social media expansion. The interview also addresses AI’s role in finance, healthcare, government, job disruption, and how individuals can future‑proof themselves. Her personal story of overcoming a restrictive ex-husband who told her she would “never speak again” underscores her powerful message: no one should silence your gifts. Now she speaks to thousands, leads major events, and helps others build new careers in AI. 3. Key Takeaways A. AI Is Evolving Fast—and So Must We AI is changing so quickly that entrepreneurs cannot afford to wait for annual updates. This is why Alicia shifted to monthly training summits. People need ongoing education to stay competitive. B. Hands‑On AI Education Is the Key Alicia doesn’t just lecture—she walks participants through real demonstrations: Uploading YouTube links Creating summaries Generating emails, mind maps, PowerPoints, quizzes, videos, and more…all from a single input. Her approach eliminates fear and teaches entrepreneurs how to use AI immediately. C. Accessibility Has Changed the Game The release of ChatGPT, especially the free version, democratized AI. Before that, tools like IBM Watson were too complex and expensive. Now anyone with a laptop and internet connection can build websites, write content, or automate business flows in minutes. [ D. The African American Community Must Lead—Not Follow Alicia emphasizes that historically, Black communities have been “last in line” in tech innovation, but this AI era presents a once‑in‑a‑generation opportunity to jump ahead.She sees it as her mission to speak everywhere Black entrepreneurs are to ensure they seize this moment. E. AI Will Replace Tasks—But People Can Future‑Proof Themselves Jobs are already shifting. Companies are laying off non–AI‑literate employees.Alicia urges people to: Become AI‑fluent Join AI committees at work Pursue certification Use AI to become their company’s internal expert “There’s no maybe—you have to learn AI,” she warns. F. AI is Transforming Every Sector: Finance, Healthcare, Government She provides insights on… AI receptionists (“Monica” and “Leslie”) that boost customer interaction to 92% Financial analysis using secure ChatGPT setups AI mental health companions Government calls for national AI leadership G. Alicia Monetizes Through Education, Certification & Consulting Her business model includes: Free monthly summits Paid masterclasses Corporate consulting AI certifications Live Atlanta workshops She teaches others to become AI consultants too. H. Her Personal Triumph Story Inspires Thousands A powerful moment is when she recounts her ex-husband saying: “There’s only one quarterback on a team—and you will never speak again.”Yet today, 1,200+ people attend her live events, and tens of thousands join her virtual trainings. Her success proves resilience and purpose overcome adversity. 4. Key Quotes On AI Opportunity “Never has there been a better time in history to start, build, or scale a business than right now.” On Training Entrepreneurs “Open your laptops… use the same prompt I use. See what results you get.” On the Power of AI Tools “You can take one episode and repurpose it into all these different content ways.” On Pivoting Her Entire Company “In 2022, I said we’re closing this business and going all in on AI.” On Being Black in Tech “My mission is to make sure our community is not left behind—but ahead of the curve.” On Personal Resilience “You will be speaking on the best stages… people will come to see you.”(A friend’s response after she was told she’d “never speak again.”) On Future-Proofing Careers “Those using AI will replace you. You have to learn how to leverage AI.” On AI as a Human-First Technology “AI plus human intelligence—that’s what takes things to the next level.” #SHMS #STRAW #BESTSupport the show: https://www.steveharveyfm.com/See omnystudio.com/listener for privacy information.

Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed Alicia Lyttle. SUMMARY OF THE ALICIA LYTTLE INTERVIEW From “Money Making Conversations Master Class” with Rushion McDonald [ 1. Purpose of the Interview The purpose of this interview was to: Showcase Alicia Lyttle, CEO and co‑founder of Air Innovations, known widely as the “Queen of AI.” [ Educate small business owners, entrepreneurs, and nonprofits on how to leverage AI for growth. Highlight her mission to empower the African American community to not only keep up with AI—but lead in it. [ Demonstrate how AI tools can transform operations, content creation, finances, and productivity in minutes instead of months. Inspire listeners through her entrepreneurial journey, professional pivots, and personal resilience. 2. High-Level Summary Alicia Lyttle returns to the show two years after her last appearance, now positioned at the forefront of the global AI movement. She explains how her work has shifted from annual summits to monthly AI Business Summits, teaching tens of thousands of entrepreneurs how to use AI hands‑on for content, marketing, operations, and scaling. She breaks down how simple tools—such as NotebookLM, ChatGPT, Jasper, Gemini, and HeyGen—can turn a single piece of content into newsletters, PowerPoints, videos, study guides, and more. She stresses that AI is now accessible, especially with free versions like ChatGPT. Alicia also shares her origin story in AI, beginning with a 15‑year‑old speaker at Walmart Tech Live describing IBM Watson. This sparked her fascination and ultimately led her to pivot her entire company toward full-time AI training and consulting by 2022—despite skepticism from her peers. She details the massive growth of her brand, including 21,000+ live summit attendees and explosive social media expansion. The interview also addresses AI’s role in finance, healthcare, government, job disruption, and how individuals can future‑proof themselves. Her personal story of overcoming a restrictive ex-husband who told her she would “never speak again” underscores her powerful message: no one should silence your gifts. Now she speaks to thousands, leads major events, and helps others build new careers in AI. 3. Key Takeaways A. AI Is Evolving Fast—and So Must We AI is changing so quickly that entrepreneurs cannot afford to wait for annual updates. This is why Alicia shifted to monthly training summits. People need ongoing education to stay competitive. B. Hands‑On AI Education Is the Key Alicia doesn’t just lecture—she walks participants through real demonstrations: Uploading YouTube links Creating summaries Generating emails, mind maps, PowerPoints, quizzes, videos, and more…all from a single input. Her approach eliminates fear and teaches entrepreneurs how to use AI immediately. C. Accessibility Has Changed the Game The release of ChatGPT, especially the free version, democratized AI. Before that, tools like IBM Watson were too complex and expensive. Now anyone with a laptop and internet connection can build websites, write content, or automate business flows in minutes. [ D. The African American Community Must Lead—Not Follow Alicia emphasizes that historically, Black communities have been “last in line” in tech innovation, but this AI era presents a once‑in‑a‑generation opportunity to jump ahead.She sees it as her mission to speak everywhere Black entrepreneurs are to ensure they seize this moment. E. AI Will Replace Tasks—But People Can Future‑Proof Themselves Jobs are already shifting. Companies are laying off non–AI‑literate employees.Alicia urges people to: Become AI‑fluent Join AI committees at work Pursue certification Use AI to become their company’s internal expert “There’s no maybe—you have to learn AI,” she warns. F. AI is Transforming Every Sector: Finance, Healthcare, Government She provides insights on… AI receptionists (“Monica” and “Leslie”) that boost customer interaction to 92% Financial analysis using secure ChatGPT setups AI mental health companions Government calls for national AI leadership G. Alicia Monetizes Through Education, Certification & Consulting Her business model includes: Free monthly summits Paid masterclasses Corporate consulting AI certifications Live Atlanta workshops She teaches others to become AI consultants too. H. Her Personal Triumph Story Inspires Thousands A powerful moment is when she recounts her ex-husband saying: “There’s only one quarterback on a team—and you will never speak again.”Yet today, 1,200+ people attend her live events, and tens of thousands join her virtual trainings. Her success proves resilience and purpose overcome adversity. 4. Key Quotes On AI Opportunity “Never has there been a better time in history to start, build, or scale a business than right now.” On Training Entrepreneurs “Open your laptops… use the same prompt I use. See what results you get.” On the Power of AI Tools “You can take one episode and repurpose it into all these different content ways.” On Pivoting Her Entire Company “In 2022, I said we’re closing this business and going all in on AI.” On Being Black in Tech “My mission is to make sure our community is not left behind—but ahead of the curve.” On Personal Resilience “You will be speaking on the best stages… people will come to see you.”(A friend’s response after she was told she’d “never speak again.”) On Future-Proofing Careers “Those using AI will replace you. You have to learn how to leverage AI.” On AI as a Human-First Technology “AI plus human intelligence—that’s what takes things to the next level.” #SHMS #STRAW #BESTSee omnystudio.com/listener for privacy information.

Two-time Emmy and Three-time NAACP Image Award-winning, television Executive Producer Rushion McDonald interviewed Alicia Lyttle. SUMMARY OF THE ALICIA LYTTLE INTERVIEW From “Money Making Conversations Master Class” with Rushion McDonald [ 1. Purpose of the Interview The purpose of this interview was to: Showcase Alicia Lyttle, CEO and co‑founder of Air Innovations, known widely as the “Queen of AI.” [ Educate small business owners, entrepreneurs, and nonprofits on how to leverage AI for growth. Highlight her mission to empower the African American community to not only keep up with AI—but lead in it. [ Demonstrate how AI tools can transform operations, content creation, finances, and productivity in minutes instead of months. Inspire listeners through her entrepreneurial journey, professional pivots, and personal resilience. 2. High-Level Summary Alicia Lyttle returns to the show two years after her last appearance, now positioned at the forefront of the global AI movement. She explains how her work has shifted from annual summits to monthly AI Business Summits, teaching tens of thousands of entrepreneurs how to use AI hands‑on for content, marketing, operations, and scaling. She breaks down how simple tools—such as NotebookLM, ChatGPT, Jasper, Gemini, and HeyGen—can turn a single piece of content into newsletters, PowerPoints, videos, study guides, and more. She stresses that AI is now accessible, especially with free versions like ChatGPT. Alicia also shares her origin story in AI, beginning with a 15‑year‑old speaker at Walmart Tech Live describing IBM Watson. This sparked her fascination and ultimately led her to pivot her entire company toward full-time AI training and consulting by 2022—despite skepticism from her peers. She details the massive growth of her brand, including 21,000+ live summit attendees and explosive social media expansion. The interview also addresses AI’s role in finance, healthcare, government, job disruption, and how individuals can future‑proof themselves. Her personal story of overcoming a restrictive ex-husband who told her she would “never speak again” underscores her powerful message: no one should silence your gifts. Now she speaks to thousands, leads major events, and helps others build new careers in AI. 3. Key Takeaways A. AI Is Evolving Fast—and So Must We AI is changing so quickly that entrepreneurs cannot afford to wait for annual updates. This is why Alicia shifted to monthly training summits. People need ongoing education to stay competitive. B. Hands‑On AI Education Is the Key Alicia doesn’t just lecture—she walks participants through real demonstrations: Uploading YouTube links Creating summaries Generating emails, mind maps, PowerPoints, quizzes, videos, and more…all from a single input. Her approach eliminates fear and teaches entrepreneurs how to use AI immediately. C. Accessibility Has Changed the Game The release of ChatGPT, especially the free version, democratized AI. Before that, tools like IBM Watson were too complex and expensive. Now anyone with a laptop and internet connection can build websites, write content, or automate business flows in minutes. [ D. The African American Community Must Lead—Not Follow Alicia emphasizes that historically, Black communities have been “last in line” in tech innovation, but this AI era presents a once‑in‑a‑generation opportunity to jump ahead.She sees it as her mission to speak everywhere Black entrepreneurs are to ensure they seize this moment. E. AI Will Replace Tasks—But People Can Future‑Proof Themselves Jobs are already shifting. Companies are laying off non–AI‑literate employees.Alicia urges people to: Become AI‑fluent Join AI committees at work Pursue certification Use AI to become their company’s internal expert “There’s no maybe—you have to learn AI,” she warns. F. AI is Transforming Every Sector: Finance, Healthcare, Government She provides insights on… AI receptionists (“Monica” and “Leslie”) that boost customer interaction to 92% Financial analysis using secure ChatGPT setups AI mental health companions Government calls for national AI leadership G. Alicia Monetizes Through Education, Certification & Consulting Her business model includes: Free monthly summits Paid masterclasses Corporate consulting AI certifications Live Atlanta workshops She teaches others to become AI consultants too. H. Her Personal Triumph Story Inspires Thousands A powerful moment is when she recounts her ex-husband saying: “There’s only one quarterback on a team—and you will never speak again.”Yet today, 1,200+ people attend her live events, and tens of thousands join her virtual trainings. Her success proves resilience and purpose overcome adversity. 4. Key Quotes On AI Opportunity “Never has there been a better time in history to start, build, or scale a business than right now.” On Training Entrepreneurs “Open your laptops… use the same prompt I use. See what results you get.” On the Power of AI Tools “You can take one episode and repurpose it into all these different content ways.” On Pivoting Her Entire Company “In 2022, I said we’re closing this business and going all in on AI.” On Being Black in Tech “My mission is to make sure our community is not left behind—but ahead of the curve.” On Personal Resilience “You will be speaking on the best stages… people will come to see you.”(A friend’s response after she was told she’d “never speak again.”) On Future-Proofing Careers “Those using AI will replace you. You have to learn how to leverage AI.” On AI as a Human-First Technology “AI plus human intelligence—that’s what takes things to the next level.” #SHMS #STRAW #BESTSteve Harvey Morning Show Online: http://www.steveharveyfm.com/See omnystudio.com/listener for privacy information.

https://traffic.libsyn.com/secure/bizpod/BEP103c-Charts-1.mp3 Welcome back to Business English Pod for today's lesson on using visuals and describing charts and trends in an English presentation. We've all sat through boring presentations, with PowerPoints that are just slide after slide of too much text. If all you're doing is reading off your slides, then why do a presentation at all? And if your audience falls asleep, then you've effectively communicated nothing. If you really want to grab people's attention, you use visuals. That could mean not just pictures, but graphs and charts. There's no better way to represent data than with graphs. But the graph doesn't do all the work for you. You still need to give it life and make it a seamless part of your overall presentation. The first thing you might do is introduce the point you want to make, before you use the visual. And remember that your audience might have some understanding of the topic already, so you should acknowledge that. And you can make it dramatic by using foreshadowing and highlighting important points. And just like in any presentation, it's good to use clear transitions between points and slides. In today's dialog, we'll hear a presentation from Pat, a director with a cell, or mobile phone manufacturer called Ambient. He's presenting to the company's sales team about how they've regained market share after a rough couple of years. We will hear how Pat uses visuals to enhance his presentation. Listening Questions 1. At the start of his presentation, what does Pat say they will focus on? 2. When talking about the company called Sirus, what does Pat “draw people's attention” to? 3. What does Pat say to transition to showing information about Ambient? Premium Members: PDF Transcript | Quizzes | PhraseCast | Lesson Module Download: Podcast MP3>>> The post BEP 103c – English Presentations Charts and Trends 1: Visuals first appeared on Business English Pod :: Learn Business English Online.

Think of your best friend. What makes them laugh? Whatmakes them mad? What makes them happy? When youknow someone very well, you know how they think andact. You even begin to think and act like them.

Dr. Peter Antevy returns to the Inside EMS co-host seat this week, filling in for Kelly Grayson and bringing some serious pediatric firepower to the conversation. Host Chris Cebollero dives right into the latest buzz around the Broselow tape recall — yes, again — as Dr. Antevy unpacks what went wrong, why it matters and what EMS agencies should be doing about it now. He also shares exciting details on his brand-new, field-focused Newborn Resuscitation & Obstetrics course (NROC), built by EMS for EMS. Designed with two hours of online content (zero PowerPoints!) and a short, in-house skills lab, this course aims to tackle one of the most nerve-wracking call types. No more dragging medics to the hospital for NRP classes that don't translate to street-level care. Also on deck: OB deserts, delayed cord clamping, why you might need to Saran-wrap a newborn (seriously), and what AI can — and can't — do for EMS. This one's packed with practical pearls, myth-busting insights and a whole lot of passion for pediatric education. Quotable takeaways from Dr. Peter Antevy “EMS is one specialty that AI will never take away, as far as like the human-to-human contact. We resuscitate people, we treat people who are seizing. AI will never do that. That's a good thing.” “Academics and the hospital folks don't recognize the value that EMS brings to the table. They think we're ambulance drivers. It's time for them to wake up and recognize that we are the people who deliver babies. We are the people who resuscitate grandma, grandpa and the little kid.” Enjoying Inside EMS? Email theshow@ems1.com to share feedback or suggest guests for future episodes. 

In this episode, Bill Scherkenbach, one of W. Edwards Deming's closest protégés, and host Andrew Stotz discuss why leadership decisions shape outcomes far more than frontline effort. Bill draws on decades of firsthand experience with Deming and with businesses across industries. Through vivid stories and practical insights, the conversation challenges leaders and learners alike to rethink responsibility, decision-making, and what it truly takes to build lasting quality. Bill's powerpoint is available here. TRANSCRIPT 0:00:02.2 Andrew Stotz: My name is Andrew Stotz, and I'll be your host as we dive deeper into the teachings of Dr. W. Edwards Deming. Today, I'm continuing my discussions with Bill Scherkenbach, a dedicated protégé of Dr. Deming since 1972. Bill met with Dr. Deming more than a thousand times and later led statistical methods and process improvement at Ford and GM at Dr. Deming's recommendation. He authored the Deming Route to Quality and Productivity at Deming's behest and at 79, still champions his mentor's message: Learn, have fun, and make a difference. The discussion for today is, I think we're going to get an answer to this question. And the question is: Where is quality made? Bill, take it away.   0:00:44.9 Bill Scherkenbach: Where is quality made? I can hear the mellifluous doctor saying that. And the answer is: In the boardroom, not on the factory floor. And over and over again, he would say that it's the quality of the decisions that the management make that can far outweigh anything that happens on the shop floor. And when he would speak about that, he would first of all, because he was talking to the auto industry, he would talk about who's making carburetors anymore. "Nobody's making carburetors because it's all fuel injectors," he would say. And anyone who has been following this, another classic one is: Do you ever hear of a bank that failed? Do you think that failed because of mistakes in tellers' windows or calculations of interest? Heck no. But there are a whole bunch of other examples that are even more current, if you will. I mean, although this isn't that current, but Blockbuster had fantastic movies, a whole array of them, the highest quality resolutions, and they completely missed the transition to streaming. And Netflix and others took it completely away from them because of mistakes made in the boardroom. You got more recently Bed Bath & Beyond having a great product, a great inventory.   0:02:51.4 Bill Scherkenbach: But management took their eyes off of it and looked at, they were concerned about stock buybacks and completely lost the picture of what was happening. It was perfect. It was a great product, but it was a management decision. WeWork, another company supplying office places. It was great in COVID and in other areas, but through financial mismanagement, they also ended up going bust. And so there are, I mean, these are examples of failures, but as Dr. Deming also said, don't confuse success with success. If you think you're making good decisions, you got to ask yourself how much better could it have been if you tried something else. So, quality is made in the boardroom, not on the factory floor.   0:04:07.9 Andrew Stotz: I had an interesting encounter this week and I was teaching a class, and there was a guy that came up and talked to me about his company. His company was a Deming Prize from Japan winner. And that was maybe 20, 25 years ago. They won their first Deming Prize, and then subsidiaries within the company won it. So the actual overall company had won something like nine or 10 Deming Prizes over a couple decades. And the president became...   0:04:43.5 Bill Scherkenbach: What business are they in?   0:04:45.5 Andrew Stotz: Well, they're in...   0:04:47.0 Bill Scherkenbach: Of winning prizes?   0:04:48.7 Andrew Stotz: Yeah, I mean, they definitely, the CEO got the distinguished individual prize because he was so dedicated to the teachings of Dr. Deming. And he really, really expanded the business well, the business did well. A new CEO took over 15 years ago, 10 years ago, and took it in another direction. And right now the company is suffering losses and many other problems that they're facing. And I asked the guy without talking about Deming, I just asked him what was the difference between the prior CEO and the current one or the current regimes that have come in. And he said that the prior CEO, it was so clear what the direction was. Like, he set the direction and we all knew what we were doing. And I just thought now as you talk about, the quality is made at the boardroom, it just made me really think back to that conversation and that was what he noticed more than anything. Yeah well, we were really serious about keeping the factory clean or we used statistics or run charts, that was just what he said, I thought that was pretty interesting.   0:06:06.7 Bill Scherkenbach: Absolutely. And that reminds me of another comment that Dr. Deming was vehement about, and that was was the management turnover. Turnovers in boardrooms every 18 months or so, except maybe in family businesses. But that's based on the quality of decisions made in the boardroom. How fast do you want to turn over the CEOs and that C-suite? So it's going to go back to the quality is made in the boardroom.   0:06:50.0 Andrew Stotz: Yeah, and I think maybe it's a good chance for me to share the slide that you have. And let's maybe look at that graphic. Does that makes sense now?   0:07:00.9 Bill Scherkenbach: Sure, for sure.   0:07:02.2 Andrew Stotz: Let's do that. Let's do that. Hold on. All right.   0:07:15.8 Bill Scherkenbach: Okay, okay, okay. You can see on the top left, we'll start the story. I've got to give you a background. This was generated based on my series of inputs and prompts, but this was generated by Notebook LM and based on the information I put in, this is what they came up with.   0:07:48.6 Andrew Stotz: Interesting.   0:07:50.1 Bill Scherkenbach: Based on various information, which I think did a fairly decent job. In any event, we're going to talk about all of these areas, except maybe the one where it says principles for active leadership, because that was the subject of a couple of our vlogs a while ago, and that is the three foundational obligations. And so the thing is that quality, even though Dr. Deming said it was made in the boardroom, one of the problems is that management did not know what questions to ask, and they would go, and Dr. Deming railed against MBWA, management by walking around, primarily because management hadn't made the transition to really take on board what Dr. Deming was talking about in profound knowledge. And that is, as you've mentioned, setting that vision, continually improving around it, and pretty much absolutely essential was to reduce fear within the organization.   0:09:25.9 Bill Scherkenbach: And so management by walking around without profound knowledge, which we've covered in previous talks, only gets you dog and pony shows. And with the fear in the organization, you're going to be carefully guided throughout a wonderful story. I mentioned I was in Disney with some of my granddaughters over the holidays, and they tell a wonderful story, but you don't ever see what's behind the scenery. And management never gets the chance because they really haven't had the opportunity to attain profound knowledge. So that's one of the things. I want to back up a little bit because Dr. Deming would... When Dr. Deming said quality is made at the top, he only agreed to help companies where the top management invited him, he wasn't out there marketing. If they invited him to come in, he would first meet with them and they had to convince him they were serious about participating, if not leading their improvement. And given that, that litmus test, he then agreed to work with them. Very few companies did he agree to on that. And again as we said, the quality of the decisions and questions and passion that determine the successfulness of the company. And so.   0:11:40.0 Andrew Stotz: It made me think about that letter you shared that he was saying about that there was, I think it was within the government and government department that just wasn't ready for change and so he wasn't going to work with it. I'm just curious, like what do you think was his... How did he make that judgment?   0:12:00.0 Bill Scherkenbach: Well, it wasn't high enough. And again, I don't know how high you'd have to go in there. But quite honestly, what we spoke about privately was in politics and in the federal government, at least in the US, things change every four years. And so you have management turnover. And so what one manager, as you described, one CEO is in there and another one comes in and wants to do it their way, they're singing Frank Sinatra's My Way. But that's life….   0:12:49.3 Andrew Stotz: Another great song.   0:12:50.7 Bill Scherkenbach: Another, yes.   0:12:52.1 Andrew Stotz: And it's not like he was an amateur with the government.   0:12:57.5 Bill Scherkenbach: No.   0:13:00.3 Andrew Stotz: He had a lot of experience from a young age, really working closely with the government. Do you think that he saw there was some areas that were worth working or did he just kind of say it's just not worth the effort there or what was his conclusions as he got older?   0:13:16.9 Bill Scherkenbach: Well, as he got older, it might, it was the turnover in management. When he worked for Agriculture, although agriculture is political, and he worked for Census Bureau back when he worked there, it wasn't that political, it's very political now. But there was more a chance for constancy and more of a, their aim was to do the best survey or census that they could do. And so the focus was on setting up systems that would deliver that. But that's what his work with the government was prior to when things really broke loose when he started with Ford and GM and got all the people wanting him in.   0:14:27.0 Andrew Stotz: I've always had questions about this at the top concept and the concept of constancy of purpose. And I'm just pulling out your Deming Route to Quality and Productivity, which, it's a lot of dog ears, but let's just go to chapter one just to remind ourselves. And that you started out with point number one, which was create constancy of purpose towards improvement of product and service with the aim to become competitive, stay in business and provide jobs. One of my questions I always kind of thought about that one was that at first I just thought he was saying just have a constancy of purpose. But the constancy of purpose is improvement of product and service.   0:15:13.6 Bill Scherkenbach: Well, yes and no. I mean, that's what he said. I believe I was quoting what his point number one was. And as it developed, it was very important to add, I believe, point number five on continual improvement. But constancy of purpose is setting the stage, setting the vision if you will, of where you want to take the company. And in Western management, and this is an area where there really is and was a dichotomy between Western and Eastern management. But in Western management, our concept of time was short-term. Boom, boom, boom, boom. And he had a definite problem with that. And that's how you could come up with, well, we're going to go with this fad and that fad or this CEO and that CEO. There was no thinking through the longer term of, as some folks ask, "what is your aim? Who do you think your customer base is now?" don't get suckered into thinking that carburetors are always going to be marketable to that market base. And so that's where he was going with that constancy of purpose. And in the beginning, I think that was my first book you're quoting, but also, in some of his earlier works, he also spoke of consistency of purpose, that is reducing the variation around that aim, that long-term vision, that aim.   0:17:19.2 Bill Scherkenbach: Now, in my second book, I got at least my learning said that you've got to go beyond the logical understanding and your constancy of purpose needs to be a mission, a values and questions. And those people who have who have listened to the the previous vlogs that we've had, those are the physiological and emotional. And I had mentioned, I think, that when when I went to GM, one of the things I did was looked up all the policy letters and the ones that Alfred Sloan wrote had pretty much consistency of three main points. One, make no mistake about it, this is what we're going to do. Two, this is why we're going to do it, logical folks who need to understand that. And to give a little bit of insight on on how he was feeling about it. Sometimes it was value, but those weren't spoken about too much back then. But it gave you an insider view, if you will. And so I looked at that, maybe I was overlooking. But I saw a physiological and emotional in his policy letters.   0:19:00.7 Bill Scherkenbach: And so that's got to be key when you are establishing your vision, but that's only the beginning of it. You have to operationalize it, and this is where management has to get out of the boardroom to see what's going on. Now, that's going to be the predictable, and some of your clients, and certainly the ones over in Asia, are speaking about Lean and Toyota Production System and going to the Gemba and all of those terms. But I see a need to do a reverse Gemba and we'll talk about that.   0:19:49.6 Andrew Stotz: So, I just want to dig deeper into this a little bit just for my own selfish understanding, which I think will help the audience also. Let's go back in time and say that the, Toyota, let's take Toyota as an example because we can say maybe in the 60s or so, they started to really understand that the improvement of product quality, products and service quality and all that was a key thing that was important to them. But they also had a goal of expanding worldwide. And their first step with that maybe was, let's just say, the big step was expanding to the US. Now, in order to expand to the US successfully, it's going to take 10, maybe 20 years. In the beginning, the cars aren't going to fit the market, you're going to have to adapt and all that. So I can understand first, let's imagine that somebody says our constancy of purpose is to continuously improve or let's say, not continuously, but let's just go back to that statement just to keep it clear. Let's say, create constancy of purpose towards improvement of product and service with the aim to become competitive, stay in business and provide jobs.   0:21:07.2 Andrew Stotz: So the core constancy in that statement to me sounds like the improvement. And then if we say, okay, also our vision of where we want to be with this company is we want to capture, let's say, 5% of the US market share within the next 15 years or five or 10 years. So you've got to have constancy of that vision, repeating it, not backing down from it, knowing that you're going to have to modify it. But what's the difference between a management or a leadership team in the boardroom setting a commitment to improvement versus a commitment to a goal of let's say, expanding the market into the US. How do we think about those two.   0:21:53.6 Bill Scherkenbach: Well as you reread what I wrote there, which is Dr. Deming's words and they led into the, I forget what he called it, but he led into the progression of as you improve quality, you improve productivity, you reduce costs.   0:22:33.6 Andrew Stotz: Chain reaction.   0:22:34.5 Bill Scherkenbach: Yeah, the chain reaction. That's a mini version of the chain reaction there. And at the time, that's what people should be signing up for. Now the thing is that doesn't, or at least the interpretations haven't really gone to the improvement of the board's decision-making process. I mean, where he was going for was you want to be able to do your market research because his sampling and doing the market research was able to close the loop to make that production view a system, a closed-loop system. And so you wanted to make sure that you're looking far enough out to be able to have a viable product or service and not get caught up in short-term thinking. Now, but again, short-term is relative. In the US, you had mentioned 10 or 20 years, Toyota, I would imagine they still are looking 100 years out. They didn't get suckered into the over-committing anyway to the electric vehicles. Plug-in hybrids, yes, hybrids yes, very efficient gas motors, yes. But their constancy of purpose is a longer time frame than the Western time frame.   0:24:27.1 Andrew Stotz: Yeah, that was a real attack on the structure that they had built to say when they were being told by the market and by everybody, investors, you've got to shift now, you've got to make a commitment to 100% EVs. I remember watching one of the boardroom, sorry, one of the shareholder meetings, and it's just exhausting, the pressure that they were under.   0:24:55.2 Bill Scherkenbach: Yep, yep. But there... Yeah.   0:25:00.0 Andrew Stotz: If we take a kid, a young kid growing up and we just say, look, your main objective, and my main objective with you is to every day improve. Whatever that is, let's say we're learning science.   0:25:17.3 Bill Scherkenbach: You're improving around your aim. What is your vision? What are you trying to accomplish? And that obviously, if you're you're saying a kid that could change otherwise there'd be an oversupply of firemen.   0:25:38.5 Andrew Stotz: So let's say that the aim was related to science. Let's say that the kid shows a really great interest in science and you're kind of coaching them along and they're like, "Help me, I want to learn everything I can in science." The aim may be a bit vague for the kid, but let's say that we narrow down that aim to say, we want to get through the main topics of science from physics to chemistry and set a foundation of science, which we think's going to take us a year to do that, let's just say. Or whatever. Whatever time frame we come up with, then every day the idea is, how do we number one improve around that aim? Are we teaching the right topics? Also, is there better ways of teaching? Like, this kid maybe learns better in the afternoon and in the morning, whereas another kid I may work with works better in another... And this kid likes five-minute modules and then some practical discussion, this kid likes, an hour of going deep into something and then having an experiment is when we're talking about improvement, is the idea that we're just always trying to improve around that aim until we reach a really optimized system? Is that what we're talking about when we're talking about constancy of purpose when it comes to improving product and service?   0:27:14.4 Bill Scherkenbach: Well there's a whole process that I take my clients through in coming up with their constancy of purpose statement. And the board should be looking at what the community is doing in the next five years, 10 years, where the market is going, where politics is going, all sorts of things. And some of it. I mean, specifically in the science area, it's fairly well recognized that the time of going generation to generation to generation has gone from years to maybe weeks where you have different iterations of technology. And so that's going to complicate stuff quite honestly, because what was good today can be, as Dr. Deming said, the world could change. And that's what you've got to deal with or you're out of business. Or you're out of relevance in what you're studying. And so you have to... If you if you have certain interests, and the interests are driven... It's all going to be internal. Some interests are driven because that's where I hear you can make the most money or that's where I hear you can make the most impact to society or whatever your internal interests are saying that those are key to establishing what your aim is.   0:29:25.7 Andrew Stotz: Okay. You've got some PowerPoints and we've been talking about some of it. But I just want to pull it up and make sure we don't miss anything. I think this is the first text page, maybe just see if there's anything you want to highlight from that. Otherwise we'll move to the next.   0:29:43.0 Bill Scherkenbach: No I think we've we've covered that. Yeah, yeah. And the second page. Yeah, I wanted to talk and I only mentioned it when the Lean folks and the Agile folks talk about Gemba, they're pretty much talking about getting the board out. It's the traditional management by walking around, seeing what happens. Hugely, hugely important. But one of the things, I had one of my clients. Okay, okay. No, that's in the the next one.   0:30:29.4 Andrew Stotz: There you go.   0:30:30.7 Bill Scherkenbach: Okay, yeah. I had one of one of my clients do a reverse Gemba. And that is, that the strategy committee would be coming up with strategies and then handing it off to the operators to execute. And that's pretty much the way stuff was done in this industry and perhaps in many of them. But what we did was we had the operators, the operating committee, the operations committee, sit in as a peanut gallery or a, oh good grief. Well, you couldn't say a thing, you could only observe what they were doing. But it helped the operators better understand and see and feel what the arguments were, what the discussions were in the strategy, so that they as operators were better able to execute the strategy. And so not the board going out and down, but the folks that are below going up if it helps them better execute what's going on. But vice versa, management can't manage the 94%, and Dr. Deming was purposely giving people marbles, sometimes he'd say 93.4%. You know the marble story?   0:32:37.5 Andrew Stotz: I remember that [laughter]. Maybe you should tell that again just because that was a fun one when he was saying to, give them marbles, and they gave me marbles back.   0:32:45.7 Bill Scherkenbach: Yeah, yeah, yeah. Well, he said there was this professor in oral surgery that said there was a an Asian mouse or cricket, whatever, that would... You put in your mouth and they would eat all of the... Be able to clean the gums of all the bacteria better than anything. And described it in detail. And that question was on the test. Okay, please describe this mouse procedure. And he said all of the people, or a whole bunch of people except one, gave him back exactly step by step that he had taught. And one said, Professor, I've talked to other professors, I've looked around, I think you're loading us, that's what Deming said. And so he made the point that teaching should not be teachers handing out marbles and collecting the same marbles they they handed out. And so to some extent, he was testing, being overly precise.   0:34:12.8 Bill Scherkenbach: He wanted people to look into it, to see, go beyond as you were speaking of earlier, going beyond this shocking statement that there perhaps is some way that that really makes sense. So he wants you to study. Very Socratic in his approach to teaching in my opinion. And any event, management can't understand or make inputs on changing what the various levels of willing workers, and you don't have to be on the shop floor, you can be in the C-suite and be willing workers depending on how your company is operating. Go ahead.   0:35:12.0 Andrew Stotz: So let me... Maybe I can, just for people that don't know, Gemba is a Japanese word that means "the actual place," right? The place where the value is created.   0:35:23.8 Bill Scherkenbach: Sure.   0:35:26.2 Andrew Stotz: And the whole concept of this was that it's kind of almost nonsense to think that you could sit up in an office and run something and never see the location of where the problem's happening or what's going on. And all of a sudden many things become clear when you go to the location and try to dig down into it. However, from Dr. Deming context, I think what you're telling us is that if the leader doesn't have profound knowledge, all they're going to do is go to the location and chase symptoms and disrupt work, ultimately...   0:36:02.0 Bill Scherkenbach: Get the dog and pony shows and all of that stuff. And they still won't have a clue. The thing is...   0:36:08.6 Andrew Stotz: So the objective at the board level, if they were to actually go to the place, the objective is observation of the system, of how management decisions have affected this. What is the system able to produce? And that gives them a deeper understanding to think about what's their next decision that they've got to make in relation to this. Am I capturing it right or?   0:36:40.2 Bill Scherkenbach: Well there's a lot more to it, I think, because top management, the board level, are the ones that set the vision, the mission, the values, the guiding principle, and the questions. And I think it's incumbent on the board to be able to go through the ranks and see how their constancy of purpose, the intended, where they want to take the place is being interpreted throughout the organization because, and I know it's an oversimplification and maybe a broad generalization, but middle management... Well, there are layers of management everywhere based on their aim to get ahead, will effectively stop communication upstream and downstream in order to fill their particular aim of what they want to get out of it. And so this is a chance for the top management to see, because they're doing their work, establishing the vision of the company, which is the mission, values and questions, they really should be able to go layer by layer as they're walking around seeing how those, their constancy, their intended constancy is being interpreted and executed. And so that's where beyond understanding how someone is operating a lathe or an accountant is doing a particular calculation, return on invested capital, whatever.   0:38:47.5 Bill Scherkenbach: Beyond that, I think it's important for management to be able to absolutely see what is happening. But the Gemba that I originally spoke about is just the other way. You've got the strategy people that are higher up, and you have the operations people that are typically, well, they might be the same level, but typically lower. You want the lower people to sit in on some higher meetings so they have a better idea of the intent, management's intent in this constancy of purpose. And that will help them execute, operationalize what management has put on paper or however they've got it and are communicating it. It just helps. So when I talk about Gemba, I'm talking the place where the quality is made or the action is. As the boardroom, you need to be able to have people understand and be able to see what's going on there, and all the way up the chain and all the way down the chain.   0:40:14.4 Andrew Stotz: That's great one. I'm just visualizing people in the operations side thinking, we've got some real problems here and we don't really understand it. We've got to go to the actual place, and that's the boardroom[laughter]. It's not the factory line.   0:40:31.7 Bill Scherkenbach: Yes. Absolutely. And if the boardroom says you're not qualified, then shame on you, the boardroom, are those the people you're hiring? So no, it goes both ways, both ways.   0:40:46.8 Andrew Stotz: Now, you had a final slide here. Maybe you want to talk a little bit about some of the things you've identified here.   0:40:53.4 Bill Scherkenbach: Okay, that's getting back to, in the logical area of this TDQA is my cycle: Theory, question, data, action. And it's based on Dr. Deming and Shewhart and Lewis saying, where do questions come from? They're based on theory. What do you do with questions? Well, the answers to questions are your data. And you're just not going to do nothing with data, you're supposed to take action. What are you going to do with it? And so the theory I'm going to address, the various questions I've found helpful in order to, to some extent, make the decisions better, the ability to operationalize them better and perhaps even be more creative, if you will. And so one of the questions I ask any team is, have you asked outside experts their opinion? Have you included them? Have you included someone to consistently, not consistently, but to take a contrarian viewpoint that their job in this meeting is to play the devil's advocate? And the theory is you're looking for a different perspective as Pete Jessup at Ford came up with that brilliant view of Escher's.   0:42:47.1 Bill Scherkenbach: Different perspectives are going to help you make a better decision. And so you want to get out of the echo chamber and you want to be challenged. Every team should be able to have some of these on there. What's going to get delayed? The underlying theory or mental model is, okay, you don't have people sitting around waiting for this executive committee to come up with new things, time is a zero-sum game. What's going to get delayed and what are they willing to get delayed if this is so darn important to get done? Decision criteria. I've seen many teams where they thought that the decision would be a majority rule. They discuss and when it came down to submit it, they said, "no, no, this VP is going to make the decision." And so that completely sours the next team to do that. And so you have to be, if you're saying trust, what's your definition of trust? If the people know that someone is going to make the decision with your advice or the executive's going to get two votes and everyone else gets one, or it's just simple voting.   0:44:35.3 Bill Scherkenbach: The point is that making the decision and taking it to the next level, the theory is you've got to be specific and relied on. Team turnover, fairly simple. We spoke about executive turnover, which was a huge concern that Dr. Deming had about Western management. But at one major auto company, we would have product teams and someone might be in charge of, be a product manager for a particular model car. Well, if that person was a hard charger and it took product development at the time was three and a half years, you're going to get promoted from a director level to a VP halfway through and you're going to screw up the team, other team members will be leaving as well because they have careers. You need to change the policy just to be able to say, if you agree that you're going to lead this team, you're going to lead it from start to finish and to minimize the hassle and the problems and the cost of turnover, team turnover. And this is a short list of stuff, but it's very useful to have a specific "no-fault policy."   0:46:20.6 Bill Scherkenbach: And this is where Dr. Deming speaks about reducing fear. I've seen teams who know they can really, once management turns on the spigot and says, let's really do this, this is important, the team is still hesitant to really let it go because that management might interpret that as saying, "well, what are you doing, slacking off the past year?" As Deming said, "why couldn't you do that if you could do it with no method, why didn't you do it last year?" but the fear in the organization, well, we're going to milk it. And so all of these things, it helps to be visible to everyone.   0:47:23.0 Andrew Stotz: So, I guess we should probably wrap up and I want to go back to where we started. And first, we talked about, where is quality made? And we talked about the boardroom. Why is this such an important topic from your perspective? Why did you want to talk about it? And what would you say is the key message you want to get across from it?   0:47:47.1 Bill Scherkenbach: The key message is that management thinks quality's made in operations. And it's the quality of the... I wanted to put a little bit more meat, although there's a lot more meat, we do put on it. But the quality of the organization, I wanted to make the point depends on the quality of the decisions, that's their output that top leaders make, whether it's the board or the C-suite or any place making decisions. The quality of your decisions.   0:48:28.9 Andrew Stotz: Excellent. And I remember, this reminds me of when I went to my first Deming seminar back in 1990, roughly '89, maybe '90. And I was a young guy just starting as a supervisor at a warehouse in our Torrance plant at Pepsi, and Pepsi sent me there. And I sat in the front row, so I didn't pay attention to all the people behind me, but there was many people behind me and there was a lot of older guys. Everybody technically was pretty much older than me because when I was just starting my career. And it was almost like these javelins were being thrown from the stage to the older men in the back who were trying to deal with this, and figure out what's coming at them, and that's where I kind of really started to understand that this was a man, Dr. Deming, who wasn't afraid to direct blame at senior management to say, you've got to take responsibility for this. And as a young guy seeing all kinds of mess-ups in the factory every day that I could see, that we couldn't really solve. We didn't have the tools and we couldn't get the resources to get those tools.   0:49:47.9 Andrew Stotz: It just really made sense to me. And I think the reiteration of that today is the idea, as I'm older now and I look at what my obligation is in the organizations I'm working at, it's to set that constancy of purpose, to set the quality at the highest level that I can. And the discussion today just reinforced it, so I really enjoyed it.   0:50:11.2 Bill Scherkenbach: Well, that's great. I mean, based on that observation, Dr. Deming many times said that the master chef is the person who knows no fear, and he was a master chef putting stuff together. And we would talk about fairly common knowledge that the great artists, the great thinkers, the great producers were doing it for themselves, it just happened that they had an audience. The music caught on, the poetry caught on, the painting caught on, the management system caught on. But we're doing it for ourselves with no fear. And that's the lesson.   0:51:11.8 Andrew Stotz: Yeah. Well, I hope that there's a 24-year-old out there right now listening to this just like I was, or think about back in 1972 when you were sitting there listening to his message. And they've caught that message from you today. So I appreciate it, and I want to say on behalf of everyone at the Deming Institute, of course, thank you so much for this discussion and for people who are listening and interested, remember to go to deming.org to continue your journey. And of course, you can reach Bill on LinkedIn, very simple. He's out there posting and he's responding. So feel free if you've got a question or comment or something, reach out to him on LinkedIn and have a discussion. This is your host, Andrew Stotz, and I'm going to leave you with one of my favorite quotes from Dr. Deming, and it doesn't change. It is, "people are entitled to joy in work."

When have you been so excited about something you just had to run and tell your best friend? What have you heard about that you really thought your friends ought to hear too, but weren't sure how to tell them?

In this episode of the HR Leaders Podcast, we sit down with David Sperl, Head of HR for Advanced Visualization Solutions at GE HealthCare, to unpack how HR earns real business credibility by shipping outcomes, not PowerPoints, inside a heavily regulated, science driven environment.David explains why AI literacy must move from theory to hands-on practice, how microlearning and shared baseline tools help drive adoption, and why leadership advocacy is essential to scale change across technical, clinical, and commercial teams. He breaks down GE HealthCare's four stages of AI adoption, how communities of practice create demand pull, and why unlearning outdated mental models is now harder than learning new ones.Most importantly, he shares why user experience and friction removal are the real unlocks for AI in HR and business, and why the future of change isn't “change management”, it's change agility.

Have you ever waited to hear from a friend who had moved to another city? Perhaps you heard about them from others, but waited anxiously to hear from them personally. Did you begin to doubt their friendship?

Have you ever waited to hear from a friend who had moved to another city? Perhaps you heard about them from others, but waited anxiously to hear from them personally. Did you begin to doubt their friendship?

don't miss George's AIE talk: https://www.youtube.com/watch?v=sRpqPgKeXNk —- From launching a side project in a Sydney basement to becoming the independent gold standard for AI benchmarking—trusted by developers, enterprises, and every major lab to navigate the exploding landscape of models, providers, and capabilities—George Cameron and Micah Hill-Smith have spent two years building Artificial Analysis into the platform that answers the questions no one else will: Which model is actually best for your use case? What are the real speed-cost trade-offs? And how open is "open" really? We discuss: The origin story: built as a side project in 2023 while Micah was building a legal AI assistant, launched publicly in January 2024, and went viral after Swyx's retweet Why they run evals themselves: labs prompt models differently, cherry-pick chain-of-thought examples (Google Gemini 1.0 Ultra used 32-shot prompts to beat GPT-4 on MMLU), and self-report inflated numbers The mystery shopper policy: they register accounts not on their own domain and run intelligence + performance benchmarks incognito to prevent labs from serving different models on private endpoints How they make money: enterprise benchmarking insights subscription (standardized reports on model deployment, serverless vs. managed vs. leasing chips) and private custom benchmarking for AI companies (no one pays to be on the public leaderboard) The Intelligence Index (V3): synthesizes 10 eval datasets (MMLU, GPQA, agentic benchmarks, long-context reasoning) into a single score, with 95% confidence intervals via repeated runs Omissions Index (hallucination rate): scores models from -100 to +100 (penalizing incorrect answers, rewarding "I don't know"), and Claude models lead with the lowest hallucination rates despite not always being the smartest GDP Val AA: their version of OpenAI's GDP-bench (44 white-collar tasks with spreadsheets, PDFs, PowerPoints), run through their Stirrup agent harness (up to 100 turns, code execution, web search, file system), graded by Gemini 3 Pro as an LLM judge (tested extensively, no self-preference bias) The Openness Index: scores models 0-18 on transparency of pre-training data, post-training data, methodology, training code, and licensing (AI2 OLMo 2 leads, followed by Nous Hermes and NVIDIA Nemotron) The smiling curve of AI costs: GPT-4-level intelligence is 100-1000x cheaper than at launch (thanks to smaller models like Amazon Nova), but frontier reasoning models in agentic workflows cost more than ever (sparsity, long context, multi-turn agents) Why sparsity might go way lower than 5%: GPT-4.5 is ~5% active, Gemini models might be ~3%, and Omissions Index accuracy correlates with total parameters (not active), suggesting massive sparse models are the future Token efficiency vs. turn efficiency: GPT-5 costs more per token but solves Tau-bench in fewer turns (cheaper overall), and models are getting better at using more tokens only when needed (5.1 Codex has tighter token distributions) V4 of the Intelligence Index coming soon: adding GDP Val AA, Critical Point, hallucination rate, and dropping some saturated benchmarks (human-eval-style coding is now trivial for small models) — Artificial Analysis Website: https://artificialanalysis.ai (https://artificialanalysis.ai ("https://artificialanalysis.ai")) George Cameron on X: https://x.com/grmcameron (https://x.com/grmcameron ("https://x.com/grmcameron")) Micah Hill-Smith on X: https://x.com/_micah_h (https://x.com/_micah_h ("https://x.com/_micah_h")) Chapters 00:00:00 Introduction: Full Circle Moment and Artificial Analysis Origins 00:01:08 Business Model: Independence and Revenue Streams 00:04:00 The Origin Story: From Legal AI to Benchmarking 00:07:00 Early Challenges: Cost, Methodology, and Independence 00:16:13 AI Grant and Moving to San Francisco 00:18:58 Evolution of the Intelligence Index: V1 to V3 00:27:55 New Benchmarks: Hallucination Rate and Omissions Index 00:33:19 Critical Point and Frontier Physics Problems 00:35:56 GDPVAL AA: Agentic Evaluation and Stirrup Harness 00:51:47 The Openness Index: Measuring Model Transparency 00:57:57 The Smiling Curve: Cost of Intelligence Paradox 01:04:00 Hardware Efficiency and Sparsity Trends 01:07:43 Reasoning vs Non-Reasoning: Token Efficiency Matters 01:10:47 Multimodal Benchmarking and Community Requests 01:14:50 Looking Ahead: V4 Intelligence Index and Beyond

Happy New Year! You may have noticed that in 2025 we had moved toward YouTube as our primary podcasting platform. As we'll explain in the next State of Latent Space post, we'll be doubling down on Substack again and improving the experience for the over 100,000 of you who look out for our emails and website updates!We first mentioned Artificial Analysis in 2024, when it was still a side project in a Sydney basement. They then were one of the few Nat Friedman and Daniel Gross' AIGrant companies to raise a full seed round from them and have now become the independent gold standard for AI benchmarking—trusted by developers, enterprises, and every major lab to navigate the exploding landscape of models, providers, and capabilities.We have chatted with both Clementine Fourrier of HuggingFace's OpenLLM Leaderboard and (the freshly valued at $1.7B) Anastasios Angelopoulos of LMArena on their approaches to LLM evals and trendspotting, but Artificial Analysis have staked out an enduring and important place in the toolkit of the modern AI Engineer by doing the best job of independently running the most comprehensive set of evals across the widest range of open and closed models, and charting their progress for broad industry analyst use.George Cameron and Micah-Hill Smith have spent two years building Artificial Analysis into the platform that answers the questions no one else will: Which model is actually best for your use case? What are the real speed-cost trade-offs? And how open is “open” really?We discuss:* The origin story: built as a side project in 2023 while Micah was building a legal AI assistant, launched publicly in January 2024, and went viral after Swyx's retweet* Why they run evals themselves: labs prompt models differently, cherry-pick chain-of-thought examples (Google Gemini 1.0 Ultra used 32-shot prompts to beat GPT-4 on MMLU), and self-report inflated numbers* The mystery shopper policy: they register accounts not on their own domain and run intelligence + performance benchmarks incognito to prevent labs from serving different models on private endpoints* How they make money: enterprise benchmarking insights subscription (standardized reports on model deployment, serverless vs. managed vs. leasing chips) and private custom benchmarking for AI companies (no one pays to be on the public leaderboard)* The Intelligence Index (V3): synthesizes 10 eval datasets (MMLU, GPQA, agentic benchmarks, long-context reasoning) into a single score, with 95% confidence intervals via repeated runs* Omissions Index (hallucination rate): scores models from -100 to +100 (penalizing incorrect answers, rewarding ”I don't know”), and Claude models lead with the lowest hallucination rates despite not always being the smartest* GDP Val AA: their version of OpenAI's GDP-bench (44 white-collar tasks with spreadsheets, PDFs, PowerPoints), run through their Stirrup agent harness (up to 100 turns, code execution, web search, file system), graded by Gemini 3 Pro as an LLM judge (tested extensively, no self-preference bias)* The Openness Index: scores models 0-18 on transparency of pre-training data, post-training data, methodology, training code, and licensing (AI2 OLMo 2 leads, followed by Nous Hermes and NVIDIA Nemotron)* The smiling curve of AI costs: GPT-4-level intelligence is 100-1000x cheaper than at launch (thanks to smaller models like Amazon Nova), but frontier reasoning models in agentic workflows cost more than ever (sparsity, long context, multi-turn agents)* Why sparsity might go way lower than 5%: GPT-4.5 is ~5% active, Gemini models might be ~3%, and Omissions Index accuracy correlates with total parameters (not active), suggesting massive sparse models are the future* Token efficiency vs. turn efficiency: GPT-5 costs more per token but solves Tau-bench in fewer turns (cheaper overall), and models are getting better at using more tokens only when needed (5.1 Codex has tighter token distributions)* V4 of the Intelligence Index coming soon: adding GDP Val AA, Critical Point, hallucination rate, and dropping some saturated benchmarks (human-eval-style coding is now trivial for small models)Links to Artificial Analysis* Website: https://artificialanalysis.ai* George Cameron on X: https://x.com/georgecameron* Micah-Hill Smith on X: https://x.com/micahhsmithFull Episode on YouTubeTimestamps* 00:00 Introduction: Full Circle Moment and Artificial Analysis Origins* 01:19 Business Model: Independence and Revenue Streams* 04:33 Origin Story: From Legal AI to Benchmarking Need* 16:22 AI Grant and Moving to San Francisco* 19:21 Intelligence Index Evolution: From V1 to V3* 11:47 Benchmarking Challenges: Variance, Contamination, and Methodology* 13:52 Mystery Shopper Policy and Maintaining Independence* 28:01 New Benchmarks: Omissions Index for Hallucination Detection* 33:36 Critical Point: Hard Physics Problems and Research-Level Reasoning* 23:01 GDP Val AA: Agentic Benchmark for Real Work Tasks* 50:19 Stirrup Agent Harness: Open Source Agentic Framework* 52:43 Openness Index: Measuring Model Transparency Beyond Licenses* 58:25 The Smiling Curve: Cost Falling While Spend Rising* 1:02:32 Hardware Efficiency: Blackwell Gains and Sparsity Limits* 1:06:23 Reasoning Models and Token Efficiency: The Spectrum Emerges* 1:11:00 Multimodal Benchmarking: Image, Video, and Speech Arenas* 1:15:05 Looking Ahead: Intelligence Index V4 and Future Directions* 1:16:50 Closing: The Insatiable Demand for IntelligenceTranscriptMicah [00:00:06]: This is kind of a full circle moment for us in a way, because the first time artificial analysis got mentioned on a podcast was you and Alessio on Latent Space. Amazing.swyx [00:00:17]: Which was January 2024. I don't even remember doing that, but yeah, it was very influential to me. Yeah, I'm looking at AI News for Jan 17, or Jan 16, 2024. I said, this gem of a models and host comparison site was just launched. And then I put in a few screenshots, and I said, it's an independent third party. It clearly outlines the quality versus throughput trade-off, and it breaks out by model and hosting provider. I did give you s**t for missing fireworks, and how do you have a model benchmarking thing without fireworks? But you had together, you had perplexity, and I think we just started chatting there. Welcome, George and Micah, to Latent Space. I've been following your progress. Congrats on... It's been an amazing year. You guys have really come together to be the presumptive new gardener of AI, right? Which is something that...George [00:01:09]: Yeah, but you can't pay us for better results.swyx [00:01:12]: Yes, exactly.George [00:01:13]: Very important.Micah [00:01:14]: Start off with a spicy take.swyx [00:01:18]: Okay, how do I pay you?Micah [00:01:20]: Let's get right into that.swyx [00:01:21]: How do you make money?Micah [00:01:24]: Well, very happy to talk about that. So it's been a big journey the last couple of years. Artificial analysis is going to be two years old in January 2026. Which is pretty soon now. We first run the website for free, obviously, and give away a ton of data to help developers and companies navigate AI and make decisions about models, providers, technologies across the AI stack for building stuff. We're very committed to doing that and tend to keep doing that. We have, along the way, built a business that is working out pretty sustainably. We've got just over 20 people now and two main customer groups. So we want to be... We want to be who enterprise look to for data and insights on AI, so we want to help them with their decisions about models and technologies for building stuff. And then on the other side, we do private benchmarking for companies throughout the AI stack who build AI stuff. So no one pays to be on the website. We've been very clear about that from the very start because there's no use doing what we do unless it's independent AI benchmarking. Yeah. But turns out a bunch of our stuff can be pretty useful to companies building AI stuff.swyx [00:02:38]: And is it like, I am a Fortune 500, I need advisors on objective analysis, and I call you guys and you pull up a custom report for me, you come into my office and give me a workshop? What kind of engagement is that?George [00:02:53]: So we have a benchmarking and insight subscription, which looks like standardized reports that cover key topics or key challenges enterprises face when looking to understand AI and choose between all the technologies. And so, for instance, one of the report is a model deployment report, how to think about choosing between serverless inference, managed deployment solutions, or leasing chips. And running inference yourself is an example kind of decision that big enterprises face, and it's hard to reason through, like this AI stuff is really new to everybody. And so we try and help with our reports and insight subscription. Companies navigate that. We also do custom private benchmarking. And so that's very different from the public benchmarking that we publicize, and there's no commercial model around that. For private benchmarking, we'll at times create benchmarks, run benchmarks to specs that enterprises want. And we'll also do that sometimes for AI companies who have built things, and we help them understand what they've built with private benchmarking. Yeah. So that's a piece mainly that we've developed through trying to support everybody publicly with our public benchmarks. Yeah.swyx [00:04:09]: Let's talk about TechStack behind that. But okay, I'm going to rewind all the way to when you guys started this project. You were all the way in Sydney? Yeah. Well, Sydney, Australia for me.Micah [00:04:19]: George was an SF, but he's Australian, but he moved here already. Yeah.swyx [00:04:22]: And I remember I had the Zoom call with you. What was the impetus for starting artificial analysis in the first place? You know, you started with public benchmarks. And so let's start there. We'll go to the private benchmark. Yeah.George [00:04:33]: Why don't we even go back a little bit to like why we, you know, thought that it was needed? Yeah.Micah [00:04:40]: The story kind of begins like in 2022, 2023, like both George and I have been into AI stuff for quite a while. In 2023 specifically, I was trying to build a legal AI research assistant. So it actually worked pretty well for its era, I would say. Yeah. Yeah. So I was finding that the more you go into building something using LLMs, the more each bit of what you're doing ends up being a benchmarking problem. So had like this multistage algorithm thing, trying to figure out what the minimum viable model for each bit was, trying to optimize every bit of it as you build that out, right? Like you're trying to think about accuracy, a bunch of other metrics and performance and cost. And mostly just no one was doing anything to independently evaluate all the models. And certainly not to look at the trade-offs for speed and cost. So we basically set out just to build a thing that developers could look at to see the trade-offs between all of those things measured independently across all the models and providers. Honestly, it was probably meant to be a side project when we first started doing it.swyx [00:05:49]: Like we didn't like get together and say like, Hey, like we're going to stop working on all this stuff. I'm like, this is going to be our main thing. When I first called you, I think you hadn't decided on starting a company yet.Micah [00:05:58]: That's actually true. I don't even think we'd pause like, like George had an acquittance job. I didn't quit working on my legal AI thing. Like it was genuinely a side project.George [00:06:05]: We built it because we needed it as people building in the space and thought, Oh, other people might find it useful too. So we'll buy domain and link it to the Vercel deployment that we had and tweet about it. And, but very quickly it started getting attention. Thank you, Swyx for, I think doing an initial retweet and spotlighting it there. This project that we released. And then very quickly though, it was useful to others, but very quickly it became more useful as the number of models released accelerated. We had Mixtrel 8x7B and it was a key. That's a fun one. Yeah. Like a open source model that really changed the landscape and opened up people's eyes to other serverless inference providers and thinking about speed, thinking about cost. And so that was a key. And so it became more useful quite quickly. Yeah.swyx [00:07:02]: What I love talking to people like you who sit across the ecosystem is, well, I have theories about what people want, but you have data and that's obviously more relevant. But I want to stay on the origin story a little bit more. When you started out, I would say, I think the status quo at the time was every paper would come out and they would report their numbers versus competitor numbers. And that's basically it. And I remember I did the legwork. I think everyone has some knowledge. I think there's some version of Excel sheet or a Google sheet where you just like copy and paste the numbers from every paper and just post it up there. And then sometimes they don't line up because they're independently run. And so your numbers are going to look better than... Your reproductions of other people's numbers are going to look worse because you don't hold their models correctly or whatever the excuse is. I think then Stanford Helm, Percy Liang's project would also have some of these numbers. And I don't know if there's any other source that you can cite. The way that if I were to start artificial analysis at the same time you guys started, I would have used the Luther AI's eval framework harness. Yup.Micah [00:08:06]: Yup. That was some cool stuff. At the end of the day, running these evals, it's like if it's a simple Q&A eval, all you're doing is asking a list of questions and checking if the answers are right, which shouldn't be that crazy. But it turns out there are an enormous number of things that you've got control for. And I mean, back when we started the website. Yeah. Yeah. Like one of the reasons why we realized that we had to run the evals ourselves and couldn't just take rules from the labs was just that they would all prompt the models differently. And when you're competing over a few points, then you can pretty easily get- You can put the answer into the model. Yeah. That in the extreme. And like you get crazy cases like back when I'm Googled a Gemini 1.0 Ultra and needed a number that would say it was better than GPT-4 and like constructed, I think never published like chain of thought examples. 32 of them in every topic in MLU to run it, to get the score, like there are so many things that you- They never shipped Ultra, right? That's the one that never made it up. Not widely. Yeah. Yeah. Yeah. I mean, I'm sure it existed, but yeah. So we were pretty sure that we needed to run them ourselves and just run them in the same way across all the models. Yeah. And we were, we also did certain from the start that you couldn't look at those in isolation. You needed to look at them alongside the cost and performance stuff. Yeah.swyx [00:09:24]: Okay. A couple of technical questions. I mean, so obviously I also thought about this and I didn't do it because of cost. Yep. Did you not worry about costs? Were you funded already? Clearly not, but you know. No. Well, we definitely weren't at the start.Micah [00:09:36]: So like, I mean, we're paying for it personally at the start. There's a lot of money. Well, the numbers weren't nearly as bad a couple of years ago. So we certainly incurred some costs, but we were probably in the order of like hundreds of dollars of spend across all the benchmarking that we were doing. Yeah. So nothing. Yeah. It was like kind of fine. Yeah. Yeah. These days that's gone up an enormous amount for a bunch of reasons that we can talk about. But yeah, it wasn't that bad because you can also remember that like the number of models we were dealing with was hardly any and the complexity of the stuff that we wanted to do to evaluate them was a lot less. Like we were just asking some Q&A type questions and then one specific thing was for a lot of evals initially, we were just like sampling an answer. You know, like, what's the answer for this? Like, we didn't want to go into the answer directly without letting the models think. We weren't even doing chain of thought stuff initially. And that was the most useful way to get some results initially. Yeah.swyx [00:10:33]: And so for people who haven't done this work, literally parsing the responses is a whole thing, right? Like because sometimes the models, the models can answer any way they feel fit and sometimes they actually do have the right answer, but they just returned the wrong format and they will get a zero for that unless you work it into your parser. And that involves more work. And so, I mean, but there's an open question whether you should give it points for not following your instructions on the format.Micah [00:11:00]: It depends what you're looking at, right? Because you can, if you're trying to see whether or not it can solve a particular type of reasoning problem, and you don't want to test it on its ability to do answer formatting at the same time, then you might want to use an LLM as answer extractor approach to make sure that you get the answer out no matter how unanswered. But these days, it's mostly less of a problem. Like, if you instruct a model and give it examples of what the answers should look like, it can get the answers in your format, and then you can do, like, a simple regex.swyx [00:11:28]: Yeah, yeah. And then there's other questions around, I guess, sometimes if you have a multiple choice question, sometimes there's a bias towards the first answer, so you have to randomize the responses. All these nuances, like, once you dig into benchmarks, you're like, I don't know how anyone believes the numbers on all these things. It's so dark magic.Micah [00:11:47]: You've also got, like… You've got, like, the different degrees of variance in different benchmarks, right? Yeah. So, if you run four-question multi-choice on a modern reasoning model at the temperatures suggested by the labs for their own models, the variance that you can see on a four-question multi-choice eval is pretty enormous if you only do a single run of it and it has a small number of questions, especially. So, like, one of the things that we do is run an enormous number of all of our evals when we're developing new ones and doing upgrades to our intelligence index to bring in new things. Yeah. So, that we can dial in the right number of repeats so that we can get to the 95% confidence intervals that we're comfortable with so that when we pull that together, we can be confident in intelligence index to at least as tight as, like, a plus or minus one at a 95% confidence. Yeah.swyx [00:12:32]: And, again, that just adds a straight multiple to the cost. Oh, yeah. Yeah, yeah.George [00:12:37]: So, that's one of many reasons that cost has gone up a lot more than linearly over the last couple of years. We report a cost to run the artificial analysis. We report a cost to run the artificial analysis intelligence index on our website, and currently that's assuming one repeat in terms of how we report it because we want to reflect a bit about the weighting of the index. But our cost is actually a lot higher than what we report there because of the repeats.swyx [00:13:03]: Yeah, yeah, yeah. And probably this is true, but just checking, you don't have any special deals with the labs. They don't discount it. You just pay out of pocket or out of your sort of customer funds. Oh, there is a mix. So, the issue is that sometimes they may give you a special end point, which is… Ah, 100%.Micah [00:13:21]: Yeah, yeah, yeah. Exactly. So, we laser focus, like, on everything we do on having the best independent metrics and making sure that no one can manipulate them in any way. There are quite a lot of processes we've developed over the last couple of years to make that true for, like, the one you bring up, like, right here of the fact that if we're working with a lab, if they're giving us a private endpoint to evaluate a model, that it is totally possible. That what's sitting behind that black box is not the same as they serve on a public endpoint. We're very aware of that. We have what we call a mystery shopper policy. And so, and we're totally transparent with all the labs we work with about this, that we will register accounts not on our own domain and run both intelligence evals and performance benchmarks… Yeah, that's the job. …without them being able to identify it. And no one's ever had a problem with that. Because, like, a thing that turns out to actually be quite a good… …good factor in the industry is that they all want to believe that none of their competitors could manipulate what we're doing either.swyx [00:14:23]: That's true. I never thought about that. I've been in the database data industry prior, and there's a lot of shenanigans around benchmarking, right? So I'm just kind of going through the mental laundry list. Did I miss anything else in this category of shenanigans? Oh, potential shenanigans.Micah [00:14:36]: I mean, okay, the biggest one, like, that I'll bring up, like, is more of a conceptual one, actually, than, like, direct shenanigans. It's that the things that get measured become things that get targeted by labs that they're trying to build, right? Exactly. So that doesn't mean anything that we should really call shenanigans. Like, I'm not talking about training on test set. But if you know that you're going to be great at another particular thing, if you're a researcher, there are a whole bunch of things that you can do to try to get better at that thing that preferably are going to be helpful for a wide range of how actual users want to use the thing that you're building. But will not necessarily work. Will not necessarily do that. So, for instance, the models are exceptional now at answering competition maths problems. There is some relevance of that type of reasoning, that type of work, to, like, how we might use modern coding agents and stuff. But it's clearly not one for one. So the thing that we have to be aware of is that once an eval becomes the thing that everyone's looking at, scores can get better on it without there being a reflection of overall generalized intelligence of these models. Getting better. That has been true for the last couple of years. It'll be true for the next couple of years. There's no silver bullet to defeat that other than building new stuff to stay relevant and measure the capabilities that matter most to real users. Yeah.swyx [00:15:58]: And we'll cover some of the new stuff that you guys are building as well, which is cool. Like, you used to just run other people's evals, but now you're coming up with your own. And I think, obviously, that is a necessary path once you're at the frontier. You've exhausted all the existing evals. I think the next point in history that I have for you is AI Grant that you guys decided to join and move here. What was it like? I think you were in, like, batch two? Batch four. Batch four. Okay.Micah [00:16:26]: I mean, it was great. Nat and Daniel are obviously great. And it's a really cool group of companies that we were in AI Grant alongside. It was really great to get Nat and Daniel on board. Obviously, they've done a whole lot of great work in the space with a lot of leading companies and were extremely aligned. With the mission of what we were trying to do. Like, we're not quite typical of, like, a lot of the other AI startups that they've invested in.swyx [00:16:53]: And they were very much here for the mission of what we want to do. Did they say any advice that really affected you in some way or, like, were one of the events very impactful? That's an interesting question.Micah [00:17:03]: I mean, I remember fondly a bunch of the speakers who came and did fireside chats at AI Grant.swyx [00:17:09]: Which is also, like, a crazy list. Yeah.George [00:17:11]: Oh, totally. Yeah, yeah, yeah. There was something about, you know, speaking to Nat and Daniel about the challenges of working through a startup and just working through the questions that don't have, like, clear answers and how to work through those kind of methodically and just, like, work through the hard decisions. And they've been great mentors to us as we've built artificial analysis. Another benefit for us was that other companies in the batch and other companies in AI Grant are pushing the capabilities. Yeah. And I think that's a big part of what AI can do at this time. And so being in contact with them, making sure that artificial analysis is useful to them has been fantastic for supporting us in working out how should we build out artificial analysis to continue to being useful to those, like, you know, building on AI.swyx [00:17:59]: I think to some extent, I'm mixed opinion on that one because to some extent, your target audience is not people in AI Grants who are obviously at the frontier. Yeah. Do you disagree?Micah [00:18:09]: To some extent. To some extent. But then, so a lot of what the AI Grant companies are doing is taking capabilities coming out of the labs and trying to push the limits of what they can do across the entire stack for building great applications, which actually makes some of them pretty archetypical power users of artificial analysis. Some of the people with the strongest opinions about what we're doing well and what we're not doing well and what they want to see next from us. Yeah. Yeah. Because when you're building any kind of AI application now, chances are you're using a whole bunch of different models. You're maybe switching reasonably frequently for different models and different parts of your application to optimize what you're able to do with them at an accuracy level and to get better speed and cost characteristics. So for many of them, no, they're like not commercial customers of ours, like we don't charge for all our data on the website. Yeah. They are absolutely some of our power users.swyx [00:19:07]: So let's talk about just the evals as well. So you start out from the general like MMU and GPQA stuff. What's next? How do you sort of build up to the overall index? What was in V1 and how did you evolve it? Okay.Micah [00:19:22]: So first, just like background, like we're talking about the artificial analysis intelligence index, which is our synthesis metric that we pulled together currently from 10 different eval data sets to give what? We're pretty much the same as that. Pretty confident is the best single number to look at for how smart the models are. Obviously, it doesn't tell the whole story. That's why we published the whole website of all the charts to dive into every part of it and look at the trade-offs. But best single number. So right now, it's got a bunch of Q&A type data sets that have been very important to the industry, like a couple that you just mentioned. It's also got a couple of agentic data sets. It's got our own long context reasoning data set and some other use case focused stuff. As time goes on. The things that we're most interested in that are going to be important to the capabilities that are becoming more important for AI, what developers are caring about, are going to be first around agentic capabilities. So surprise, surprise. We're all loving our coding agents and how the model is going to perform like that and then do similar things for different types of work are really important to us. The linking to use cases to economically valuable use cases are extremely important to us. And then we've got some of the. Yeah. These things that the models still struggle with, like working really well over long contexts that are not going to go away as specific capabilities and use cases that we need to keep evaluating.swyx [00:20:46]: But I guess one thing I was driving was like the V1 versus the V2 and how bad it was over time.Micah [00:20:53]: Like how we've changed the index to where we are.swyx [00:20:55]: And I think that reflects on the change in the industry. Right. So that's a nice way to tell that story.Micah [00:21:00]: Well, V1 would be completely saturated right now. Almost every model coming out because doing things like writing the Python functions and human evil is now pretty trivial. It's easy to forget, actually, I think how much progress has been made in the last two years. Like we obviously play the game constantly of like the today's version versus last week's version and the week before and all of the small changes in the horse race between the current frontier and who has the best like smaller than 10B model like right now this week. Right. And that's very important to a lot of developers and people and especially in this particular city of San Francisco. But when you zoom out a couple of years ago, literally most of what we were doing to evaluate the models then would all be 100% solved by even pretty small models today. And that's been one of the key things, by the way, that's driven down the cost of intelligence at every tier of intelligence. We can talk about more in a bit. So V1, V2, V3, we made things harder. We covered a wider range of use cases. And we tried to get closer to things developers care about as opposed to like just the Q&A type stuff that MMLU and GPQA represented. Yeah.swyx [00:22:12]: I don't know if you have anything to add there. Or we could just go right into showing people the benchmark and like looking around and asking questions about it. Yeah.Micah [00:22:21]: Let's do it. Okay. This would be a pretty good way to chat about a few of the new things we've launched recently. Yeah.George [00:22:26]: And I think a little bit about the direction that we want to take it. And we want to push benchmarks. Currently, the intelligence index and evals focus a lot on kind of raw intelligence. But we kind of want to diversify how we think about intelligence. And we can talk about it. But kind of new evals that we've kind of built and partnered on focus on topics like hallucination. And we've got a lot of topics that I think are not covered by the current eval set that should be. And so we want to bring that forth. But before we get into that.swyx [00:23:01]: And so for listeners, just as a timestamp, right now, number one is Gemini 3 Pro High. Then followed by Cloud Opus at 70. Just 5.1 high. You don't have 5.2 yet. And Kimi K2 Thinking. Wow. Still hanging in there. So those are the top four. That will date this podcast quickly. Yeah. Yeah. I mean, I love it. I love it. No, no. 100%. Look back this time next year and go, how cute. Yep.George [00:23:25]: Totally. A quick view of that is, okay, there's a lot. I love it. I love this chart. Yeah.Micah [00:23:30]: This is such a favorite, right? Yeah. And almost every talk that George or I give at conferences and stuff, we always put this one up first to just talk about situating where we are in this moment in history. This, I think, is the visual version of what I was saying before about the zooming out and remembering how much progress there's been. If we go back to just over a year ago, before 01, before Cloud Sonnet 3.5, we didn't have reasoning models or coding agents as a thing. And the game was very, very different. If we go back even a little bit before then, we're in the era where, when you look at this chart, open AI was untouchable for well over a year. And, I mean, you would remember that time period well of there being very open questions about whether or not AI was going to be competitive, like full stop, whether or not open AI would just run away with it, whether we would have a few frontier labs and no one else would really be able to do anything other than consume their APIs. I am quite happy overall that the world that we have ended up in is one where... Multi-model. Absolutely. And strictly more competitive every quarter over the last few years. Yeah. This year has been insane. Yeah.George [00:24:42]: You can see it. This chart with everything added is hard to read currently. There's so many dots on it, but I think it reflects a little bit what we felt, like how crazy it's been.swyx [00:24:54]: Why 14 as the default? Is that a manual choice? Because you've got service now in there that are less traditional names. Yeah.George [00:25:01]: It's models that we're kind of highlighting by default in our charts, in our intelligence index. Okay.swyx [00:25:07]: You just have a manually curated list of stuff.George [00:25:10]: Yeah, that's right. But something that I actually don't think every artificial analysis user knows is that you can customize our charts and choose what models are highlighted. Yeah. And so if we take off a few names, it gets a little easier to read.swyx [00:25:25]: Yeah, yeah. A little easier to read. Totally. Yeah. But I love that you can see the all one jump. Look at that. September 2024. And the DeepSeek jump. Yeah.George [00:25:34]: Which got close to OpenAI's leadership. They were so close. I think, yeah, we remember that moment. Around this time last year, actually.Micah [00:25:44]: Yeah, yeah, yeah. I agree. Yeah, well, a couple of weeks. It was Boxing Day in New Zealand when DeepSeek v3 came out. And we'd been tracking DeepSeek and a bunch of the other global players that were less known over the second half of 2024 and had run evals on the earlier ones and stuff. I very distinctly remember Boxing Day in New Zealand, because I was with family for Christmas and stuff, running the evals and getting back result by result on DeepSeek v3. So this was the first of their v3 architecture, the 671b MOE.Micah [00:26:19]: And we were very, very impressed. That was the moment where we were sure that DeepSeek was no longer just one of many players, but had jumped up to be a thing. The world really noticed when they followed that up with the RL working on top of v3 and R1 succeeding a few weeks later. But the groundwork for that absolutely was laid with just extremely strong base model, completely open weights that we had as the best open weights model. So, yeah, that's the thing that you really see in the game. But I think that we got a lot of good feedback on Boxing Day. us on Boxing Day last year.George [00:26:48]: Boxing Day is the day after Christmas for those not familiar.George [00:26:54]: I'm from Singapore.swyx [00:26:55]: A lot of us remember Boxing Day for a different reason, for the tsunami that happened. Oh, of course. Yeah, but that was a long time ago. So yeah. So this is the rough pitch of AAQI. Is it A-A-Q-I or A-A-I-I? I-I. Okay. Good memory, though.Micah [00:27:11]: I don't know. I'm not used to it. Once upon a time, we did call it Quality Index, and we would talk about quality, performance, and price, but we changed it to intelligence.George [00:27:20]: There's been a few naming changes. We added hardware benchmarking to the site, and so benchmarks at a kind of system level. And so then we changed our throughput metric to, we now call it output speed, and thenswyx [00:27:32]: throughput makes sense at a system level, so we took that name. Take me through more charts. What should people know? Obviously, the way you look at the site is probably different than how a beginner might look at it.Micah [00:27:42]: Yeah, that's fair. There's a lot of fun stuff to dive into. Maybe so we can hit past all the, like, we have lots and lots of emails and stuff. The interesting ones to talk about today that would be great to bring up are a few of our recent things, I think, that probably not many people will be familiar with yet. So first one of those is our omniscience index. So this one is a little bit different to most of the intelligence evils that we've run. We built it specifically to look at the embedded knowledge in the models and to test hallucination by looking at when the model doesn't know the answer, so not able to get it correct, what's its probability of saying, I don't know, or giving an incorrect answer. So the metric that we use for omniscience goes from negative 100 to positive 100. Because we're simply taking off a point if you give an incorrect answer to the question. We're pretty convinced that this is an example of where it makes most sense to do that, because it's strictly more helpful to say, I don't know, instead of giving a wrong answer to factual knowledge question. And one of our goals is to shift the incentive that evils create for models and the labs creating them to get higher scores. And almost every evil across all of AI up until this point, it's been graded by simple percentage correct as the main metric, the main thing that gets hyped. And so you should take a shot at everything. There's no incentive to say, I don't know. So we did that for this one here.swyx [00:29:22]: I think there's a general field of calibration as well, like the confidence in your answer versus the rightness of the answer. Yeah, we completely agree. Yeah. Yeah.George [00:29:31]: On that. And one reason that we didn't do that is because. Or put that into this index is that we think that the, the way to do that is not to ask the models how confident they are.swyx [00:29:43]: I don't know. Maybe it might be though. You put it like a JSON field, say, say confidence and maybe it spits out something. Yeah. You know, we have done a few evils podcasts over the, over the years. And when we did one with Clementine of hugging face, who maintains the open source leaderboard, and this was one of her top requests, which is some kind of hallucination slash lack of confidence calibration thing. And so, Hey, this is one of them.Micah [00:30:05]: And I mean, like anything that we do, it's not a perfect metric or the whole story of everything that you think about as hallucination. But yeah, it's pretty useful and has some interesting results. Like one of the things that we saw in the hallucination rate is that anthropics Claude models at the, the, the very left-hand side here with the lowest hallucination rates out of the models that we've evaluated amnesty is on. That is an interesting fact. I think it probably correlates with a lot of the previously, not really measured vibes stuff that people like about some of the Claude models. Is the dataset public or what's is it, is there a held out set? There's a hell of a set for this one. So we, we have published a public test set, but we we've only published 10% of it. The reason is that for this one here specifically, it would be very, very easy to like have data contamination because it is just factual knowledge questions. We would. We'll update it at a time to also prevent that, but with yeah, kept most of it held out so that we can keep it reliable for a long time. It leads us to a bunch of really cool things, including breakdown quite granularly by topic. And so we've got some of that disclosed on the website publicly right now, and there's lots more coming in terms of our ability to break out very specific topics. Yeah.swyx [00:31:23]: I would be interested. Let's, let's dwell a little bit on this hallucination one. I noticed that Haiku hallucinates less than Sonnet hallucinates less than Opus. And yeah. Would that be the other way around in a normal capability environments? I don't know. What's, what do you make of that?George [00:31:37]: One interesting aspect is that we've found that there's not really a, not a strong correlation between intelligence and hallucination, right? That's to say that the smarter the models are in a general sense, isn't correlated with their ability to, when they don't know something, say that they don't know. It's interesting that Gemini three pro preview was a big leap over here. Gemini 2.5. Flash and, and, and 2.5 pro, but, and if I add pro quickly here.swyx [00:32:07]: I bet pro's really good. Uh, actually no, I meant, I meant, uh, the GPT pros.George [00:32:12]: Oh yeah.swyx [00:32:13]: Cause GPT pros are rumored. We don't know for a fact that it's like eight runs and then with the LM judge on top. Yeah.George [00:32:20]: So we saw a big jump in, this is accuracy. So this is just percent that they get, uh, correct and Gemini three pro knew a lot more than the other models. And so big jump in accuracy. But relatively no change between the Google Gemini models, between releases. And the hallucination rate. Exactly. And so it's likely due to just kind of different post-training recipe, between the, the Claude models. Yeah.Micah [00:32:45]: Um, there's, there's driven this. Yeah. You can, uh, you can partially blame us and how we define intelligence having until now not defined hallucination as a negative in the way that we think about intelligence.swyx [00:32:56]: And so that's what we're changing. Uh, I know many smart people who are confidently incorrect.George [00:33:02]: Uh, look, look at that. That, that, that is very humans. Very true. And there's times and a place for that. I think our view is that hallucination rate makes sense in this context where it's around knowledge, but in many cases, people want the models to hallucinate, to have a go. Often that's the case in coding or when you're trying to generate newer ideas. One eval that we added to artificial analysis is, is, is critical point and it's really hard, uh, physics problems. Okay.swyx [00:33:32]: And is it sort of like a human eval type or something different or like a frontier math type?George [00:33:37]: It's not dissimilar to frontier frontier math. So these are kind of research questions that kind of academics in the physics physics world would be able to answer, but models really struggled to answer. So the top score here is not 9%.swyx [00:33:51]: And when the people that, that created this like Minway and, and, and actually off via who was kind of behind sweep and what organization is this? Oh, is this, it's Princeton.George [00:34:01]: Kind of range of academics from, from, uh, different academic institutions, really smart people. They talked about how they turn the models up in terms of the temperature as high temperature as they can, where they're trying to explore kind of new ideas in physics as a, as a thought partner, just because they, they want the models to hallucinate. Um, yeah, sometimes it's something new. Yeah, exactly.swyx [00:34:21]: Um, so not right in every situation, but, um, I think it makes sense, you know, to test hallucination in scenarios where it makes sense. Also, the obvious question is, uh, this is one of. Many that there is there, every lab has a system card that shows some kind of hallucination number, and you've chosen to not, uh, endorse that and you've made your own. And I think that's a, that's a choice. Um, totally in some sense, the rest of artificial analysis is public benchmarks that other people can independently rerun. You provide it as a service here. You have to fight the, well, who are we to, to like do this? And your, your answer is that we have a lot of customers and, you know, but like, I guess, how do you converge the individual?Micah [00:35:08]: I mean, I think, I think for hallucinations specifically, there are a bunch of different things that you might care about reasonably, and that you'd measure quite differently, like we've called this a amnesty and solutionation rate, not trying to declare the, like, it's humanity's last hallucination. You could, uh, you could have some interesting naming conventions and all this stuff. Um, the biggest picture answer to that. It's something that I actually wanted to mention. Just as George was explaining, critical point as well is, so as we go forward, we are building evals internally. We're partnering with academia and partnering with AI companies to build great evals. We have pretty strong views on, in various ways for different parts of the AI stack, where there are things that are not being measured well, or things that developers care about that should be measured more and better. And we intend to be doing that. We're not obsessed necessarily with that. Everything we do, we have to do entirely within our own team. Critical point. As a cool example of where we were a launch partner for it, working with academia, we've got some partnerships coming up with a couple of leading companies. Those ones, obviously we have to be careful with on some of the independent stuff, but with the right disclosure, like we're completely comfortable with that. A lot of the labs have released great data sets in the past that we've used to great success independently. And so it's between all of those techniques, we're going to be releasing more stuff in the future. Cool.swyx [00:36:26]: Let's cover the last couple. And then we'll, I want to talk about your trends analysis stuff, you know? Totally.Micah [00:36:31]: So that actually, I have one like little factoid on omniscience. If you go back up to accuracy on omniscience, an interesting thing about this accuracy metric is that it tracks more closely than anything else that we measure. The total parameter count of models makes a lot of sense intuitively, right? Because this is a knowledge eval. This is the pure knowledge metric. We're not looking at the index and the hallucination rate stuff that we think is much more about how the models are trained. This is just what facts did they recall? And yeah, it tracks parameter count extremely closely. Okay.swyx [00:37:05]: What's the rumored size of GPT-3 Pro? And to be clear, not confirmed for any official source, just rumors. But rumors do fly around. Rumors. I get, I hear all sorts of numbers. I don't know what to trust.Micah [00:37:17]: So if you, if you draw the line on omniscience accuracy versus total parameters, we've got all the open ways models, you can squint and see that likely the leading frontier models right now are quite a lot bigger than the ones that we're seeing right now. And the one trillion parameters that the open weights models cap out at, and the ones that we're looking at here, there's an interesting extra data point that Elon Musk revealed recently about XAI that for three trillion parameters for GROK 3 and 4, 6 trillion for GROK 5, but that's not out yet. Take those together, have a look. You might reasonably form a view that there's a pretty good chance that Gemini 3 Pro is bigger than that, that it could be in the 5 to 10 trillion parameters. To be clear, I have absolutely no idea, but just based on this chart, like that's where you would, you would land if you have a look at it. Yeah.swyx [00:38:07]: And to some extent, I actually kind of discourage people from guessing too much because what does it really matter? Like as long as they can serve it as a sustainable cost, that's about it. Like, yeah, totally.George [00:38:17]: They've also got different incentives in play compared to like open weights models who are thinking to supporting others in self-deployment for the labs who are doing inference at scale. It's I think less about total parameters in many cases. When thinking about inference costs and more around number of active parameters. And so there's a bit of an incentive towards larger sparser models. Agreed.Micah [00:38:38]: Understood. Yeah. Great. I mean, obviously if you're a developer or company using these things, not exactly as you say, it doesn't matter. You should be looking at all the different ways that we measure intelligence. You should be looking at cost to run index number and the different ways of thinking about token efficiency and cost efficiency based on the list prices, because that's all it matters.swyx [00:38:56]: It's not as good for the content creator rumor mill where I can say. Oh, GPT-4 is this small circle. Look at GPT-5 is this big circle. And then there used to be a thing for a while. Yeah.Micah [00:39:07]: But that is like on its own, actually a very interesting one, right? That is it just purely that chances are the last couple of years haven't seen a dramatic scaling up in the total size of these models. And so there's a lot of room to go up properly in total size of the models, especially with the upcoming hardware generations. Yes.swyx [00:39:29]: So, you know. Taking off my shitposting face for a minute. Yes. Yes. At the same time, I do feel like, you know, especially coming back from Europe, people do feel like Ilya is probably right that the paradigm is doesn't have many more orders of magnitude to scale out more. And therefore we need to start exploring at least a different path. GDPVal, I think it's like only like a month or so old. I was also very positive when it first came out. I actually talked to Tejo, who was the lead researcher on that. Oh, cool. And you have your own version.George [00:39:59]: It's a fantastic. It's a fantastic data set. Yeah.swyx [00:40:01]: And maybe it will recap for people who are still out of it. It's like 44 tasks based on some kind of GDP cutoff that's like meant to represent broad white collar work that is not just coding. Yeah.Micah [00:40:12]: Each of the tasks have a whole bunch of detailed instructions, some input files for a lot of them. It's within the 44 is divided into like two hundred and twenty two to five, maybe subtasks that are the level of that we run through the agenda. And yeah, they're really interesting. I will say that it doesn't. It doesn't necessarily capture like all the stuff that people do at work. No avail is perfect is always going to be more things to look at, largely because in order to make the tasks well enough to find that you can run them, they need to only have a handful of input files and very specific instructions for that task. And so I think the easiest way to think about them are that they're like quite hard take home exam tasks that you might do in an interview process.swyx [00:40:56]: Yeah, for listeners, it is not no longer like a long prompt. It is like, well, here's a zip file with like a spreadsheet or a PowerPoint deck or a PDF and go nuts and answer this question.George [00:41:06]: OpenAI released a great data set and they released a good paper which looks at performance across the different web chat bots on the data set. It's a great paper, encourage people to read it. What we've done is taken that data set and turned it into an eval that can be run on any model. So we created a reference agentic harness that can run. Run the models on the data set, and then we developed evaluator approach to compare outputs. That's kind of AI enabled, so it uses Gemini 3 Pro Preview to compare results, which we tested pretty comprehensively to ensure that it's aligned to human preferences. One data point there is that even as an evaluator, Gemini 3 Pro, interestingly, doesn't do actually that well. So that's kind of a good example of what we've done in GDPVal AA.swyx [00:42:01]: Yeah, the thing that you have to watch out for with LLM judge is self-preference that models usually prefer their own output, and in this case, it was not. Totally.Micah [00:42:08]: I think the way that we're thinking about the places where it makes sense to use an LLM as judge approach now, like quite different to some of the early LLM as judge stuff a couple of years ago, because some of that and MTV was a great project that was a good example of some of this a while ago was about judging conversations and like a lot of style type stuff. Here, we've got the task that the grader and grading model is doing is quite different to the task of taking the test. When you're taking the test, you've got all of the agentic tools you're working with, the code interpreter and web search, the file system to go through many, many turns to try to create the documents. Then on the other side, when we're grading it, we're running it through a pipeline to extract visual and text versions of the files and be able to provide that to Gemini, and we're providing the criteria for the task and getting it to pick which one more effectively meets the criteria of the task. Yeah. So we've got the task out of two potential outcomes. It turns out that we proved that it's just very, very good at getting that right, matched with human preference a lot of the time, because I think it's got the raw intelligence, but it's combined with the correct representation of the outputs, the fact that the outputs were created with an agentic task that is quite different to the way the grading model works, and we're comparing it against criteria, not just kind of zero shot trying to ask the model to pick which one is better.swyx [00:43:26]: Got it. Why is this an ELO? And not a percentage, like GDP-VAL?George [00:43:31]: So the outputs look like documents, and there's video outputs or audio outputs from some of the tasks. It has to make a video? Yeah, for some of the tasks. Some of the tasks.swyx [00:43:43]: What task is that?George [00:43:45]: I mean, it's in the data set. Like be a YouTuber? It's a marketing video.Micah [00:43:49]: Oh, wow. What? Like model has to go find clips on the internet and try to put it together. The models are not that good at doing that one, for now, to be clear. It's pretty hard to do that with a code editor. I mean, the computer stuff doesn't work quite well enough and so on and so on, but yeah.George [00:44:02]: And so there's no kind of ground truth, necessarily, to compare against, to work out percentage correct. It's hard to come up with correct or incorrect there. And so it's on a relative basis. And so we use an ELO approach to compare outputs from each of the models between the task.swyx [00:44:23]: You know what you should do? You should pay a contractor, a human, to do the same task. And then give it an ELO and then so you have, you have human there. It's just, I think what's helpful about GDPVal, the OpenAI one, is that 50% is meant to be normal human and maybe Domain Expert is higher than that, but 50% was the bar for like, well, if you've crossed 50, you are superhuman. Yeah.Micah [00:44:47]: So we like, haven't grounded this score in that exactly. I agree that it can be helpful, but we wanted to generalize this to a very large number. It's one of the reasons that presenting it as ELO is quite helpful and allows us to add models and it'll stay relevant for quite a long time. I also think it, it can be tricky looking at these exact tasks compared to the human performance, because the way that you would go about it as a human is quite different to how the models would go about it. Yeah.swyx [00:45:15]: I also liked that you included Lama 4 Maverick in there. Is that like just one last, like...Micah [00:45:20]: Well, no, no, no, no, no, no, it is the, it is the best model released by Meta. And... So it makes it into the homepage default set, still for now.George [00:45:31]: Other inclusion that's quite interesting is we also ran it across the latest versions of the web chatbots. And so we have...swyx [00:45:39]: Oh, that's right.George [00:45:40]: Oh, sorry.swyx [00:45:41]: I, yeah, I completely missed that. Okay.George [00:45:43]: No, not at all. So that, which has a checkered pattern. So that is their harness, not yours, is what you're saying. Exactly. And what's really interesting is that if you compare, for instance, Claude 4.5 Opus using the Claude web chatbot, it performs worse than the model in our agentic harness. And so in every case, the model performs better in our agentic harness than its web chatbot counterpart, the harness that they created.swyx [00:46:13]: Oh, my backwards explanation for that would be that, well, it's meant for consumer use cases and here you're pushing it for something.Micah [00:46:19]: The constraints are different and the amount of freedom that you can give the model is different. Also, you like have a cost goal. We let the models work as long as they want, basically. Yeah. Do you copy paste manually into the chatbot? Yeah. Yeah. That's, that was how we got the chatbot reference. We're not going to be keeping those updated at like quite the same scale as hundreds of models.swyx [00:46:38]: Well, so I don't know, talk to a browser base. They'll, they'll automate it for you. You know, like I have thought about like, well, we should turn these chatbot versions into an API because they are legitimately different agents in themselves. Yes. Right. Yeah.Micah [00:46:53]: And that's grown a huge amount of the last year, right? Like the tools. The tools that are available have actually diverged in my opinion, a fair bit across the major chatbot apps and the amount of data sources that you can connect them to have gone up a lot, meaning that your experience and the way you're using the model is more different than ever.swyx [00:47:10]: What tools and what data connections come to mind when you say what's interesting, what's notable work that people have done?Micah [00:47:15]: Oh, okay. So my favorite example on this is that until very recently, I would argue that it was basically impossible to get an LLM to draft an email for me in any useful way. Because most times that you're sending an email, you're not just writing something for the sake of writing it. Chances are context required is a whole bunch of historical emails. Maybe it's notes that you've made, maybe it's meeting notes, maybe it's, um, pulling something from your, um, any of like wherever you at work store stuff. So for me, like Google drive, one drive, um, in our super base databases, if we need to do some analysis or some data or something, preferably model can be plugged into all of those things and can go do some useful work based on it. The things that like I find most impressive currently that I am somewhat surprised work really well in late 2025, uh, that I can have models use super base MCP to query read only, of course, run a whole bunch of SQL queries to do pretty significant data analysis. And. And make charts and stuff and can read my Gmail and my notion. And okay. You actually use that. That's good. That's, that's, that's good. Is that a cloud thing? To various degrees of order, but chat GPD and Claude right now, I would say that this stuff like barely works in fairness right now. Like.George [00:48:33]: Because people are actually going to try this after they hear it. If you get an email from Micah, odds are it wasn't written by a chatbot.Micah [00:48:38]: So, yeah, I think it is true that I have never actually sent anyone an email drafted by a chatbot. Yet.swyx [00:48:46]: Um, and so you can, you can feel it right. And yeah, this time, this time next year, we'll come back and see where it's going. Totally. Um, super base shout out another famous Kiwi. Uh, I don't know if you've, you've any conversations with him about anything in particular on AI building and AI infra.George [00:49:03]: We have had, uh, Twitter DMS, um, with, with him because we're quite big, uh, super base users and power users. And we probably do some things more manually than we should in. In, in super base support line because you're, you're a little bit being super friendly. One extra, um, point regarding, um, GDP Val AA is that on the basis of the overperformance of the models compared to the chatbots turns out, we realized that, oh, like our reference harness that we built actually white works quite well on like gen generalist agentic tasks. This proves it in a sense. And so the agent harness is very. Minimalist. I think it follows some of the ideas that are in Claude code and we, all that we give it is context management capabilities, a web search, web browsing, uh, tool, uh, code execution, uh, environment. Anything else?Micah [00:50:02]: I mean, we can equip it with more tools, but like by default, yeah, that's it. We, we, we give it for GDP, a tool to, uh, view an image specifically, um, because the models, you know, can just use a terminal to pull stuff in text form into context. But to pull visual stuff into context, we had to give them a custom tool, but yeah, exactly. Um, you, you can explain an expert. No.George [00:50:21]: So it's, it, we turned out that we created a good generalist agentic harness. And so we, um, released that on, on GitHub yesterday. It's called stirrup. So if people want to check it out and, and it's a great, um, you know, base for, you know, generalist, uh, building a generalist agent for more specific tasks.Micah [00:50:39]: I'd say the best way to use it is get clone and then have your favorite coding. Agent make changes to it, to do whatever you want, because it's not that many lines of code and the coding agents can work with it. Super well.swyx [00:50:51]: Well, that's nice for the community to explore and share and hack on it. I think maybe in, in, in other similar environments, the terminal bench guys have done, uh, sort of the Harbor. Uh, and so it's, it's a, it's a bundle of, well, we need our minimal harness, which for them is terminus and we also need the RL environments or Docker deployment thing to, to run independently. So I don't know if you've looked at it. I don't know if you've looked at the harbor at all, is that, is that like a, a standard that people want to adopt?George [00:51:19]: Yeah, we've looked at it from a evals perspective and we love terminal bench and, and host benchmarks of, of, of terminal mention on artificial analysis. Um, we've looked at it from a, from a coding agent perspective, but could see it being a great, um, basis for any kind of agents. I think where we're getting to is that these models have gotten smart enough. They've gotten better, better tools that they can perform better when just given a minimalist. Set of tools and, and let them run, let the model control the, the agentic workflow rather than using another framework that's a bit more built out that tries to dictate the, dictate the flow. Awesome.swyx [00:51:56]: Let's cover the openness index and then let's go into the report stuff. Uh, so that's the, that's the last of the proprietary art numbers, I guess. I don't know how you sort of classify all these. Yeah.Micah [00:52:07]: Or call it, call it, let's call it the last of like the, the three new things that we're talking about from like the last few weeks. Um, cause I mean, there's a, we do a mix of stuff that. Where we're using open source, where we open source and what we do and, um, proprietary stuff that we don't always open source, like long context reasoning data set last year, we did open source. Um, and then all of the work on performance benchmarks across the site, some of them, we looking to open source, but some of them, like we're constantly iterating on and so on and so on and so on. So there's a huge mix, I would say, just of like stuff that is open source and not across the side. So that's a LCR for people. Yeah, yeah, yeah, yeah.swyx [00:52:41]: Uh, but let's, let's, let's talk about open.Micah [00:52:42]: Let's talk about openness index. This. Here is call it like a new way to think about how open models are. We, for a long time, have tracked where the models are open weights and what the licenses on them are. And that's like pretty useful. That tells you what you're allowed to do with the weights of a model, but there is this whole other dimension to how open models are. That is pretty important that we haven't tracked until now. And that's how much is disclosed about how it was made. So transparency about data, pre-training data and post-training data. And whether you're allowed to use that data and transparency about methodology and training code. So basically, those are the components. We bring them together to score an openness index for models so that you can in one place get this full picture of how open models are.swyx [00:53:32]: I feel like I've seen a couple other people try to do this, but they're not maintained. I do think this does matter. I don't know what the numbers mean apart from is there a max number? Is this out of 20?George [00:53:44]: It's out of 18 currently, and so we've got an openness index page, but essentially these are points, you get points for being more open across these different categories and the maximum you can achieve is 18. So AI2 with their extremely open OMO3 32B think model is the leader in a sense.swyx [00:54:04]: It's hooking face.George [00:54:05]: Oh, with their smaller model. It's coming soon. I think we need to run, we need to get the intelligence benchmarks right to get it on the site.swyx [00:54:12]: You can't have it open in the next. We can not include hooking face. We love hooking face. We'll have that, we'll have that up very soon. I mean, you know, the refined web and all that stuff. It's, it's amazing. Or is it called fine web? Fine web. Fine web.Micah [00:54:23]: Yeah, yeah, no, totally. Yep. One of the reasons this is cool, right, is that if you're trying to understand the holistic picture of the models and what you can do with all the stuff the company's contributing, this gives you that picture. And so we are going to keep it up to date alongside all the models that we do intelligence index on, on the site. And it's just an extra view to understand.swyx [00:54:43]: Can you scroll down to this? The, the, the, the trade-offs chart. Yeah, yeah. That one. Yeah. This, this really matters, right? Obviously, because you can b

Carmela Then: When Remote Teams Stop Listening—The Silent Killer of Agile Collaboration Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: http://bit.ly/SMTP_ShowNotes.   "Two minutes into it, my mind's starting to wander and I started to do my own thing." - Carmela Then   Carmela paints a vivid picture of a distributed team stretched across Sydney, New Zealand, India, and beyond—a team where communication had quietly become the enemy of progress. The warning signs were subtle at first: in meetings with 20 people on the call, only two or three would speak for the entire hour or two, with no visual aids, no PowerPoints, no drawings. The result? Within minutes, attention drifted, and everyone assumed someone else understood the message.  The speakers believed their ideas had landed; the listeners had already tuned out. This miscommunication compounded sprint after sprint until, just two months before go-live, the team was still discussing proof of concept. Trust eroded completely, and the Product Owner resorted to micromanagement—tracking developers by the hour, turning what was supposed to be an Agile team into a waterfall nightmare. Carmela points to a critical missing element: the Scrum Master had been assigned delivery management duties, leaving no one to address the communication dysfunction.  The lesson is clear—in remote, cross-cultural teams, you cannot simply talk your way through complex ideas; you need visual anchors, shared artifacts, and constant verification that understanding has truly been achieved.   In this segment, we talk about the importance of visual communication in remote teams and psychological safety.   Self-reflection Question: How do you verify that your message has truly landed with every team member, especially when working across time zones and cultures? Featured Book of the Week: How to Win Friends and Influence People by Dale Carnegie Carmela recommends How to Win Friends and Influence People by Dale Carnegie, a timeless classic that remains essential reading for every Scrum Master. As Carmela explains, "We work with people—customers are people, and our team, they are human beings as well. Whether we want it or not, we are leaders, we are coaches, and sometimes we could even be mentors." Written during the Great Depression and predating software entirely, this book emphasizes that relationships and understanding people are the foundation of personal and professional success. Carmela was first introduced to the book by a successful person outside of work who advised her not just to read it once, but to revisit it every year. For Scrum Masters navigating team dynamics, stakeholder relationships, and the human side of Agile, Carnegie's principles remain as relevant today as they were nearly a century ago.   [The Scrum Master Toolbox Podcast Recommends]

Imagine what John the Baptist might have said to share the reason for his simple lifestyle with someone your age.

HHave you ever been confused over what someone was trying to say? It sounded important. It sounded right, but you just needed to think about it for a while. Imagine a young man asking John the Baptist about his message.

Was passiert mit einer KI, wenn niemand mit ihr chattet? Kann mein Chatbot endlich ordentliche PowerPoints? Und warum schreibt meine KI plötzlich auf Arabisch? Gregor, Fritz und Marie packen eure Fragen aus dem Jahr 2025 aus.

Bill George, former CEO of Medtronic and Harvard Business School Executive Fellow, explains how leaders can stay grounded, principled, and effective in chaotic times. "It's a world of chaos and it requires a very different kind of leader than in more stable times." The skills that once mattered (process control, long-term plans) are now secondary to courage, self-awareness, and moral clarity. George says most executives still lead comfortably "inside the walls" but fear the external world (media, public scrutiny, and rapid change). "Today, if you're a leader, you are a public figure. You have to face that reality." Leadership now starts with knowing your True North, your values and principles. "When everything's going your way, you start to think you're better than you are. When you lose, you learn your weaknesses." He warns: "The people who will struggle are those faking it to make it. They're trying to impress the outside world but aren't grounded inside." Purpose, not position, defines identity. "A CEO once said, 'Without a title, I'm nothing.' You won't hold that title forever. Who are you then?" True fulfillment comes from alignment between personal purpose and work. "Every business has a deep sense of purpose if it's well run. The ones that only make money, like GE, go away." He lists five traits of leaders who thrive in crisis: Face reality. Stay true to values. Adapt strategies fast. Engage your team. Go on offense when others retreat. Each requires courage. "You can't teach courage in a classroom. It has to come from within." He urges humility: "Leadership is all about relationships, it's a two-way street." His turning point came when he stopped "building a résumé" and started building people. He defines authentic leadership as growth through feedback: "I never walk into a classroom unless I'm going to learn from everyone there." And he closes with the core message: "You don't have to be CEO. If you can do great work and help others, you'll feel fulfilled. Leaders make the difference between success and failure."   Key Insights (Verbatim Quotes) 1. Chaos demands a new kind of leader. "It's a world of chaos and it requires a very different kind of leader than in more stable times." 2. Authenticity starts with grounding. "Our true north is our principles, our beliefs, and our values all rolled into one." 3. Titles are temporary. "I am not the CEO of Best Buy. …That's the title I hold. I won't hold that forever." 4. Courage separates real leaders. "You can't teach courage in a classroom. It has to come from within." 5. Purpose drives resilience. "Every business has a deep sense of purpose if it's well run." 6. Leadership is relational. "I was building a résumé, not relationships. Leadership is all about relationships." 7. Fear destroys authenticity. "A lot of people are living in fear. That's no way to live your life." 8. Great leaders empower others. "You want everyone on your team to be better than you are at what they do." 9. Growth never ends. "Anyone who's authentic knows they have to continue to grow as a human being." 10. True success is internal. "You'll never have enough power, fame, or money. You find fulfillment within."   Action Items "Face reality, starting with yourself." Look in the mirror and ask, "Maybe I'm creating this negative culture. What did I do wrong?" "Stay true to your purpose and your values." Never abandon principles when pressure rises. "Adapt your strategies and tactics." What worked yesterday may not work today. "Get your team involved." Say, "Hey guys, we've got a real problem. What ideas do you have to keep it going?" "Go on offense when everyone else is pulling back." Make bold moves when others retreat. "Have the courage to look yourself in the mirror." Courage starts with self-reflection. Ask, "What's the worst case? What do I have to lose?" and move forward without fear. "If one door closes, maybe another one's going to open that I never even saw." "Know who you are." Reflect on your life story, relationships, and crucibles that shaped you. "Don't get caught up in titles or money." Remember, "Without a title I'm nothing" leads nowhere. "Find a congruence between your purpose and the organization's purpose." "Every business has a deep sense of purpose if it's well run." Identify how yours helps people. "Get away from toxic leaders." If they drive you down, take credit for your work, or never support you, move on. "Work for people you feel really good about working with." "Learn all aspects of the business and how to integrate them creatively." "Pull together a cross-disciplinary team" and act as the integrator. "Have everyone on your team be better than you are at what they do." "Be the glue." Integrate experts to solve tough problems. "Care about your people first." They must know you care before they'll perform. "Get everyone into their sweet spot" — where they use all their skills and are highly motivated. "Align everyone around purpose and goals." "Challenge people to reach their full potential." Say, "I know you can do better. Let's take your game to the next level." "Get out there and be with the people." Don't hide behind PowerPoints. "Help your people do better." Work beside them. "Believe in someone who doesn't believe in themselves." Tell them, "You have this potential. Go for it." "Find someone who believes in you." A mentor, boss, or spouse who sees your potential. "As a leader, be that person who believes in others." "Face your blind spots." Ask people who care about you for honest feedback. "If you get feedback from people that care about you, take it in." "Stop building a résumé and start building relationships." "Take time for people. Ask, 'How are you doing today? What challenges are you facing?'" "Leadership is all about relationships — it's a two-way street." "Tell the truth — the good, the bad, and the ugly." "Stay away from blame." Take responsibility instead of pointing fingers. "Be transparent." Don't hide problems; fix them. "Never fake it to make it." "Keep growing as a human being." "Take feedback and adapt." Growth requires awareness of impact on others. "Believe in yourself even if you fail." Failure is learning. "Spend time reflecting on your purpose and the person you are becoming." "Help other people reach their full potential." "Measure success by how many people you help every day." "Remember: leadership is about who you are, not what title you hold." Get Bills book, True North, here: https://shorturl.at/bRXsK Claim your free gift: Free gift #1 McKinsey & BCG winning resume www.FIRMSconsulting.com/resumePDF Free gift #2 Breakthrough Decisions Guide with 25 AI Prompts www.FIRMSconsulting.com/decisions Free gift #3 Five Reasons Why People Ignore Somebody www.FIRMSconsulting.com/owntheroom Free gift #4 Access episode 1 from Build a Consulting Firm, Level 1 www.FIRMSconsulting.com/build Free gift #5 The Overall Approach used in well-managed strategy studies www.FIRMSconsulting.com/OverallApproach Free gift #6 Get a copy of Nine Leaders in Action, a book we co-authored with some of our clients: www.FIRMSconsulting.com/gift    

Send us a textPeaches and Trent roll into another beautifully unprepared episode packed with humor, straight talk, and real military insight. From the Okinawa body-slam everyone argues about to actually useful Air Force leadership lessons, fan-mail adventures, pipeline expectations, and what young candidates should really learn before joining Special Warfare, the guys keep it light, honest, and genuinely helpful. If you want a mix of Air Force culture, Special Warfare mindset, leadership truth bombs, and a laugh or two, this one delivers without the negativity spiral.⏱️ TIMESTAMPS00:00 Zero prep, full personality 02:00 OTS updates and gear that actually works 04:20 Fan mail roulette: from wholesome to wild 09:00 Waivers, pipelines, and realistic expectations 13:00 Life skills every future operator should master 16:30 Why commanders get roasted (and the reality behind it) 22:00 Chiefs, officers, and the leadership lessons nobody teaches 26:00 Okinawa body-slam drama — what matters and what doesn't 33:00 SOFA agreements and overseas military life 39:00 LSCO talk without panic or PowerPoints 44:00 NCO Corps: how to lead without being needy 53:00 GWOT nostalgia and lessons for the next generation 58:00 Commander's intent vs permission culture 01:04:00 LEDs, merch, and Peaches campaigning for a fresh SR shirt

Are you secretly applying for jobs you're overqualified for because you think it's your only option? In this raw, unfiltered episode recorded at 5am, I'm saying the thing that might trigger some people, but needs to be said.I'm calling out the posts on LinkedIn where people are defending why they should be considered for lower-level roles, and why fighting for your limitations is keeping you stuck. Your brain wants certainty so badly that it's convinced you taking scraps is the "realistic" choice. But here's what I know after coaching hundreds of people: when you can't even get the job you're overqualified for, it's not because the market is impossible, it's because you're trying to solve the wrong problem.I share the story of a client who thought he "just put together some PowerPoints" (spoiler: he didn't), why employers' concerns about overqualified candidates are actually valid, and the harsh truth about what skills you're missing that worked fine 20 years ago but don't cut it now. If you're tired of shrinking yourself and ready to learn what actually works, this episode won't coddle you, but it will show you the way forward.Watch the free training, How to Finally Value Yourself and Get Paid What You Deserve in 2026: https://www.asknataliefisher.com/workshop-2026Get full show notes and more information here: https://www.asknataliefisher.com/episode-260

A piano recital, public speaking, jumping off the high dive at a pool. Do these things make you think of sweaty palms and butterfly stomachs? We all have to take risks sometimes. But Jesus took the greatest risk of all.

Steve Sullivan joins me for a lively conversation about podcasting, tutor videos, and digital A&P teaching. We explore how he humanizes online learning, why students crave multiple approaches, and what he's learned after 23 years of teaching. From LMS-independent course design to global podcast reach, Steve shares practical strategies and inspiring stories that can help any A&P instructor evolve their teaching. 0:00:00 | Introduction 0:00:49 | This Episode 0:02:28 | Becoming Steve Sullivan 0:06:41 | Your Teaching Voice* 0:07:30 | Why Start a Podcast? 0:14:03 | Farewell to TAPP ed* 0:15:45 | Growing a Podcast & Growing Through It 0:19:56 | Authors Alert * 0:21:05 | Digital Teaching That Actually Helps 0:30:59 | When Our Tools Disappear* 0:32:48 | A&P Tools That Fit Any Textbook 0:48:36 | Collaboration Audit* 0:49:14 | What 23 Years of A&P Reveals 1:01:10 | Innovation Check * 1:01:44 | Staying Connected * Breaks ★ If you cannot see or activate the audio player, go to: theAPprofessor.org/podcast-episode-156.html ❓ Please take the anonymous survey: theAPprofessor.org/survey ☝️ Questions & Feedback: 1-833-LION-DEN (1-833-546-6336)

Welcome to 30 Tips in 30 Days! Over the entire month of November, I will be releasing a short, bite sized episode of Fearless Presentations every morning covering things that are absolutely essential to being a better presenter. Whether you've been speaking professionally for years and years or are looking to just start your public speaking journey, applying just these 30 tips I cover here will instantly and easily make you improve as a speaker. This does not mean you shouldn't use slideshows or PowerPoints. They are still the standard for a reason. But they are also not the only form of visual aid that works at conveying your presentation to people in the audience.Mixing it up with things like posters boards, props, samples, handouts, or videos can spice things up a bit and, in many cases, are actually better than just going with the safe slideshow.Show Notes: 101 Public Speaking Tips For Delivering Your Best Speech(https://www.fearlesspresentations.com/101-public-speaking-tips-for-delivering-your-best-speech/)

#310st for 14th November, 2025 or 3311! (33-Oh-Leven, not Oh-Eleven, OH-Leven)http://loosescrewsed.comJoin us on discord! And check out the merch store! PROMO CODEShttps://discord.gg/3Vfap47ReaSupport us on Patreon: https://www.patreon.com/LooseScrewsEDSquad Update:  (Updated by Bloom 10/16)Busted in old and fun ways. Come join us colonizing, BGS works out here.Ish. So does the colonizing.Ish.PowerPlay Update: - (unashamedly copied from KrugerFive's post in our Discord, 11/13)Cycle 54:Soontil relics hit 600t supply this cycle and the powers jumped on to boom for huge gains. Last relics rush was 14 cycles ago.The power of princess Aisling showed with the relics rush. +138 new systems, +8 new fortifieds.The other powers to maximize this were Yong-Rui (+73 systems), Antal (+70), and Mahon (+60)Delaine putting up a fight and keeping Torval behind for now (-3 systems difference)This relic boom creates a nice battle in the FDev board between Archer, Antal, and Kaine for Archer's P6. Archer 1131 systemsKaine 1100 systemsAntal 1089 systems1t trading is gone, trade is next to useless for control points, and relics are back down (but still at a healthy 120t). Next week is going to be interesting.Kruger 5's Power Rankings - https://k5elite.com/ Niceygy's Power Points - https://elite.niceygy.net/powerpointsFind out more in the LSN-powerplay-hub forum channel.Dev News: HIP 87621 Permit issuedCG - HIP 87621 Exobiology Initiative beginsPilots can support this initiative by first signing up at Exogene Sciences in the HIP 87621 system, before gathering samples of the newly discovered flora at biological sites located on several bodies of the HIP 87621 system. These samples must then be sold to Vista Genomics at Exogene Sciences, via the representative located in the station concourse.Pilots who register at least 1 sample will receive the following rewards:- Artemis Photon Blue Suit Pack- Credits, depending on success tier achieved and individual contribution level.Pilots in the top 75% and above of contributions will receive a grade 5 Artemis suit, with Improved Battery Capacity, Night Vision, Increased Sprint Duration and Improved Jump Assist modifications.Careful, it's hot out thereColonization main starport effects nerfed, then retracted, a bit. Lots of people apparently (cynically) think it's so FDev can sell more Dodec's…?Galnet News: https://community.elitedangerous.com/ (updated 11/14)Pilots' Federation Members Enter HIP 87621Trailblazer Fleet WithdrawnDiscussion:HIP 87621 bio's, CG, leading to?

How would you feel if your family planned to move to a place where you had never been before? Scared, excited, or both? This week we'll learn about some people who made a big move during the time of Ezra and Nehemiah.

#309th  for 5th November, 2025 or 3311! (33-Oh-Leven, not Oh-Eleven, OH-Leven)http://loosescrewsed.comJoin us on discord! And check out the merch store! PROMO CODEShttps://discord.gg/3Vfap47ReaSupport us on Patreon: https://www.patreon.com/LooseScrewsEDSquad Update:  (Updated by Bloom 10/16)Busted in old and fun ways. Come join us colonizing, BGS works out here.Ish. So does the colonizingPowerPlay Update: - (unashamedly copied from KrugerFive's post in our Discord, 10/30)Cycle 52: we are 1 day ahead of the cycle so… no updateKruger 5's Power Rankings - https://k5elite.com/ Niceygy's Power Points - https://elite.niceygy.net/powerpointsFind out more in the LSN-powerplay-hub forum channel.Dev News: Elite Dangerous | Developer Log - 4 November 2025Galnet News: https://community.elitedangerous.com/ (updated 10/23)Trailblazer Fleet To Be WithdrawnDiscussion:New Video StyleTrailblazers out of beta on 11 November Significant amount of fixes and QoL to BGS, PP, and ColonizationBalance pass for on-foot combatNew star port - Dodec station - Tier 3+ Available at the 11Nov updateTech broker, higher stats all around50k ARX to unlock per account, deploy one instantly where allowed, and then build others as normalNew ship - Zorgon Caspian Explorer - early access in DecemberLarge padCan load mk2 modulesIncluding new MK2 FSD with improved neutron superchargingRetracting engine bitsSmall landing footprintSaid something about “mind that gravity and spot interesting plating pattern on hull”New feature pushed to early 2026 - OperationsNew set of multi-phased scenariosOn foot and in space4 CMDRs take on a challenging obstacleNever seen before areas - internals of hostile megashipMultiple operations, varying difficultyRewards that are difficult to obtain

“Stories build trust faster than any strategy deck ever could.”In this episode of Business is Human, Rebecca Fleetwood Hession shares how she designed her signature event “Stand Tall in Your Story” to foster genuine human connection through neuroscience-backed storytelling. She explores why traditional business gatherings often miss the mark and how emotional, story-centered experiences can transform relationships between colleagues, clients, and communities. Rebecca offers practical takeaways for leaders looking to make meetings, events, and company retreats more meaningful by trading PowerPoints for purpose and conversation for connection.In this episode, you'll learn:How storytelling triggers trust-building chemicals like oxytocin and strengthens relationships faster than facts or data aloneWhy emotional shared experiences create psychological safety and lasting engagement within teams and client groupsPractical ways to reimagine your next meeting or event, from TED-style storytelling formats to intentional conversation designThings to listen for:(00:00) Intro(02:41) The importance of celebration and connection(04:48) Emotional and social bonding at events(06:39) The power of storytelling(08:40) Creating meaningful conversations(15:27) Practical tips for hosting effective events(26:49) Virtual event strategiesConnect with Rebecca:https://www.rebeccafleetwoodhession.com/

Growing up, Vanessa's family was basically two animals away from running a full-on zoo—but parenting with pets? That's a whole different story. In this episode, she sits down with Katherine Schwarzenegger Pratt—New York Times bestselling author, animal advocate, and mom—to ask the big question: Are pets really worth it? They talk about the beauty and chaos of raising kids (and animals), how pets teach responsibility and empathy, and the heartbreak that comes when it's time to say goodbye. Katherine shares stories from her new children's book Kat and Brandy—inspired by her own childhood pony—and offers thoughtful advice for families deciding whether to add a furry (or feathered!) friend to the mix. Whether you're a lifelong "animal person" or still dodging your kids' puppy PowerPoints, this conversation will make you laugh, reflect, and maybe even rethink what "family" really means.   Katherine's book is out now! Order Kat and Brandy today!   Start printing your photos with Chatbooks!   Follow us on Instagram @vanessaquigley @chatbooks  

In this episode, Roman Axelrod, founder and CEO of Xpanceo, shares the bold vision behind raising capital - $290M to create smart contact lenses designed to expand human capability. From building prototypes to leading a deep-tech team, Roman opens up about the real challenges of turning science fiction into science fact. He discusses the grit it takes to lead a company operating at the edge of innovation—and how clarity, communication, and conviction become non-negotiables in the process. We explore: • The role of storytelling in raising capital for moonshot ideas • Why prototypes matter more than PowerPoints in deep tech • How to attract world-class talent in a hyper-competitive market • What makes co-founder relationships thrive under pressure • How creativity and discipline coexist in breakthrough innovation Whether you're a founder, investor, or future-focused leader, Roman's journey offers powerful lessons on building what doesn't yet exist—and getting others to believe in it. — Subscribe to CPO PLAYBOOK for more conversations at the intersection of leadership, innovation, and capital strategy. Chapters 00:00 The Vision Behind Xpanceo 10:16 Challenges and Reactions to the Idea 14:14 Building a Deep Tech Company 17:22 Motivating a High-Stakes Team 21:47 The Importance of Prototypes 23:58 Recruiting Top Talent in Deep Tech 27:35 The Co-Founder Dynamic 31:14 Communication and Leadership in High-Stakes Environments 34:42 Cultivating Creativity and Vision 39:49 Looking Ahead: The Future of Xpanceo

#308th  for 30th of October, 2025 or 3311! (33-Oh-Leven, not Oh-Eleven, OH-Leven)http://loosescrewsed.comJoin us on discord! And check out the merch store! PROMO CODEShttps://discord.gg/3Vfap47ReaSupport us on Patreon: https://www.patreon.com/LooseScrewsEDSquad Update:  (Updated by Bloom 10/16)Busted in old and fun ways. Come join us colonizing, BGS works out here.Ish. So does the colonizingPowerPlay Update: - (unashamedly copied from KrugerFive's post in our Discord, 10/30)Cycle 52: Here's to one year of powerplay 2.0 complete! Cheers! Princess Aisling with 3 strongholds lost! First week she's went negative since at least cycle 22Li Yong-Rui wins across all the boards this week with +39 new systems, including 6 new fortifieds, and 1 stronghold.Possible the most gained in pp2.0Kaine upgrades 5 systems to strongholds with the most this week, and +20 systems overallDelaine hit with a loss of -4 systemTorval passes Delaine for P10 in the Nicey/KrugerFive boardsShe is in sight of Delaine for P10 in the FDev boards as well, possibly passing in a 2-3 weeksAll the powers are starting to show pretty steady trends and the FDev leaderboard is getting pretty close to being sorted. The Nicey/KrugerFive oneThen after that may be a really long wait. 14 and 24 cycles are a pretty ls are pretty much sorted out now. If everyone keeps playing the same for the FDev leaderboard my passing predictions are:Torval passes Delaine in 3 cyclesEmperor Arissa passes Mahon in 14 cyclesKaine passes Archer in 24 cyclesong time as it is. I hope this stuff around HIP 87621 shakes up powerplay some. (edited)Thursday, October 30, 2025 1:20 PMKruger 5's Power Rankings - https://k5elite.com/ Niceygy's Power Points - https://elite.niceygy.net/powerpointsFind out more in the LSN-powerplay-hub forum channel.Galnet Update: https://community.elitedangerous.com/ (updated 10/23)Panther Clipper Enters Full Production ( Galnet News | Elite Dangerous Community Site )Brewer Construction Campaign Achieves Targets“Independent observers believe that the concentration of megaship traffic and the secrecy surrounding the order, together with the reported direct messages to pilots pledged to one of the twelve Powers, are strong indicators of an intention to rapidly construct a science and security enclave around HIP 87621.”Dev News: New paint job - “ https://www.elitedangerous.com/store/catalog/promoHalloween event is live, Paints are the reward! I couldn't find the link ~ larkDiscussion:Gameplay: Making the case that fixing BGS and other bugs would bring some people back to the game, who are currently doing other things but would like to play elite. Combat vs other gameplays Community Corner:***** Audaxius' song: THE MUSIC OF THE HARBINGER *****

Soham Mazumdar, CEO and Co-Founder of WisdomAI, discusses how organizations can break free from the "drowning in data but starving for insights" paradox that plagues modern enterprises. We explore his journey from Google's TeraGoogle project to co-founding and scaling Rubrik through its $5.6 billion IPO, and why he left that success to build an agentic AI approach to Business Intelligence (BI) that transforms how businesses extract value from their data investments.SHOW: 971SHOW TRANSCRIPT: The Cloudcast #963 TranscriptSHOW VIDEO: https://youtube.com/@TheCloudcastNET NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SPONSORS:[Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcastSHOW NOTES:WisdomAI websiteTopic 1 - Welcome to the show, Soham. We overlapped briefly at Rubrik. Give everyone a quick introduction and tell everyone a bit about your time at Google prior to RubrikTopic 2 - You helped scale Rubrik from inception to a $5.6 billion IPO in 2024. What was the "aha moment" that made you leave that success to tackle the enterprise data analytics problem with WisdomAI?Topic 3 - Let's define the core problem. Organizations invest heavily in modern data platforms - Snowflake, Databricks, etc. - but there is the term "drowning in data but starving for insights." What's broken in the traditional BI stack that prevents business users from getting answers?Topic 4 - How do agentic AI and BI fit together? WisdomAI introduces the concept of "Knowledge Fabric" and agentic data insights. Break this down for us - how does this fundamentally differ from traditional dashboards and BI tools?Topic 5 - One of the biggest challenges with GenAI in enterprise settings is hallucination. You've emphasized that WisdomAI separates GenAI from answer generation. How does your approach tackle this critical trust issue?Topic 6 - Let's talk about data integration complexity. Your platform works with both structured and unstructured data - Snowflake, BigQuery, Redshift, but also Excel, PDFs, PowerPoints. How do you handle this "dirty" data reality that most enterprises face?Topic 6a - With so much data, how do most organizations get started? What's a typical use case for adoption?Topic 7 - If anyone is interested, what's the best way to get started?FEEDBACK?Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

We've all sat through bad slide decks—but what about the ones that change history? In this episode of Is This Really a Thing?, Dean Paul Jarley is joined by Jim Balaschak, Dr. Mike Pape, and Derek Saltzman to explore whether the so-called “billion-dollar PowerPoint” is myth or reality. From Airbnb and Tesla's iconic pitch decks to the role of storytelling, trust, and investor psychology, they unpack what makes a presentation powerful, what doesn't, and whether AI or new tools might one day dethrone PowerPoint. Featured Guests Michael Pape, Ph.D. - Dr. Phillips Entrepreneur in Residence & Professor of Practice, Management Jim G. Balaschak - Principal, Deanja, LLC Derek Saltzman - Co-Founder & Chief Executive Officer, Soarce Episode Transcription Paul Jarley: We've all sat through terrible slide decks, but every so often a PowerPoint does more than communicate. It creates value. Think of the pitch deck that launched Airbnb, the presentation that convinced investors to fund Tesla or the strategy decks that shape billion dollar mergers. So is the billion dollar PowerPoint really a thing? Can a few slides actually change the course of business history, or is it just a fancy way of describing really good storytelling? This show is all about separating hype from fundamental change. I'm Paul Jarley, Dean of the College of Business here at UCF. I've got lots of questions. To get answers, I'm talking to people with interesting insights into the future of business. Have you ever wondered, Is This Really a Thing? Onto our show. To help me figure this out, I've invited three guests. Jim Balaschak is an alum of the college, in our Hall of Fame, and a serial investor. Dr. Mike Pape is an Entrepreneur in Residence here at the College of Business, and Derek Saltzman is a former winner of the Joust and is co-founder of a company called Soarce. Thank you gentlemen for being here today. We've all seen really bad PowerPoints. Talk a little bit about what makes a great one. Jim, I'll start with you. Jim Balaschak: A PowerPoint that catches my eyes shows a big potential market, a problem they've identified that they have a solution for that they can make money on. It's not necessarily always the slides, but the slides can quickly convey the idea of the thoughts. And a lot of times before I meet with a founder, I'm emailed the pitch deck and going through the pitch deck helps me determine do I want to pursue this to the next step, get on the call with the founder, have them pitch it to me? I think it's a good way to open the door. Paul Jarley: The quality of the pitch deck tells you something about how serious and well thought out this is, right? So a schlocky one can really close the door, maybe more than a really good one can enhance it. Is that fair in your view? Derek Saltzman: Yeah. Paul Jarley: Derek, what do you think? Derek Saltzman: I think there's a lot to take into consideration with the audience and the stage gate of when you're first starting a pitch or when you're trying to interact. There's multiple decks for multiple stage gates. So in the first beginning intro, like for instance, how Jim said, when you're trying to send and get that initial meeting, it's all about a hook. Can you describe what you do in the most succinct, effective way possible to get the message across of what the problem is, how you're solving that problem, and what's the revenue potential like he described? Because that's what all investors are really looking for. Once you move past that initial stage gate, you have much more detailed decks that go into your financials that go into your true revenue model, your business model, maybe your IP strategy, and a variety of other topics. The overall optics and the overall clear messaging is I'd say the two biggest things. Paul Jarley: Mike, what do you tell students? Michael Pape: The way I deal with the pitch deck is treat it as just one element of a much bigger picture.

#307rd for 23st of October, 2025 or 3311! (33-Oh-Leven, not Oh-Eleven, OH-Leven)http://loosescrewsed.comJoin us on discord! And check out the merch store! PROMO CODEShttps://discord.gg/3Vfap47ReaSupport us on Patreon: https://www.patreon.com/LooseScrewsEDSquad Update:  (Updated by Bloom 10/16)BGS - Alec and our friends from Lave were reading the update notes for T-11 Patch 2 from last week. Reviewing the issue tracker ID's in the patch notes - BGS getting stuck is what FDev thinks is fixed and it looks fixed.What wasn't fixed per the patch notes - Mission influence going to the right place still doesn't seem to be fixed. So now it's half brokeOur friends were discussing when BGS Broke, was it PP 2.0, was it Trailblazers, when did it break? (Cockney Accent) - Blimey - It all began with PP 2.0, bloke! Fifteen Quid For a Broken Game?!?!?!Colonization Update - The Loose Screws control IC 22602 Sector ZU-Y d103!Arai's Inheritance. It is the official platinum mining hole of the Loose Screws Network. Thank you to Volt, Edward Skeele, Uraniborg, BorkedPowerPlay Update: - (unashamedly copied from KrugerFive's post in our Discord, 10/23)Cycle 51: Can you believe we are entering into 1 year of powerplay 2.0 this week?Winters with a strong week adding the most systems at +18 (all exploited)Yong-Rui again with the overall strongest week with +5 more strongholds and +8 fortifiedsPatreus goes -1 system overall, but -3 fortifiedsDelaine also kept flat with 0 systems gainedKruger 5's Power Rankings - https://k5elite.com/ Niceygy's Power Points - https://elite.niceygy.net/powerpointsFind out more in the LSN-powerplay-hub forum channel.Galnet Update: https://community.elitedangerous.com/ (updated 10/23)Megaship Movements Spark HIP 87621 SpeculationIndependent observers have reported unusual activity in systems surrounding HIP 87621, intensifying rumours of covert operations in the region.Multiple reports indicate that megaships have been spotted operating near the permit-locked system over the past week. Though no Power has formally acknowledged involvement, analysts believe this early mobilisation suggests a push for influence around HIP 87621.CG NOTE “Merit-palooza”: The large merit awards for mining within the CG system are no longer available, due to revoking the ‘God-Handed' powerplay state. The only power within 20-30ly is Grom (as it always was), so the ‘normal' mechanic for getting mining merits there doesn't work now.Will it come back?...Dev News: New paint job - “ https://www.elitedangerous.com/store/catalog/promoHalloween paint jobsSpectrix for all the new ships - looks like monster teeth on the ships' backsMalevolent Horror for AnacondaVarious ‘wisps' (haunt, poltergeist, shade, yurei, revenant, phantasm, horror)Basically pumpkin faces of various sizes for the old shipsOn-foot pumpkin outfitsOn-foot skeleton outfitsOn-foot ‘slimed' outfitsPumpkin ship decal

Send us a textBuckle up — Peaches sits down with Black Rifle Coffee's Jared Taylor and AFSW's Chief Jimbo Spreeder to torch the nonsense strangling the Air Force from the inside out. From the death-by-a-thousand-cuts of the A-10, to the badge redesign drama, to the Tech P force reduction nobody understood, this episode pulls zero punches.Peaches calls out leadership confusion (“Wait, you didn't know what TacPs do?!”), while JT and Jimbo laugh their way through the bureaucratic chaos that makes warriors less lethal. Expect hard truths, gallows humor, and the kind of brutally honest conversation you'll never hear in a press briefing. If you think the military's “heritage problem” ends with pilots and PowerPoints, think again. The boys talk heritage, mental toughness, rebuilding the pipeline, and why being “Instagram fit” won't save your ass when the rotors kick up and it's go time.This one's pure Ones Ready energy: real talk, no filters, and all attitude.⏱️ Timestamps: 00:00 – “So… the Air Force forgot what TacPs do?” 03:00 – JT & Jimbo on making the ‘Controlled' documentary and saving the legacy 07:00 – How two dudes turned chaos into a badass TacP history film 10:00 – “The A-10 ain't dead yet… but it's bleeding out” 15:00 – Inside the new badge redesign and why it pissed everyone off (again) 20:00 – Future of the TacP pipeline: less fluff, more fight 25:00 – “We don't want influencers — we want killers” 32:00 – Swimming, stress, and suffering: TacPs hit the pool 38:00 – Morale shocker: why commanders are finally happy again 43:00 – Peaches & Jimbo on the State of TacP: cutting dead weight, building killers 50:00 – The new Scout Program and the legend of Funky Bunkley 54:00 – JT's next mission: writing, war stories, and whiskey 56:00 – “Train hard, shut up, and stop believing the rumors”

When Amazon infamously ditched PowerPoints in meetings and opted to use a six-page written narrative format, many professionals took notice of their bold move. However, very few followed their lead. After reading a book on Amazon's leadership philosophy (“Working Backwards”), I decided to experiment with a new meeting format. In this podcast, I provide a […] The post Ep. 380 – The B.E.S.T. Meeting Method appeared first on Just Saying.