A Beginner's Guide to AI

AI agents are rapidly becoming one of the most influential technologies inside modern organizations — often without leaders even realizing the shift. In this episode, Dietmar Fischer sits down with MIT Sloan podcast host Sam Ransbotham to uncover why AI agents and agentic AI systems are spreading through enterprises at remarkable speed.Based on a global study of 2,100 executives across 116 countries, Sam shares how AI agents improve productivity, increase job satisfaction, and fundamentally reshape how companies work. From Chevron’s proactive exploration tools to the rise of autonomous knowledge assistants, we explore the surprising ways enterprise AI adoption is unfolding in real time.📧💌📧Tune in to get my thoughts and all episodes — don’t forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧This wide-ranging conversation covers practical use cases, risks and transparency issues, the future of generalists vs specialists, how universities adapt to AI, and why understanding the technology still matters deeply.Quotes from the Episode“We’re moving from tools we command to tools that proactively act on our behalf.”“AI agents don’t just make us more productive; they make us happier by removing the parts of work we dislike.”“Understanding AI makes you a better user of AI. Depth still matters.”Chapters00:00 Welcome & How Sam Got Into AI03:21 What Are AI Agents? Definitions and Early Insights07:14 Real Enterprise Use Cases of AI Agents12:05 Job Satisfaction, Productivity, and Human-AI Collaboration17:20 Generalists, Specialists & the Future of Work22:30 Risks, Transparency & Avoiding an Oppressive AI Future28:45 How Companies Should Start with Agentic AI33:20 AI in Education and Changing Learning Environments39:00 Sam’s Personal Use of AI — What Works and What Doesn’t41:20 Terminator vs Matrix? AI Futures42:41 Where to Find Sam and the MIT Sloan StudyWhere to Find the Sam Ransbothamsite at Boston CollegeOr you find him on LinkedInThe study of MIT Sloan lies hereAnd, last, but not least, Sam's podcast “Me, Myself, and AI”!About Dietmar Fischer:Dietmar is a podcaster and AI marketer from Berlin. If you want to elevate your AI or digital marketing strategy, get in touch anytime at argoberlin.comMusic credit: “Modern Situations” by Unicorn Heads 🎵 Hosted on Acast. See acast.com/privacy for more information.

In this episode of Beginner’s Guide to AI, we sit down with Alex Kihm, founder of POMA AI, to explore how enterprises can finally make sense of their data. AI search is broken, RAG often fails, and corporate documents are notoriously hard for LLMs to interpret. Alex explains how POMA AI’s patented method reconstructs structure inside unstructured data, enabling powerful, accurate enterprise search.You’ll hear how his journey from engineering to legal tech to big-data econometrics led to a breakthrough in information structuring. Alex shares why PDFs confuse AI systems, how chunking destroys meaning, and why context engines will replace classical retrieval systems. This is a deep, funny, insightful conversation about what AI can and cannot do — and how companies can use it responsibly.📧💌📧Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧About Dietmar FischerDietmar is a podcaster and AI marketer from Berlin. If you want to elevate your AI strategy or your digital marketing, feel free to reach out anytime at Argoberlin.comQuotes from the Episode“Chunking is like reading wrongly sorted text messages from the 90s.”“Intelligence is pattern recognition — and most enterprise data is not recognisable to machines.”“PDF was made for printers, not for AI.”“POMA AI restores the spatial awareness inside documents — the missing context that LLMs need.”“We don’t do RAG anymore. We build context engines.”“If your AI breaks the world, show me the invoice.”Chapters00:00 Welcome and Introduction 02:45 Alex Kihm’s Background: Engineering, Legal Tech and Early AI Work 10:32 The Problem with RAG, Training, Fine-Tuning and Hallucinations 18:55 The Birth of POMA AI and Solving the Chunking Problem 32:40 How POMA AI Rebuilds Document Structure and Enables True Enterprise Search 45:50 AI Safety, Manipulation Bots and The Future of AI in Business 52:10 Where to Find Alex Kihm and Closing Thoughts Where to Find the Dr. Alex KihmAll you need to know about chunking strategies, you'll find here: poma-ai.comContact Alex on LinkedIn! Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Artificial intelligence breakthroughs might appear magical from the outside, but underneath lies a predictable and surprisingly elegant structure. This episode of A Beginner’s Guide to AI takes listeners on a clear and engaging journey into the three scaling laws of AI, exploring how model size, dataset size, and compute power work together to shape the intelligence of modern systems. Through practical explanations, entertaining analogies, and detailed real-world case studies, this episode demystifies the rules that drive every meaningful AI advancement.Listeners will learn why bigger models often perform better, how data becomes the lifeblood of learning, and why compute power is the critical engine behind every training run. The episode includes a memorable cake analogy, a breakdown of how scaling laws led to the rise of state-of-the-art large language models, and practical tips for evaluating AI tools using these principles.This deep yet accessible explanation is designed for beginners, creators, and curious minds who want to understand what truly makes AI work.📧💌📧Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧About Dietmar Fischer: Dietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or your digital marketing going, just contact him at argoberlin.comQuotes from the Episode“AI doesn’t just grow; it scales, and scaling changes everything.”“Compute isn’t the cherry on top; it is the oven that makes the entire AI cake possible.”“Scaling laws show us that AI progress isn’t magic; it’s engineered.”Chapters00:00 Introduction to AI Scaling03:24 The Three Scaling Laws Explained11:02 The Cake Analogy for AI Models17:40 Case Study: How Scaling Transformed Large Language Models23:58 Practical Tips for Understanding and Applying Scaling Laws28:45 Final Recap and Key TakeawaysMusic credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

🚀 Matt Weaver, Solutions Engineering Leader at OpenAI, takes us inside the launch of GPT-5, the rise of AI agents, and how these tools are transforming industries. From practical business adoption tips to exploring advanced features like Deep Research and Custom GPTs, this episode is packed with actionable insights.📧 Tune in to get my thoughts, tips and tricks and all the episode in your mailbox: beginnersguide.nl💡 What you’ll learn in this episode:How GPT-5 chooses the right reasoning model automatically for better answersWhy AI literacy is the foundation for business adoptionIndustry examples from banking (BBVA) to travel (Virgin Atlantic)How AI agents like Deep Research work – and why they’re a game changerCreating your own Custom GPTs without codingAddressing AI objections: security, hallucinations, and cost concernsQuotes from the Episode:💬 “AI is such a transformative technology — now is the time to reimagine your processes, not just bolt it onto old ones.” – Matt Weaver💬 “Your first AGI moment changes how you see every problem — you start thinking, ‘How can ChatGPT help me with this?’” – Matt Weaver🧾 Chapters (experimental):00:00 Welcome & Introduction to Matt Weaver01:18 Matt’s Journey into AI and Joining OpenAI03:58 GPT-5 Launch – What’s New and Why It Matters08:28 How Businesses Should Start with ChatGPT10:45 AI Adoption Strategies & Avoiding Common Mistakes12:14 Industry Examples – Banking, Travel, and Professional Services14:06 Deep Research: AI Agents Explained18:06 Study Mode & AI in Education19:56 Overcoming Objections: Security, Hallucinations & Costs24:06 ROI of ChatGPT in Business28:22 The “AGI Moment” & Personal Uses of ChatGPT32:03 The Future of AI: Agents, Coding, and New Businesses35:48 Custom GPTs – Building Your Own AI Apps39:06 AI Safety & Optimism for the Future41:16 Where to Find Matt Weaver & ClosingWant to know more?🔗 ChatGPT is now also at Chat.com🔗 OpenAI's learning resources are at: academy.openai.com🎵 Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Ever wished you could clone yourself to get more done? Julian Goldie actually did it — and built a content empire out of it. In this episode of A Beginner’s Guide to AI, host Dietmar Fischer talks with Julian about how he uses AI to create five videos a day, automate workflows, and still keep a personal, human touch that builds real trust with his audience.Julian reveals how he turned his initial fear of AI into a full-scale growth engine for his business, transforming his SEO agency into a modern AI-powered content studio. He shares the systems, tools, and mindset that helped him automate marketing, scale his team, and reach millions — all while avoiding the “AI slop” that floods the internet.📧💌📧Tune in to get my thoughts and all episodes — don’t forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠📧💌📧💡 Key HighlightsHow Julian scaled from one YouTube channel to nine using AIThe tools behind his workflow: Descript, Claude, and HeyGenWhy AI videos sometimes outperform human ones (and when they don’t)The importance of quality control and the “human in the loop”How AI can make leadership more human — through reflection and empathyWhy it’s not humans vs AI, but humans with AI vs everyone else🧠 Quotes from the Episode“I thought AI would destroy my agency — instead, it became my best employee.”“It’s not humans versus AI — it’s humans with AI versus everyone else.”“My AI avatar never gets tired, never mispronounces a word, and somehow gets better watch time than me.”🕒 Chapters00:00 Julian’s AI Origin StoryHow the fear of losing his SEO agency pushed him into AI — and why his first ChatGPT video went viral.06:12 Scaling Content: From Livestreams to 5 Videos a DayJulian explains his full workflow, the role of AI avatars, repurposing, and why human connection still matters.14:40 AI Tools That Power the SystemA practical look at Descript, HeyGen, Claude, and how his team uses them to automate editing, clipping, and content creation.22:18 Leadership, Teams & the Human in the LoopHow AI supports decision-making, reflection, communication, and empowers team members instead of replacing them.30:44 The Future of AI Content & Final ThoughtsQuality control, the fight against “AI slop,” the risks ahead — and whether the Terminator is coming.🌐 Where to Find the Julian Goldie:Julian Goldie's Agency: goldie.agencyAI Profit Boardroom: aiprofitboardroom.comYouTube: @JulianGoldieTwitter/X: @JulianGoldieSEOAnd Julian's Website: juliangoldie.com👤 About Dietmar FischerDietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or digital marketing going, just reach out at argoberlin.com 🚀🎵 Music credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Step into the future of artificial intelligence with Fred Jordan as he introduces “Biocomputing”—the next evolutionary leap for AI. In this episode, Fred unpacks how biocomputing uses nature’s own design principles to build more adaptive, resilient, and intelligent systems.📧💌📧Tune in to get my thoughts, and don’t forget to ⁠subscribe to our Newsletter⁠! 📧💌📧Highlights from the episode:What “Biocomputing” is, and why it matters for the future of AIHow biocomputing fundamentally differs from traditional approachesFred Jordan’s personal journey and vision for next-generation intelligenceReal-world examples and the untapped potential of biocomputingQuotes from the Episode:“Biocomputing is about harnessing the principles of life itself to create intelligence that adapts and evolves, just like nature intended.”“We’re not just building smarter machines; with biocomputing, we’re taking inspiration from biology to leap forward in how AI thinks and grows.”Chapters (experimental):00:00 Introduction and Fred Jordan’s Background04:15 What Is Biocomputing? The Big Idea15:30 Biocomputing vs. Traditional AI: Key Differences28:50 Real-World Applications and the Future of Biocomputing41:10 Closing Thoughts and Next StepsWhere to find Fred Jordan and FinalSpark:Discord: discord.com/invite/edPetHUYtxWebsite: finalspark.comApply to join: finalspark.com/neuroplatform/Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

🎙️ He Taught AI How to Have Manners — Meet David Petrou of Continua AIWhat if your next group chat had an extra participant — one that listens, understands the social context, remembers what you said last week, and even knows when to stay quiet? In today’s episode, host Dietmar Fischer sits down with David Petrou, founder and CEO of Continua AI, to explore the emerging world of Social AI — intelligent agents designed not just to talk, but to collaborate inside group chats.David, formerly at Google and part of the original Google Glasses team, has spent decades thinking about how humans and machines interact. With Continua, he’s building the world’s first truly human-aware AI that can join your Discord, iMessage, or Google Message conversations and behave like a socially intelligent teammate. This isn’t a chatbot — it’s an AI that understands when to talk, when to listen, and when to help.📧💌📧 Get my NewsletterTune in to get my thoughts and all episodes, don’t forget to subscribe to our Newsletter: 👉 https://beginnersguide.nl📧💌📧Get ready for a deep dive into social intelligence, etiquette in AI systems, agentic actions, and the future of communication where AI participates naturally alongside humans.💡 What You’ll Learn in This EpisodeWhy Social AI is the next big evolution beyond traditional chatbotsHow Continua trains AI to understand timing, tone, context, and social cuesWhy David believes text messaging with AI will reach a billion usersThe engineering challenge behind teaching AI “manners” and “machine etiquette”How AI group chat agents improve communication, planning, and collaborationThe real use cases: debugging code, planning trips, updating documents, running games, and summarizing informationHow Continua’s multi-model architecture orchestrates LLMs, fine-tunes, and intent classifiersWhy Social AI is surprisingly safe — and why today’s fears don’t match the technical realityThe leadership perspective: how to integrate AI thoughtfully without overwhelming teamsWhere Social AI is heading next: meetings, real-time participation, contextual computing, and agentic actions like shoppingThis episode is packed with insights for anyone interested in AI agents, human–AI collaboration, team communication, or the future of intelligent digital assistants.📌 Quotes from the Episode“We had to break the LLM’s brain and teach it social etiquette: when to talk, when to listen, and when to stay quiet.”“Traditional chatbots operate in single-player mode — Continua is built for multiplayer conversation.”“There are problems beyond our ability to solve directly — the real ingenuity is creating something that can learn how to solve them.”“Introducing a foreign intelligence into human group dynamics is one of the most fascinating problems in AI.”“Text messaging with AI will be the next form factor to hit a billion users.”“Language itself is the interface. You don’t need menus. You just tell the AI how you want it to behave.”⏱️ Chapters00:00 David Petrou’s Origin Story & Early Fascination with AI04:51 Why Social AI Matters: From APIs to Human-Aware Group Agents09:12 Teaching AI Social Etiquette: When to Talk, Listen, or Stay Quiet16:11 Inside Continuum: Multi-Model Architecture, Fine-Tuning & Real Use Cases24:05 Social AI in the Real World: Planning Trips, Debugging, Collaboration & Automation35:01 The Future of Social AI: Meetings, Agentic Actions, Leadership & Ethical Considerations🧑‍💼 About Dietmar FischerDietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or your digital marketing going, just contact him at argoberlin.com🔗 Where to Find the Guest: David PetrouWebsite: continua.aiLinkedIn: David PetrouInstagram: David Petrou🎵 Closing CreditsMusic credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Artificial Intelligence isn’t just reshaping technology — it is reshaping leadership.In this episode, former Google strategist Louisa Loran joins Dietmar Fischer to explore how leaders can adapt, evolve, and thrive in an age defined by rapid AI acceleration.Louisa shares her journey across Moët Hennessy, Maersk, and Google, revealing why the biggest barrier to meaningful AI adoption isn’t technology but leadership behavior, culture, and the willingness to unlearn. She explains why strategy must come before tools, how organizations waste months chasing the wrong use cases, and why AI doesn’t challenge culture — it scales it.---Newsletter:Tune in to get deeper insights and all episodes. Subscribe at beginnersguide.nl---This conversation offers a clear and practical blueprint for anyone leading teams, shaping strategy, or trying to stay relevant in an AI-enabled world.In this episode you will learn:How leaders can build an effective AI leadership mindsetWhy organizations waste time on “AI use-case lists”How generative AI distorted expectations across industriesHow to build a culture of curiosity rather than controlWhy middle management often resists AI transformationThe four elements of Louisa’s Leadership Anatomy frameworkHow Louisa uses three AIs as strategic thought partnersWhat AI literacy really means for modern organizationsHow Europe’s AI culture compares to the U.S.Quotes from the Episode:“AI doesn’t challenge culture. It scales it.”“If you don’t unlearn, you can’t lead.”“AI won’t replace you — but bad leadership will.”Chapters:00:00 Welcome & Introduction — Meet Louisa Loran00:37 How curiosity led Louisa from Moët Hennessy to AI and Google02:21 Early digital transformation and the roots of AI in logistics04:46 Why strategy comes before tools — the real AI leadership lesson07:15 The global “AI panic” and how leaders wasted 18 months on use-case lists09:42 Rediscovering critical thinking in the AI era11:56 Learning to lead through uncertainty and data discovery14:33 Building a culture of curiosity instead of control17:28 The leadership challenge: unlearning the habits of success20:14 Lessons from Google — when inefficiency is actually innovation23:01 How AI puts pressure on leaders and middle management25:47 The anatomy of leadership: eyes, lungs, arms, and spine29:42 Using three AIs as thought partners while writing a book33:11 What AI literacy really means in organizations36:18 Education, ethics, and the future of learning with AI39:22 The European AI mindset vs. U.S. drive42:15 Final insights: leading with clarity, courage, and curiosity43:37 Where to find Louisa Loran and her bookWhere to find the Guest:Website: LouisaLoran.comLinkedIn: Louisa LoranBook: Leadership Anatomy in Motion (wherever you buy your books)About Dietmar Fischer:Dietmar is a podcaster and AI marketer based in Berlin. If you want to get your AI or digital marketing moving, visit Argo.berlin.Music credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

📖 AI-Created Books: Chance or Threat?In this eye-opening episode of A Beginner’s Guide to AI, Professor GePhardT unpacks the fascinating, chaotic and sometimes alarming rise of AI-generated books. From Amazon’s restrictions on AI content to the ethics of machine-written storytelling, this episode dives deep into the future of publishing and what it means for readers, writers and creators.We explore how AI-written books are made, why platforms are overwhelmed and how readers can distinguish human creativity from machine-made text. You’ll hear surprising real-world cases, including the Clarkesworld shutdown and the now-infamous “82% AI-written” herbal remedy category on Amazon.📌 What you’ll learn:How AI book generation actually worksWhy AI is both a creative partner and a creative threatThe risks of misinformation in AI-written booksHow to spot an AI-generated bookWhy platforms like Amazon are tightening their rulesThe future of authorship in an AI-saturated world📧💌📧Tune in to get my thoughts and all episodes — don't forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧Quotes from the Episode“A book is more than content; it’s a relationship between the mind that wrote it and the mind that reads it.”“AI doesn’t dream, doubt or desire — it just predicts what comes next.”“AI can help creativity bloom, but it can also bury real voices under mountains of machine-written noise.”🧑🏻 About Dietmar FischerDietmar is a podcaster and AI marketer from Berlin. If you want to kickstart your AI or digital marketing journey, he’s your guy!You can find him at Argoberlin.com🎧 Music credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

// This is a repost of a great episode - and why, you ask yourself, did he not publish a new episode? Because you are nearly the only one listening to my podcast on the Thanksgiving weekend 😂The Terminator films have profoundly shaped how society thinks about artificial intelligence. This episode analyzes concepts like artificial general intelligence through the lens of Skynet, the malevolent AI in the movies. We explore real-world AI safety research inspired by cautionary sci-fi narratives. The episode prompts a thoughtful examination of how we can develop advanced AI that enhances humanity rather than destroying it. With ethical, responsible innovation, we can steer the future toward an AI-enabled world that benefits all.📧💌📧 Tune in to get my thoughts and all episodes, don’t forget to ⁠subscribe to our Newsletter⁠.📧💌📧About Dietmar FischerHost of Beginner’s Guide to AI. Economist and digital marketer helping teams turn AI from hype into workflows.Training, talks, and courses with thousands of participants. 🎙️Go to ⁠argoberlin.com ⁠to see how we can help you!This podcast was generated with the help of artificial intelligence. We do fact check with human eyes, but there might still be hallucinations in the output.Music credit: "Modern Situations by Unicorn Heads" Hosted on Acast. See acast.com/privacy for more information.

In this episode of A Beginner’s Guide to AI, host Dietmar Fischer talks with Roman Chernin from Nebius, about how AI democratization is reshaping the enterprise world. Roman reveals what it really takes to move from prototype LLMs to reliable, scalable AI platforms - and why most companies don’t need to train their own models to harness AI’s potential. 📧💌📧 Tune in to get my thoughts and all episodes - don’t forget to subscribe to our Newsletter: ⁠beginnersguide.nl⁠ 📧💌📧From his early years at Yandex, where machine learning quietly powered maps and search, to helping Nebius build global AI infrastructure, Roman’s story is a blueprint for how cloud platforms can make AI accessible to everyone. He explains how Nebius Token Factory enables businesses to deploy AI applications fast, how to navigate the minefield of compliance and cost, and why real success in AI comes from better collaboration and iteration — not from “being a genius.” 🚀 Key HighlightsWhat democratizing AI means for modern enterprisesWhy infrastructure scaling 10× a year forces constant reinventionHow Nebius bridges the gap between OpenAI and open-source ecosystemsMaking AI usable for non-technical teams through better developer experienceWhy Europe still has a chance to catch up in the AI raceHow AI changes leadership, creativity, and collaboration💡 Quotes from the Episode“The goal isn’t to build more data centers - it’s to make AI usable for people who aren’t AI experts.”“You don’t need your own LLM. You need a problem to solve - and the right infrastructure to do it.”“If you want to scale a system ten times, you don’t fix it - you rewrite it.”“Compute is becoming the new electricity, but we don’t want to be just a utility company.”“The real bottleneck isn’t GPUs - it’s making AI usable, compliant, and cost-efficient for real businesses.”“We can’t forbid AI use; it’s already here. The real challenge is helping society adapt fast enough.”🧾 Chapters00:00 Introduction - Welcoming Roman Chernin to the show00:28 Why AI? Roman’s early journey and Yandex years01:24 What Nebius does: Building AI infrastructure for builders03:02 The challenge of scaling AI infrastructure 10× per year05:06 From utility computing to full-stack AI platforms07:15 Why developer experience matters for AI growth09:45 How enterprises move from OpenAI to open-source models12:10 Compliance, data sovereignty, and enterprise security14:55 Cost, latency, and optimization challenges in AI scaling16:50 Which industries are adopting AI fastest18:40 Democratizing AI for mid-sized businesses19:35 Nebius Token Factory: Enabling custom AI APIs22:14 Open-source vs closed models - the real trade-offs26:03 The U.S. vs. European AI market and regulation31:20 How governments can drive AI demand (not just infrastructure)33:58 How AI changes leadership, creativity, and collaboration37:40 Why iteration beats genius - and how AI accelerates it38:56 Roman’s personal “wow moment” with AI video generation40:55 The real risks of AI - and how fast society must adapt43:35 Final thoughts and where to find Nebius and Roman Where to Find Roman Chernin and NebiusNebius WebsiteNebius Token FactoryRoman Chernin on LinkedInMusic Credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Human-Centered AI at Work with Monica Marquez: A Practical Adoption PlaybookIf you’re still treating AI like a shiny gadget, this episode will be a polite intervention.Monica Marquez (Flipwork) shows how to build a human-centered AI adoption playbook that actually sticks.We dig into AI as a partner, not a tool; psychological safety for teams; and the one-workflow-per-month rule that turns experimentation into measurable AI ROI.You’ll learn how to avoid work slop, build agentic workflows, and translate machine output into authentic intelligence that reflects your expertise. 🤖What you’ll learnShift identity first: “I experiment with AI daily.”Redesign workflows before adding tools.Create psychological safety so teams can try, fail, and improve.Kill work slop and layer your context for quality.Build agentic workflows that scale judgment and consistency.Track time saved and quality gains to prove ROI.📧💌📧 Tune in to get my thoughts and all episodes, don’t forget to subscribe to our Newsletter.📧💌📧Quotes from the Episode“The real danger isn’t killer robots. It’s disengaged humans.”“Don’t ship work slop. Turn artificial intelligence into your authentic intelligence.”“Redesign your workflow first, then layer AI. Otherwise you just automate the old mess.”“Stop treating AI like a tool. Treat it like a partner.”“Adoption starts with identity: I experiment with AI every day.”“Use AI for five-dollar tasks so you can solve five-thousand-dollar problems.”Chapters00:00 Welcome, who is Monica Marquez and what is Flipwork02:59 AI as a partner, not a tool05:34 Practical example: recruiting, prompts, and human judgment07:02 Generational beliefs, “artificial intern,” and mindset shifts11:24 From effort to impact: redefining success with AI12:46 Redesigning workflows before layering AI14:44 Psychological safety and daily experiments16:55 Leaders model usage, run side-by-side experiments18:37 Avoiding “work slop” and building authentic intelligence21:44 Doing more of your “zone of genius” with AI24:39 The one-workflow-per-month rule29:25 Industry adoption patterns, lessons from Blockbuster vs Netflix33:12 Personal AI use cases and voice-based workflows36:32 Matrix, Terminator, and Monica’s real fear: disengaged humans37:58 Where to find Monica and FlipworkWhere to find Monica MarquezHer Agency: FlipworkMonica’s site: themonicamarquez.comNewsletter: Ay Ay Ay, AIAbout Dietmar FischerHost of Beginner’s Guide to AI. Economist and digital marketer helping teams turn AI from hype into workflows.Training, talks, and courses with thousands of participants. 🎙️Go to argoberlin.com to see how we can help you!Music credit: “Modern Situations” by Unicorn Heads 🎵 Hosted on Acast. See acast.com/privacy for more information.

AI’s Biggest Secret: It’s Addicted to Being AverageLarge Language Models are masters of fluency but victims of probability. In this episode, Professor GePhardT unpacks why averaging—inside embeddings, attention mechanisms, and token probabilities—quietly drains AI of originality. Through humour, insight, and one brilliant case study from the University of Tübingen, we explore how “safe” AI outputs create the illusion of intelligence while smothering creativity.From mathematical foundations to philosophical implications, this episode challenges listeners to rethink what “intelligence” really means — and to look for brilliance not in the middle, but at the edges.📌 Key Takeaways:Why LLMs default to safe, predictable outputsHow averaging erases nuance in AIReal-world evidence of AI’s blind spots in reasoningTechniques to push models beyond the middle ground📧💌📧Tune in to get my thoughts and all episodes — and don’t forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧💡 Quotes from the Episode:“AI doesn’t need to be smarter. It needs to be braver.”“The tragedy of the average is that it sounds right but feels wrong.”“A bold sentence is an act of rebellion against probability.”Where to find Professor Gephardt:🌐 We help you figure out your AI game: argoberlin.comMusic credit: “Modern Situations” by Unicorn Heads 🎵 Hosted on Acast. See acast.com/privacy for more information.

AI tools for business coaching are transforming how leaders and professionals unlock performance and personal growth. In this episode of Beginner’s Guide to AI, Lisa Turner of CETfreedom joins Dietmar Fischer to share real-world strategies and 40+ actionable AI tools that help coaches, entrepreneurs, and business leaders boost results. 📧💌📧Ready to take your business to the next level? Subscribe for more AI strategies, share your questions in the comments, and visit our website for free resources. Don’t miss exclusive content in our newsletter—sign up today: beginnersguide.nl📧💌📧Learn how practical AI can revolutionize business processes, streamline leadership, and enhance productivity.Whether you want to overcome procrastination, empower your team, or drive personal development, this episode delivers proven approaches and expert insights.💡 Key takeaways:• Learn top AI tools for business coaching• Discover AI techniques to beat imposter syndrome• Explore AI strategies for leadership development• Find practical uses for AI in personal growth• See real examples of AI-ified coaching processes🧾 Chapters (experimental):00:00 – Welcome & Guest Introduction02:30 – Why AI? Lisa’s Journey from Engineering to Coaching07:10 – First Steps with AI: Overcoming Skepticism12:00 – Building 40+ AI Tools for Coaches18:45 – Busting Procrastination & Limiting Beliefs with AI24:20 – Empowering Leadership & Journaling via AI30:00 – The “Doctor Who” Mindset for Innovation35:15 – Trends: How Coaches Use AI in 202540:05 – Final Insights & Where to Find Lisa👉 Quotes:• "I found a way to AI-ify personal growth and leadership tools for real business results."• "If you want to grow fast, you have to experiment boldly with new technology."🔗 Where to find Lisa Turner:Go to Lisa's website and get a free book (a real one!) at: www.cetfreedom.com👩 Or follow Lisa on social media:TikTok: www.tiktok.com/@cetfreedomInstagram: www.instagram.com/cetfreedomFacebook: www.facebook.com/cetfreedomLinkedIn: www.linkedin.com/company/cetfreedom---🎵 Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Are you GenX and curious about AI, but not sure where to start? In this episode, Greg Steele breaks down how Generation X can confidently embrace artificial intelligence—no tech background required!📧💌📧Tune in to get my thoughts and all episodes in your mailbox, don't forget to ⁠⁠⁠subscribe to our Newsletter⁠⁠⁠!📧💌📧Join us as Greg shares his own AI journey, debunks common myths about technology adoption after 40, and explains why now is the perfect time for GenX professionals to upskill. Whether you’re looking to stay relevant at work, explore new career paths, or just understand the buzz around AI, this episode delivers clear guidance and practical tips.Key Highlights:Why AI matters for GenX and people over 40Overcoming technology barriers and digital fearEssential AI skills for midlife professionalsGreg Steele’s step-by-step approach to mastering AIReal-world stories of GenX success with AI toolsQuotes from the Episode:“AI isn’t just for digital natives. GenX has a lifetime of experience—and that’s an asset in the age of artificial intelligence.”“You don’t need to be a coder to thrive with AI. Curiosity and willingness to learn matter most.”Chapters (experimental feature):00:00 Introduction and Greg Steele’s AI Journey04:55 Why GenX Needs to Understand AI Now12:30 Overcoming AI Myths and Barriers for GenX21:00 Practical AI Skills for People Over 4029:15 Greg Steele’s Tips for Embracing AI with Confidence34:40 Closing Thoughts and Key TakeawaysGet Gregs Book Gen X, Y? - I had a big laugh listening to it 😂- On Amazon- On YouTube, read by himself!Look how his CustomGPT on Wildlife Photography can help you 📸 I actually tried it with the bee and wasp photos I took on my balcony - and I can tell you: I'll have to do better 😅Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.