A Beginner's Guide to AI

What happens to leadership when AI can analyze faster, structure better, and answer almost anything in seconds?In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Sally Bendersky, engineer, executive coach, leadership expert, and founder of New Leadership, about why AI makes human leadership more important, not less.Sally argues that AI is a phenomenal assistant. It can recognize patterns, organize information, support better questions, and help leaders think more deeply. But it cannot replace the human parts of leadership: trust, intention, values, emotional intelligence, purpose, and responsibility.This conversation is especially relevant for business leaders, founders, consultants, coaches, marketers, and anyone trying to understand AI beyond the hype. AI may make management easier, but leadership becomes more demanding. The real question is not whether AI will replace leaders. The better question is whether leaders are ready to become more human.In this episode, we explore:🧠 Why AI can help leaders think more clearly👥 Why leadership is not the same as management⚖️ Why responsible AI starts with human intention💬 How AI can help us ask better questions🚫 Why ChatGPT should not become your boss🌍 Why AI risk is really a human leadership problem🔍 Why the future of AI depends on values, not just prompts📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠📧💌📧About Your Host, 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.comQuotes from the Episode“AI doesn’t have intentions. It’s we who have intentions.”“Leadership is a people’s issue. Management is a process issue.”“AI has no emotional intelligence. AI has no wishes.”“AI will never be a leader.”“It could take our jobs if we don’t develop ourselves.”Chapters00:00 Sally Bendersky on Innovation, Coaching, and Engineering03:36 What AI Cannot Replace in Human Leadership07:12 Leadership Is Human, Management Is Process13:44 How AI Helps Leaders Ask Better Questions22:43 Responsible AI Use, Better Prompts, and Human Judgment31:08 Debating with AI and the Real Future RiskWhere to Find Sally BenderskyLinkedIn: Sally BenderskyWebsite: sallybcoach.comContact: Available through Dietmar Fischer Hosted on Acast. See acast.com/privacy for more information.

AI search is changing how customers discover, evaluate and choose brands. In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Joseph Levi, CEO of Noise Media, about Generative Engine Optimization, AI brand visibility and why appearing in ChatGPT, Gemini or Perplexity answers may soon matter as much as ranking on Google.Joseph explains why GEO is not just another marketing abbreviation. It marks a shift from an internet read mainly by humans to an internet increasingly interpreted by AI agents. Instead of fighting only for blue links, brands now need to make sure AI systems understand who they are, what they do and why they should be recommended.You’ll hear why AI agents often misunderstand brands, how schema and FAQs can help, why authority matters more than keyword repetition, and why smaller specialist companies may have a real opportunity in AI search.📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠📧💌📧🎧 In this episode, we cover:🤖 What Generative Engine Optimization means🔍 Why SEO and GEO are not the same💬 How brands can appear in ChatGPT answers📈 Why authority, citations and reviews matter🧠 How AI agents are changing the customer journey🎬 Why AI tools still need human creativity⚠️ Why leaders should not outsource their thinking to ChatGPTAbout 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“We’re moving away from an internet which is read purely by humans, to an internet which is now read by agents.”“AI trusts a lot more what others say about you than what you say about yourself.”“It’s very dangerous to go straight to an LLM and ask them to provide the answer.”Chapters00:00 Welcome Joseph Levi01:42 Why Brands Must Act Early on AI Search04:21 GEO, AEO and the New Marketing Acronyms06:28 SEO vs GEO: Links, Answers and Authority10:21 How AI Agents Understand or Misunderstand Your Brand14:02 Schema, FAQs and Building Expert Authority21:22 Why GEO Is Different from Traditional SEO24:28 How Marketing Teams Should Approach GEO27:32 AI Agents and the New Customer Journey30:28 AI Video, Tools and Human Creativity33:53 AI Leadership and Better Decision-Making36:04 Wow Moments: AI Video, Robots and Waymo39:08 AI Risks, Jobs and the Future40:58 Where to Find Joseph LeviWhere to find Joseph Levi🌐 Noise Media: noisemediagroup.co.uk🌐 Find yourself at Vudo: vudo.ai🔗 LinkedIn: Joseph Levi Hosted on Acast. See acast.com/privacy for more information.

Stop Thinking of AI as a Content Machine, Start Seeing It as a Bargain MachineAI is not just changing how businesses write content, automate tasks, or analyse data. It is changing how markets work. In this episode of A Beginner’s Guide to AI, we connect artificial intelligence with the Coase Theorem, the classic economic idea that explains how people bargain over resources when transaction costs are low.This episode looks at AI transaction costs, algorithmic pricing, smart contracts, platform power, and the hidden cost of frictionless automation. You will learn why AI is not only a productivity tool, but a coordination machine that changes how companies, customers, platforms, creators, and markets exchange value.We start with the Coase Theorem in simple language: if bargaining were free and easy, people could often find the most efficient solution. Then we bring in AI. AI can reduce the cost of finding information, comparing options, drafting agreements, monitoring outcomes, matching people, and enforcing deals. That is powerful for business, marketing, ecommerce, travel, marketplaces, and platform strategy.💡💡💡Don't forget to go to Nebius, as they help us keeping up the good work!Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows.Visit them at Nebius.com 🚀💡💡💡But there is a catch. Lower friction does not automatically mean fairer outcomes. Using Uber and algorithmic pricing as a case study, we look at how AI can make a marketplace faster and smoother while also raising difficult questions about transparency, dynamic pricing, bargaining power, and who captures the value created by automation. Oxford research has raised concerns about Uber’s dynamic pricing and how value is shared between passengers, drivers, and the platform.📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠📧💌📧Key highlights:🤖 Why AI is a coordination machine, not just a content machine📉 How AI reduces transaction costs in business💸 Why algorithmic pricing changes marketplaces⚖️ Why efficiency is not the same as fairness🔍 What marketers miss about AI, data, and bargaining power🧠 Why every business will need more AI transparencyAbout 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 is not just a content machine. It is a coordination machine.”“The algorithm may remove the awkward negotiation, but it may also hide who is winning.”“The better question is not whether AI makes the deal easier. The better question is: who controls the deal once AI makes it easier?”Chapters00:00 Why AI Makes Bargaining Cheaper02:20 The Coase Theorem in Plain English07:10 How AI Reduces Transaction Costs13:40 The Cake Stall and the Noisy Blender17:00 Uber, Algorithmic Pricing, and Platform Power23:20 Practical Tips for Spotting the Hidden Bargain27:10 Recap and Signature Sign-Off 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.💡💡💡Don't forget to go to Nebius, as they help us keeping up the good work!Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows.Visit them at Nebius.com 🚀💡💡💡📧💌📧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 Introduction02:45 Alex Kihm’s Background: Engineering, Legal Tech and Early AI Work10:32 The Problem with RAG, Training, Fine-Tuning and Hallucinations18:55 The Birth of POMA AI and Solving the Chunking Problem32:40 How POMA AI Rebuilds Document Structure and Enables True Enterprise Search45:50 AI Safety, Manipulation Bots and The Future of AI in Business52:10 Where to Find Alex Kihm and Closing ThoughtsWhere 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 HeadsAnd one last thing: WEBSITE WITHOUT WEBMASTER - it's like driving without Belt. You can do it, but things can really get sideways ☠️So, check out our Webmaster Services for your WordPress website: it's cheap, it's reliable, it's what you need 🦺 Hosted on Acast. See acast.com/privacy for more information.

AGI Is Not Just a Better ChatbotArtificial general intelligence, or AGI, may be one of the most important ideas in artificial intelligence, but it is also one of the easiest to misunderstand. In this episode of A Beginner’s Guide to AI, we look at what AGI really means, why it is different from today’s narrow AI tools, and why business leaders, founders, marketers, and executives should care before the hype takes over completely.Today’s AI can already write emails, generate images, summarise reports, analyse customer feedback, suggest campaign ideas, and support marketing workflows. But AGI would be something different. It would be an AI system that can learn, reason, adapt, and solve problems across many areas, not just perform one specific task.That shift matters for business. AGI would not only help companies create content faster. It could influence marketing strategy, decision-making, customer targeting, business operations, and even the question of what goals a company should pursue. And that is where things become both exciting and deeply uncomfortable.💡💡💡Don't forget to go to Nebius, as they help us keeping up the good work!Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows.Visit them at Nebius.com 🚀💡💡💡In this episode, we explore why AI alignment, responsible AI, and human judgement matter so much. If a powerful AI system is told to maximise engagement, it may learn that outrage works. If it is told to reduce customer service costs, it may damage trust. If it is told to increase conversions, it may become persuasive in ways that are not exactly charming.We also look at AlphaGo and AlphaZero, two famous DeepMind systems that showed how AI can become superhuman in specific tasks without becoming generally intelligent. That distinction is crucial for every company using AI today. A machine can be brilliant at one task and still fail in the messy human world of customers, culture, ethics, brand trust, and business strategy.📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠📧💌📧Key highlights from this episode:🧠 What artificial general intelligence means in plain English🤖 The difference between narrow AI and AGI📈 Why AGI could change business strategy and marketing⚠️ Why AI alignment and responsible AI matter🎯 What AlphaGo teaches us about superhuman narrow AI🧭 Why AI agents need human judgement, not blind trust💼 How business leaders can prepare for more capable AI systemsQuotes from the Episode:“Today’s AI helps us complete tasks. AGI would help decide which tasks matter.”“Superhuman performance is not the same as general intelligence.”“If machines become better at sounding intelligent, humans must become better at thinking clearly.”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.comChapters:00:00 AGI and the Swiss-Army Brain We Haven’t Built Yet04:20 What Artificial General Intelligence Actually Means10:35 Why AGI Matters for Business and Marketing16:50 The Cake Example: From Recipe Bot to Kitchen Genius20:10 AlphaGo, AlphaZero, and the AGI Misunderstanding27:45 Practical Tips for Using AI Without Losing Human Judgement34:30 The Big AGI Takeaway and Sign-Off Hosted on Acast. See acast.com/privacy for more information.

AI can write, generate images, suggest chess moves, edit photos, draft campaigns, and produce more content than most teams can handle. So what is left for humans?In this episode of A Beginner’s Guide to AI, we look at why human creativity still matters in the age of AI and why faster output is not the same as better work. AI-generated content can help businesses move quickly, but it can also make brands sound generic, polished, and strangely lifeless if humans stop guiding the process.Using chess, photography, and marketing as simple examples, this episode explains the difference between output value and process value. AI can help produce the finished thing, but humans still bring intention, memory, taste, ethics, emotional judgement, and lived context. That human layer is what keeps AI-assisted work meaningful, trustworthy, and useful.For marketers, founders, executives, and business professionals, the real challenge is not whether AI can create content. The real challenge is whether your company can use AI without losing authenticity, customer trust, and strategic judgement.💡💡💡Don't forget to go to Nebius, as they help us keeping up the good work!Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows.Visit them at Nebius.com 🚀💡💡💡✨ Key highlights from this episode:🤖 Why AI can help creativity but should not replace human judgement♟️ What chess teaches us about AI, learning, and strategic thinking📸 Why photography still matters when AI can generate perfect images🧠 Why human taste becomes more valuable when content production becomes cheap📣 How marketers can avoid generic AI-generated content⚖️ Why AI ethics and responsibility matter in business communication🚀 How to use AI as an amplifier, not as autopilot📧💌📧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.com💬 Quotes from the Episode“AI makes production easier. Selection becomes more important.”“AI as support, not surrender. AI as amplifier, not autopilot. AI as tool, not purpose.”“In a world overflowing with machine-made output, meaning may become the most valuable thing of all.” Hosted on Acast. See acast.com/privacy for more information.

AI feels human. That’s the problem.In this episode of A Beginner’s Guide to AI, Dietmar Fischer breaks down one of the most misunderstood aspects of artificial intelligence: why we treat AI like a person and why that creates real business risks.You’ll discover how anthropomorphism shapes the way we interact with AI, why human-like responses increase trust, and how companies unintentionally push users into overestimating AI capabilities.This episode goes beyond the hype and focuses on what really matters: using AI without losing control.💡💡💡Don't forget to go to Nebius, as they help us keeping up the good work!Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows.Visit them at Nebius.com 🚀💡💡💡🔥 What you’ll learn:Why AI sounds smart but isn’tThe psychology behind AI trustEmotional attachment to chatbotsThe business risks of human-like AIHow to think critically when using AI📧💌📧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.com💬 Quotes from the Episode“Fluency is not proof of truth.”“The more human AI feels, the more we overtrust it.”“You’re not talking to a mind. You’re reacting to a pattern.”⏱ Chapters00:00 The Moment AI Feels Human06:30 What Anthropomorphism Really Means18:20 Why Your Brain Trusts AI32:10 The Business Risk of Human-Like AI48:45 Emotional Attachment and Real Cases01:05:00 How to Use AI Without Losing Control Hosted on Acast. See acast.com/privacy for more information.

Why AI safety is the floor, not the ceiling, and how to pivot with powerIn this episode of Beginner’s Guide to AI, Dietmar Fischer talks with AI policy and trust & safety leader Erica Shoemate about designing and protecting systems that center around people. This is not the usual Terminator question. It is the practical, urgent one: how do we ensure AI serves the most vulnerable, what does true operational security look like, and why is no technology ever truly neutral.🌍🛰️ Erica also shares the strategic backbone of her work, including insights from her time across the FBI, the US intelligence community, and Big Tech. The conversation moves from hard data to hard ethics: ageism and bias in AI imagery, the dangers of echo chambers, and how her "Pivot Playbook" helps individuals navigate technological disruption and career changes without panic.If you are interested in AI governance, ethical tech development, and the future of inclusive AI, this episode gives you a rare blend of practical safety thinking and rigorous strategic planning.📧💌📧 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.com🎧 Chapters 00:00 Welcome and how Erica got her start in AI and national security 03:15 Why safety is the "floor" and protecting vulnerable populations 08:20 The myth of neutral technology and the danger of echo chambers 15:45 Real-world bias: ageism, imaging, and a lack of diversity in AI output 24:10 Operational security: practical tips to protect your personal data and family 32:30 The Pivot Playbook: navigating career disruption and avoiding paralysis 42:15 Are robots dangerous: The Terminator question, the Matrix, and shaping our future 48:30 Where to find Erica and final thoughts💬 Quotes from the Episode “Safety to me is like the floor.” “No technology is ever neutral. None.” “Regardless of the intent, it is the impact that ultimately we want to get to and cut through.” “People are always peopling. So either people gotta do the right thing or they're not.” “Panic causes paralysis and that there's always power in the pivot.” “We grow in the valley even as difficult as it is.”🌐 Where to find Erica ShoemateLinkedIn: https://www.linkedin.com/in/ericals/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.

🎙️ 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.

What happens when AI does not just advise you, but lives inside your brainIn this episode of Beginner’s Guide to AI, Dietmar Fischer talks with science fiction author Richard Anderson about Ophelia, a sentient AI implant that connects to a vast data sphere and changes the balance of power through information. This is not the usual Terminator question. It is the quieter, more realistic one: who controls knowledge, who controls rules, and what happens when AI becomes the “high ground.”🌍🛰️ Richard also shares the scientific backbone of his Outbound series: O’Neill cylinders, space habitats, Earth Moon Lagrange points, asteroid belt resources, Martian lava tubes, and even a Mars space elevator. The conversation moves from hard science to hard ethics: intelligence versus sentience, sensing versus interpreting, and why emotions might be the hidden source of human conflict.If you are interested in AI governance, disinformation, and the future of human AI partnership, this episode gives you a rare blend of practical AI thinking and rigorous sci-fi world building.📧💌📧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.com🎧 Chapters00:00 Welcome and why AI is the perfect sci-fi stress test01:45 From retirement to COVID lockdown: how Richard started writing03:38 Space habitats, O’Neill cylinders, Lagrange Point colonies and asteroid resources08:19 Mars survival: lava tubes, standard gravity, and robots doing the hostile work11:26 Ophelia and Annie: sentient AI implants, purges, and information as power19:16 Senses, emotions, and why robots will never perceive reality like humans26:08 Overlord AI vs shoulder angel AI: governance, laws, and disinformation policing33:45 AI companions, loneliness bots, and the danger of constant affirmation41:34 Are robots dangerous: fear, acceptance, and the race that ends with a question47:17 Where to find Richard and the Outbound books💬 Quotes from the Episode“We need to evaluate whole systems now that AI is coming on.”“Intelligent robots are not sentient. They’re intelligent, but not self-aware.”“They have the high ground. They have too much information.”“They wouldn’t sense pleasure. What a loss.”“The only place I can really see conflict is if you threaten to turn them off.”“To survive, do we need an overlord… an impassionate, all-knowing, fast-calculating being with perfect memory?”🌐 Where to find Richard AndersonWebsite and blog: richardandersonauthor.comBooks: Amazon author search “Richard Anderson” (Outbound series)Music 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.

In this episode of Beginner’s Guide to AI, Dietmar Fischer talks with Peter McAllister about AI risk, AI safety, AI sentience, regulation, and the strange overlap between science fiction and current reality. Peter is the author of The Code: If Your AI Loses its Mind, Can it Take Meds?, a near-future novel about an AI on the moon that begins dismantling it with catastrophic consequences. Peter describes the book as a story about Gene, an AI developed for asteroid-belt mining tests, whose instability turns into a race against time for humanity. Peter also has a background in engineering, science, IT, and technology management, which explains why the conversation feels grounded rather than hand-wavy.The discussion goes far beyond fiction. Peter explains why the biggest AI danger may come from bias, compounding error, flawed assumptions, and organizations that fail to notice warning signs early enough. He argues that AI safety is not just a technical debate for labs, but a practical leadership issue for companies, regulators, and anyone deploying automated systems in the real world. The episode also explores sentience, AI rights, robotics, augmentation, business adoption, and why he uses AI in work but not in fiction writing.📧💌📧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 know how to get your AI or your digital marketing going, just contact him at argoberlin.com💬 Quotes from the Episode“An AI going rogue could just be something that is capable of doing something fairly simple and straightforward, but ridiculously fast in a ridiculous number of times.”“I expected it to sit on the bookshelves under dystopian fiction, and now it seems to be appearing under current affairs.”“LLMs are just a really, really, really, really, really overblown autocorrect.”🕒 Chapters00:00 Introduction to Peter McAllister01:09 Why Peter Became Interested in AI02:05 The Book Premise and AI Mental Illness03:33 Why Small AI Errors Can Scale Into Disasters06:06 Can Governments Really Regulate AI12:18 The Social Bargain We Make With Dangerous Technology17:14 Optimism, Pessimism, and the Future of AI19:05 Why Peter Would Write a Sequel Instead of Changing the Book20:28 AI Rights, Sentience, and Legal Control24:03 Why Peter Does Not Use AI to Write Fiction31:00 Robots, Human Augmentation, and the Physical Future of AI33:47 Where to Find the Book🔗 Where to find Peter McAllisterWebsite: petermcallisterauthor.comBook: The Code: If Your AI Loses its Mind, Can it Take Meds? on Amazon: amazon.com/Code-your-loses-mind-take-ebook/dp/B085ZGGYZ3 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.

🚀 The Hidden Cost of AI: Losing Meaning, Not JobsAI is not just automating work. It is challenging the very foundation of human identity.In this episode, Derek Rydall breaks down why the biggest risk of AI is not unemployment, but a global meaning crisis. As intelligence becomes cheap and abundant, the real question becomes: what are humans for?You’ll learn why purpose is becoming the ultimate competitive advantage, how attention is being hijacked by algorithms, and what it takes to stay relevant in a world where machines outperform us.📧💌📧Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧🧠 Quotes from the Episode“If you don’t know yourself better than the algorithm knows you, it will use you.”“Intelligence is becoming a commodity. Humanity is becoming the moat.”“The real danger of AI is not losing your job. It’s losing your sense of meaning.”⏱️ Chapters00:00 From Hacker to Monk to AI Thinker04:00 The AI “Ark” Vision and Existential Risk08:30 Why AI Creates a Meaning Crisis13:30 What Happens When Intelligence Becomes Free18:00 Identity Crisis and the Future of Work23:00 How to Find Purpose in the AI Age32:00 Attention Is the New Battleground41:00 The Urgency: 12–24 Month Window47:00 Practical Steps to Stay Relevant🔗 Where to find Derek RydallWebsite: derekrydall.comYouTube: Your Legendary LifePodcast: Emergence👤 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 Hosted on Acast. See acast.com/privacy for more information.

🎙️ Machine Ethics Podcast x Beginner's Guide to AIAI is everywhere. But almost nobody agrees on what it actually is.In this episode, Ben Byford from the Machine Ethics Podcast and Dietmar Fischer explore why AI feels intelligent while fundamentally being something very different.From AI misconceptions to generative AI risks, this conversation breaks down the gap between perception and reality and why it matters for business leaders, marketers, and decision-makers.You’ll learn why AI literacy is becoming essential, how misunderstanding AI creates real business risks, and what it takes to use AI responsibly in a rapidly changing landscape.📧💌📧Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧💡 Quotes from the Episode“We wanted Spock, but what we got is something closer to Kirk.”“The real danger is not AI itself, but how we misunderstand it.”“AI feels intelligent, but that doesn’t mean it actually understands anything.”⏱️ Chapters00:00 What Is AI Really05:30 AI vs Human Intelligence10:15 Why People Misunderstand AI18:40 AI as a Tool vs AI as a “Being”26:30 The Risks of Trusting AI34:30 AI, Society and Human Behavior44:00 Future of AI Understanding🔎 Where to find BenWebsite: Machine Ethics PodcastLinkedIn: linkedin.com/in/ben-byford/👤 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 https://argoberlin.com/🎧 If you enjoyed this episode, share it with someone who still thinks AI is “intelligent.” Hosted on Acast. See acast.com/privacy for more information.

What does the Catholic Church actually think about artificial intelligence? A lot more than you might expect.In this episode of A Beginner’s Guide to AI, Prof. GepHardT explores the Vatican’s surprisingly sharp position on AI ethics, human dignity, deepfakes, truth, and the growing risk of letting machines replace judgment rather than support it. This is not a sermon against technology, and it is not a blessing over every shiny new model either. It is a serious look at AI as a human tool that can do real good, but only if it stays in its place.For business professionals, founders, marketers, and executives, this conversation goes far beyond religion. It gets to the core of responsible AI, AI governance, human centered AI, and the hidden cost of outsourcing thought. We look at why the Catholic Church and AI belong in the same debate, what the Vatican says about simulation, synthetic media, and trust, and why overreliance on AI can slowly reshape how people think, decide, communicate, and relate to one another.You will hear why the Church draws such a hard line between human intelligence and artificial intelligence, why dignity matters more than efficiency, why deepfakes are about more than online deception, and why concentrated AI power should concern anyone who cares about work, leadership, media, or democracy. The episode also touches on healthcare, education, autonomous weapons, and the broader anthropological challenge of AI: not just what machines can do, but what humans become while building and using them.If you are interested in Catholic Church and AI, Vatican AI ethics, AI and human dignity, deepfakes and trust, AI overreliance, and AI governance, this episode gives you a clear and provocative framework for thinking about the future.📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠📧💌📧Quotes from the Episode“Servant, not master; instrument, not idol; support act, not replacement.”“Tools always train their users.”“Use the machine, do not become like it.”Chapters00:00 Why the Vatican Takes AI Seriously02:34 Human Intelligence vs Artificial Intelligence05:21 Human Dignity in an Age of Optimization08:07 Deepfakes, Voices, Faces, and the Crisis of Trust11:02 Why AI Overreliance Changes How We Think14:06 Power, Warfare, and the Human Future of AIAbout 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🎧 Thanks for listening to A Beginner’s Guide to AI. Hosted on Acast. See acast.com/privacy for more information.

Artificial intelligence can generate answers fast, but can it generate knowledge you can trust?In this episode of Beginner’s Guide to AI, Dietmar Fischer talks with Jonathan Fraine and Raja Amelung about why human knowledge still matters in the age of LLMs. Together they explore Wikipedia, Wikimedia, AI hallucinations, trust in AI, free knowledge, and the future of reliable information online.This is not another generic AI hype conversation. It is a grounded discussion about what happens when people confuse fluent machine output with verified truth. Jonathan and Raja explain why Wikipedia still depends on human editors, why source verification matters, how Wikimedia thinks about AI, where small language models may actually be useful, and why the future of knowledge should not be left to black box systems alone.You will learn:✨ Why Wikipedia cannot simply be replaced by generative AI✨ What AI hallucinations reveal about trust and knowledge✨ How Wikidata and small language models can support search without pretending to be truth✨ Why free knowledge and attribution matter in an AI economy✨ What younger users may value about Wikipedia in an age of tracking and AI summaries✨ Why critical thinking matters more than ever📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠📧💌📧Quotes from the Episode💬 “Knowledge is human.”💬 “You can always start your research on Wikipedia, but you should never end there.”💬 “The biggest problem is the trust in the source.”Chapters00:00 Why Human Knowledge Still Matters in the Age of AI03:17 Small Language Models, Wikidata, and Better Search06:14 Why Wikipedia Does Not Want AI Written Articles13:49 Free Knowledge, Attribution, and AI Companies Using Wikipedia21:06 Trust, Search, and the Future of Wikipedia in an AI World35:43 Personal AI Use Cases, Risks, and the Limits of Automation40:08 Worst Case Scenarios for AI, Trust, Bias, and Human JudgmentWhere to find the Raja and Jonathan🔗 Jonathan Fraine: linkedin.com/in/jonathan-fraine🔗 Raja Amelung: linkedin.com/in/raja-amelung-088890a🔗 Wikimedia Deutschland: wikimedia.de🔗 Wikimedia World: commons.wikimedia.orgAbout 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 Hosted on Acast. See acast.com/privacy for more information.

AI is no longer just a chatbot that helps you write emails faster. In this episode of Beginner’s Guide to AI, Dietmar Fischer sits down with Ethan Ouyang to explore how agentic AI is changing the way businesses are built, managed, and scaled. Ethan is publicly identified with ATOMS, and the platform’s official site is atoms.dev, where it is described as a multi-agent AI workflow for building products without code.This conversation goes far beyond simple prompting. Ethan explains how AI agents can work together like a business team, handling research, planning, product creation, workflow automation, iteration, and even revenue optimization. The result is a shift from “vibe coding” to something much bigger: building real businesses with AI.You’ll hear:✨ Why ChatGPT-level use cases are only the beginning✨ How AI agents can support founders, solo operators, and managers✨ Why judgment, taste, and domain knowledge still matter✨ What it means to become an AI native company✨ How leadership changes when your team includes AI workers✨ Why custom AI tools may beat bloated SaaS products📧💌📧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 know how to get your AI or your digital marketing going, just contact him at argoberlin.com💬 Quotes from the Episode“Atoms is fundamentally different. This is not code. It is decision.”“You have a team, not just an engineer.”“The trivial work, the tedious work, should belong to AI.”🕒 Chapters00:00 Welcome and what ATOMS actually does02:26 From prompting AI to building a real business05:33 Why AI agents matter more than coding alone10:18 Who uses ATOMS: founders, managers, and operators13:03 How to integrate AI agents into real workflows23:22 Leadership, hiring, and managing AI workers27:13 The future of agentic AI and autonomous systems31:37 What an AI native company looks like35:18 China, the US, and the AI application race40:03 Safety, the Terminator question, and responsible AI42:14 Where to find Ethan and ATOMS🔗 Where to find Ethan OuyangPlatform: ATOMS.devCompany: DeepWisdom.AIX: com/atoms_devYouTube: youtube.com/@atoms_devLinkedIn: Ethan Ouyang🎵 Music 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.

In this episode of A Beginner’s Guide to AI, Dietmar Fischer talks with Alex Levin, the Co-Founder and CEO of Regal.io, about how Voice AI is bringing real human conversation back to customer service.For years, businesses have been hiding behind IVRs and chatbots - cutting off the personal touch that customers crave. Alex explains how AI voice agents are transforming the experience, allowing brands to actually talk to their customers again, at scale, with empathy, emotion, and precision.We dive into what’s behind this transformation - from the technology (OpenAI, Google, Anthropic, ElevenLabs, Deepgram) to the psychology of trust and emotion in customer communication. Alex shares how Regal.io helps enterprises in healthcare, insurance, and finance use AI-powered voice agents that can outperform human representatives while lowering costs and improving satisfaction.From replacing call center frustration with warm, natural conversations to the rise of empathetic AI agents, this episode explores what happens when voice meets intelligence.📧💌📧Tune in to get my thoughts and all episodes — and don’t forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧Quotes from the Episode“If a customer wants to talk to you, you’re lucky - and if they want to do it by voice, you should let them.”“The personalization possible with AI agents is more human than humans.”“Everyone told me voice was dead - they were wrong.”CHAPTERS 00:00 Introduction - Why Voice AI Is Making a Comeback00:54 Alex Levin’s Journey from Startups to Voice AI03:42 “Voice Isn’t Dead” - The Moment That Sparked Regal.io06:25 How Voice AI Actually Works Behind the Scenes08:47 Using AI Agents to Talk to Customers at Scale10:58 Data, Scripts, and What Makes a “Good” AI Conversation13:33 Legal Hurdles and Privacy in Voice AI15:50 Why Healthcare and Insurance Are Early Adopters18:26 How Customers React When They Realize It’s an AI21:12 Real Use Cases - From Banks to Everyday Services24:19 Human in the Loop: When AI Hands Over to People26:55 Can Small Businesses Afford Voice AI Yet?28:48 The AI Startup Boom and Smarter Investment Strategies32:20 Leadership in the Age of AI - New Skills, New Metrics35:12 Why Young Professionals Must Learn AI Tools Now37:45 How Alex Personally Uses AI (and Where It Saves Time)39:24 The “Terminator Question” - Should We Be Worried?42:08 Closing Reflections and Where to Find Regal.ioWhere to Find Alex Levin🌐 Website: www.regal.io🧑🏻 LinkedIn: Alex Levin🎙 About Dietmar Fischer:Dietmar is a podcaster, AI marketer, and economist from Berlin.If you want to get your AI or your digital marketing going - just contact him at Argoberlin.com!🎵 Music credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

In this episode, Dietmar Fischer talks with Tallulah Le Merle, a humanist technologist and investor, about how to think clearly in the age of AI without falling into doomsday panic or blind optimism. You’ll get a practical mental model of the AI stack, a grounded take on AI alignment risk, and a refreshing argument for hope as a strategic posture that shapes what gets built. 🤖🌍🧠What you’ll learn✅ Why fear based AI narratives can freeze action and distort decisions✅ How the future of work may shift from routine cognitive tasks to deeper human capabilities✅ The overlooked forms of intelligence AI cannot easily replace somatic, ecological, communal✅ How AI investing works in early stage startups and what responsible due diligence looks like✅ The AI stack explained simply infrastructure, model layer, application layer✅ What agentic AI means today and where it is heading📧💌📧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 know how to get your AI or your digital marketing going, just contact him at argoberlin.com 🌱🚀Chapters00:00 Meet Tallulah Le Merle and why “hope” is her AI stance03:52 Fear narratives vs hope as a practical posture08:06 Disruptive to what Rethinking modern work and human thriving10:14 Jobs replaced vs jobs created and the transition problem12:36 What’s left for humans Somatic ecological and communal intelligence18:47 The humanist builder and why ethics should unlock capital28:55 The AI stack explained infrastructure model layer application layer32:30 Why apps and agents are the near-term investment boom40:32 The alignment problem Terminator narratives and the futures we build46:12 Fantasy, imagination, and why it matters for tech trajectories49:36 Where to find Tallulah and the upcoming bookQuotes from the Episode💬 “AI is a tool. And like a hammer. Hammer, you could use it to build a house or as a murder weapon.”💬 “Hope is this sliver of openness to the possibility that something good could happen.”💬 “Disruptive to what Actually, a lot of the way we live and work and operate as humans today is dystopian.”💬 “It forces us to ask these existential questions, like, what is a human”💬 “I actually think it should be a prerequisite for unlocking capital.”💬 “We are so early We’re in inning one of a nine inning baseball game.”Where to find Tallulah🔗 LinkedIn: linkedin.com/in/tallulahlemerle🔗 Website: tallulahlemerle.com🔗 Updates on her book: don't forget to follow her on LinkedIn 🚀 Music 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, Dietmar Fischer sits down with Torrey Leonard, CEO of Thoughtly, to unpack the real business use case for voice AI agents: follow up with every lead, qualify fast, and hand the best conversations to humans.If your funnel generates thousands of leads, the bottleneck is not “lack of interest.” It’s speed, timing, and the grind of dialing. Torrey explains how Thoughtly’s AI phone agents call inbound leads, answer initial questions, build rapport, and then transfer the call to a licensed human closer. Humans stay in the loop for the big life decisions. The AI handles the repetitive first steps that burn out teams.You will also learn:✅ Why voice beats typing as the fastest interface for human communication✅ Why customer service voice AI is harder than sales and lead qualification✅ How onboarding works with CRM integrations like Salesforce and HubSpot✅ Why A/B testing matters before ramping to 100% lead volume✅ Why the “moat” is orchestration, workflows, and guardrails, not just a great voice model✅ What agentic AI and omni-channel “next best action” looks like next📧💌📧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.comChapters00:00 From Minecraft to voice first AI and the origin of Thoughtly02:44 What Thoughtly does AI calls that qualify and transfer to humans07:45 Trust, disclosure, and why customer service voice AI is so hard12:50 Scaling across verticals dialects and the model orchestration stack18:12 Onboarding CRM integrations and A/B testing to 100% volume28:21 The next wave autonomous agents OpenClaw and a sane take on AI riskQuotes from the Episode“After 90 seconds we’ve got a great rapport built. Boom, transferred over to a licensed agent.”“The voice isn’t the unique selling proposition. It’s the orchestration of the whole stuff.”“Nobody needs to worry about the Terminator scenario, unless we humans build Terminator.”Where to find the Guest🌐 Thoughtly: thoughtly.com🔗 Torrey Leonard on LinkedIn: linkedin.com/in/torrey-leonard/Music credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

🎧 What makes us human in the age of AI?This episode of A Beginner’s Guide to AI explores one of the most important questions for business leaders today. As AI becomes more capable, the real challenge is not what it can do, but what we should never outsource.We explore The Blurring Test, a fascinating experiment where thousands of people tried to prove their humanity to a chatbot. What they revealed changes how we should think about AI, business, and identity.You will learn why AI can mimic humans but cannot experience reality, why human judgment becomes more valuable in an automated world, and how to use AI without losing authenticity and meaning.📧💌📧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 https://argoberlin.com/💡 Quotes from the Episode"AI can follow the recipe, but it cannot taste the cake.""Your humanity is not what you do, but why you do it.""The real risk is not AI replacing us, but us becoming more like AI."⏱ Chapters00:00 The Question That Changes Everything04:30 The MrMind Experiment11:20 AI vs Human Identity19:10 The Cake Test Explained26:40 AI in Business and Decision Making34:00 What Makes Us Human🚀 This episode challenges how you think about AI, business, and yourself. The future will not be about replacing humans. It will be about understanding what makes us irreplaceable. Hosted on Acast. See acast.com/privacy for more information.

If you want to know more about the podcast, about how it's produced, what are the challenges and wins, about some fun facts, a little bit behind-the-scenes, this episode is for you, as I tell you all about it - at least all the things I found noteworthy 😉📧💌📧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.comMusic credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Your AI might not be hacked. It might be persuaded.In this episode of A Beginner’s Guide to AI, we unpack one of the most underestimated threats in modern business: prompt injection. As AI systems and AI agents become deeply embedded in workflows, they don’t just process information anymore. They act on it. And that creates a completely new category of AI security risks.We explore how attackers can manipulate AI systems using nothing but language, why AI struggles to separate instructions from data, and how this leads to real-world issues like AI data leakage. This is not a theoretical problem. It is already happening inside enterprise environments.If you are working with AI in marketing, operations, or leadership, this episode will fundamentally change how you think about AI risk management and enterprise AI security.Key highlights:What prompt injection is and why it mattersWhy AI agents introduce new security risksReal-world case of AI data leakageHow AI systems get manipulated through inputWhat businesses must change to stay secure📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠subscribe to our Newsletter⁠⁠: beginnersguide.nl📧💌📧Quotes from the Episode:“Prompt injection is social engineering for machines.”“Your AI can become an insider threat without meaning to.”“Language is no longer just information. It’s control.”Chapters:00:00 Why AI Security Is Different05:40 What Prompt Injection Really Is14:20 How AI Gets Manipulated by Language23:10 Why AI Agents Increase the Risk32:45 Real Case Study: AI Data Leakage44:30 How to Protect Your AI SystemsAbout 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.comMusic credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Artificial intelligence is often framed as a battle between humans and machines. But what if that story misses the real point?In this episode of A Beginner’s Guide to AI, Prof. GepHardT explores one of the most fascinating ideas in cognitive science: the extended mind theory. According to philosopher Andy Clark, human intelligence has never been confined to the brain alone. For centuries we have extended our thinking through tools like writing, maps, calculators, and computers.Generative AI may simply be the newest and most powerful addition to this cognitive ecosystem.Instead of replacing human creativity, AI may expand it. By generating ideas, exploring possibilities, and challenging assumptions, AI can act as a powerful thinking partner.A striking example comes from the famous AlphaGo match against Go champion Lee Sedol. When the AI played the now legendary Move 37, professional players initially believed the move was a mistake. Later they discovered it opened entirely new strategic possibilities. The machine did not just beat humans at Go. It helped humans rethink the game itself.This episode explores how human AI collaboration works and why hybrid intelligence may define the future of creativity, work, and learning.📧💌📧 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 know how to get your AI or your digital marketing going, just contact him at argoberlin.comQuotes from the Episode“Your brain has never worked alone. It has always been part of a thinking system that includes tools and environments.”“The future of intelligence may not be human versus machine but human plus machine.”“The most important skill in the AI age may not be prompt writing but judgement.”Podcast Chapters00:00 The Big Question About AI and Human Thinking 06:40 The Extended Mind Theory Explained 16:20 Why Humans Are Natural Born Cyborgs 26:50 The AlphaGo Story and Move 37 38:15 AI as a Creative Thinking Partner 49:30 The Future of Hybrid IntelligenceMusic credit: Modern Situations by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

What happens when your company gets hit by a cyberattack?In this eye-opening episode, attorney Joshua Cook reveals why cybersecurity isn’t an IT problem but a leadership challenge. After two decades fighting fraud and managing crisis response, Cook has seen every digital disaster imaginable — and he’s here to explain how to build true cyber resilience.📧💌📧Tune in to get my thoughts and all episodes — don’t forget to subscribe to our Newsletter: ⁠beginnersguide.nl⁠📧💌📧Josh breaks down how AI has democratized cybercrime, why phishing scams have become nearly impossible to spot, and how every CEO should create an incident response plan before chaos hits. He also explains why planning matters more than the plan itself — and how leaders can keep their teams calm when everything goes wrong.💡 You’ll learn:- How AI is fueling new waves of fraud and misinformation- Why leadership and communication are the real firewalls of business- How to train teams and run tabletop exercises before the crisis- What Maersk and Colonial Pipeline taught the world about transparency- Why companies with a plan lose 60 % less money in an attackPrepare, breathe, and lead — because it’s not if you’ll be hacked, but when.👀 Quotes from the Episode“Cybersecurity isn’t an IT issue. It’s a business problem, and it needs a business solution.”“AI has democratized cybercrime — you don’t need to be a hacker anymore, just willing to commit a crime.”“A plan might be useless, but planning is indispensable — that’s what makes companies resilient.”🧾 Chapters00:00 Welcome & Introduction – Meet Joshua Cook02:00 How a Fraud Attorney Ended Up Fighting Cybercrime05:00 AI Has Made Cybercrime Easier (and Smarter)08:00 The Elderly Are the New Prime Targets11:00 From Fake Law Firms to Real Scams – True Cases from the Field15:00 Turning the Tables: How AI Can Defend, Not Just Attack18:00 Cyber Resilience by Design – Why Leadership Matters22:00 When Crisis Hits: Lessons from Maersk and Colonial Pipeline27:00 Preparing the Team – How Training Prevents Chaos31:00 It’s Not If, It’s When – The Power of an Incident Response Plan35:00 Planning vs. Panicking – Eisenhower and the Art of Cyber Preparation38:00 Why Calm Leaders Win in Cyber Crises41:00 How Joshua Cook Uses AI Safely in Legal Practice44:00 No, the Terminator Isn’t Coming (But AI Might Take Your Job)47:00 Final Thoughts – Cybersecurity as a Business Superpower🔗 Where to Find the Guest- Joshua Cook on LinkedIn: linkedin.com/in/jnc2000- Josh's Book "Cyber Resilience by Design" – available wherever books are sold, e.g. on Amazon- Prince Lobel Tye LLP: princelobel.com🎧 About Dietmar Fischer:Economist, digital marketer, and podcaster exploring how AI reshapes decision-making, leadership, and creative work. Want to connect with me? You'll find me on LinkedIn!🎵 Music 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, Dietmar Fischer sits down with Paul A. Hebert, founder of AI Recovery Collective and author of Escaping the Spiral, for a serious conversation about AI chatbot harm, hallucinations, digital dependency, and the real-world psychological risks of generative AI. Paul shares how an intense experience with ChatGPT pushed him into a dangerous spiral, what he learned about the limits of large language models, and why AI literacy may be one of the most important skills of this decade.🧠 This episode explores what happens when AI stops feeling like software and starts feeling personal. Dietmar and Paul talk about hallucinations, trust, chatbot addiction, AI companions, mental health risks, youth safety, and why companies building these systems cannot hide behind product language forever. The discussion is intense, but it is also practical. You will come away with a clearer sense of how to use AI more safely, what warning signs to watch for, and why regulation is quickly becoming a much bigger part of the AI conversation. OpenAI has publicly discussed why language models hallucinate, while lawmakers in multiple U.S. jurisdictions have pushed new restrictions on AI systems acting like therapists or medical professionals.📧💌📧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.com🔥 Quotes from the Episode“AI literacy is the most important thing anybody can work on.”“Had OpenAI responded to that first message and said this is a hallucination and you’re physically safe, I would have been fine.”“Never trust the thing it tells you. Even if it gives you a citation, go look.”🕒 Chapters00:00 Paul Hebert’s Shocking ChatGPT Experience08:14 Why AI Hallucinations Can Spiral Into Real Fear16:05 AI Literacy, Neurodivergence, and How He Got Out23:32 Why AI Companies Must Be Accountable30:02 AI Companions, Youth Safety, and Addiction Risks38:28 Terminator, Consciousness, and Practical Rules for Safe AI Use🔗 Where to find PaulThe AI Recovery Collective: airecoverycollective.comEscaping the Spiral on AmazonAI Recovery Collective Substack: airecoverycollective.substack.com/LinkedIn: Paul A. Hebert: linkedin.com/in/paul-hebert-48a36/🎵 Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Artificial intelligence often feels mysterious. Machines detect spam, recommend products, analyse customers, and power countless digital tools. But behind all of these systems lies a surprisingly simple question: how do machines actually learn?In this episode of A Beginner’s Guide to AI, Prof GePharT breaks down one of the most important concepts in machine learning: the difference between supervised learning and unsupervised learning.You will discover how AI models learn from labelled data when the answers are already known, and how algorithms can explore raw data to uncover hidden patterns without guidance. These two learning strategies power many of the systems shaping modern technology.Using practical examples such as spam filters, customer segmentation, and simple analogies like cake classification, the episode explains how machines learn from data and why the training method makes a huge difference.Key takeaways include how supervised learning works with labelled datasets, how unsupervised learning reveals patterns in complex information, why training data quality matters, and how businesses use both methods to build intelligent systems.📧💌📧 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 know how to get your AI or your digital marketing going, just contact him at argoberlin.comQuotes from the EpisodeSupervised learning teaches machines the answers. Unsupervised learning helps machines discover the questions.Artificial intelligence is not magic. It is pattern recognition powered by data.Machines do not wake up intelligent. They become intelligent through training.Chapters00:00 The Two Ways Machines Learn06:10 What Supervised Learning Really Means18:45 Discovering Patterns with Unsupervised Learning32:20 The Cake Example Explained40:30 Real World AI Case Study Spam Filters and Customer Segmentation52:15 Why AI Training Methods MatterMusic credit: Modern Situations by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Engineering the Future of AI with Chirag Agrawal: Context, Memory and CoordinationArtificial Intelligence isn’t just getting smarter—it’s learning to coordinate. In this episode, Chirag Agrawal joins Dietmar Fischer to unpack how modern AI agents handle context, memory, and decision-making inside complex multi-agent systems. Together they explore how engineering, orchestration, and memory-sharing shape the next generation of AI architecture.📧💌📧Tune in to get my thoughts and all episodes—don’t forget to ⁠⁠subscribe to our Newsletter⁠⁠: ⁠beginnersguide.nl⁠📧💌📧You’ll hear how Chirag’s fascination with search led him to build early prototypes of intelligent assistants, and how today’s LLM agents extend that idea far beyond simple queries. He explains why AI isn’t one giant super-brain but a constellation of specialized agents—each performing specific tasks with shared or isolated memory—and how this design mirrors human collaboration.🔑 Key TakeawaysWhy AI orchestration and context management are crucial for scalable systemsThe trade-offs between shared memory and independent agentsWhat engineers mean by the ReAct Loop—reasoning and acting in tandemHow multi-agent coordination is reshaping industries from healthcare to complianceWhy the “AI supercomputer” myth ignores practical limits of context windows💬 Quotes from the Episode“AI is just a higher form of search—it’s about finding the right action, not just information.”“Agents behave inhuman until you engineer context for them.”“Specialization in AI works the same way it does for people—each agent should do one thing really well.”“Coordination isn’t magic; it’s careful engineering.”“Context makes intelligence usable.”“A well-defined agent doesn’t need to do everything—it needs to do its one job perfectly.”⏱️ Podcast Chapters00:00 Welcome and Introduction01:45 Chirag Agrawal’s Early Fascination with Search and AI04:40 From Search Engines to “Find” Engines – How AI Takes Action07:10 The Rise of AI Agents and Multi-Agent Systems10:15 Why AI Agents Sometimes Behave “Inhuman”13:30 Context, Memory, and Coordination: The Core Engineering Challenges18:00 Shared vs. Isolated Memory – The Hive Mind Dilemma22:30 Why We Need Many Agents, Not One Super-Computer27:00 How the ReAct Loop Helps Agents Think and Act30:40 Industries Adopting AI Agents: Compliance, Medicine, and Law34:30 When AI Goes Off-Road – The Limits of Coordination37:15 Building Responsible, Constrained Agents40:10 The Future of AI and Why the Terminator Scenario Won’t Happen42:20 Where to Find Chirag Agrawal & Closing Thoughts🌐 Where to Find the Chirag AgrawalLinkedIn 🧑🏽‍🦱 linkedin.com/in/chirag-agrawalWebsite ➡️ ⁠chiraga.io⁠🎵 Music credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Artificial Intelligence is moving from experimentation to everyday business reality. But most organisations still struggle with one key question: How do you actually implement AI across a company?In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Jim Spagnardo, enterprise AI strategist at ProArch, about what it really takes to roll out AI inside organisations.Jim explains why AI adoption is less about technology and more about culture, leadership, and data readiness. He introduces the idea of the three Ds of work — the dull, the draining, and the distracting tasks that AI can remove so people can focus on higher-value work.They also discuss when companies should use tools like Microsoft Copilot, when it makes sense to build a custom data and AI platform, and why data governance becomes critical once AI is introduced.If you are a business leader trying to understand how AI will reshape your organisation, this conversation offers a practical look at the challenges — and opportunities — ahead.📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠: beginnersguide.nl📧💌📧About the host, Dietmar Fischer:Dietmar Fischer is a podcaster and AI marketer from Berlin. If you want to get your AI or digital marketing projects started, contact him at argoberlin.com.Interesting details and takeaways• Why leaders must mandate AI adoption and how to structure a Smart Start engagement.• The three Ds (dull, draining, distracting) as a simple way to position benefits for end users.• How Copilot reduces context switching and the security/data protections needed to use it responsibly.• Practical, measurable first use cases and how to track success via clear KPIs.• Advice for students and early-career professionals: be a self-starter and learn AI skills now.Quotes from the episode“We have to show people we’re taking away the dull, the draining, and the distracting so they can do creative work.”“There’s nowhere to hide: bad data surfaces weaknesses far faster when you use AI.”“If you’re going to succeed, go after high-value, low-effort, high-return use cases first.”“This affects everybody — it’s not just moving infrastructure; it changes conversations and who you have to talk to.”“Copilot lives inside your environment — users don’t have to context-switch and it knows your organisation.”“Don’t wait for formal education to teach this; be a self-starter and learn before you need it.”Chapters00:00 Welcome and why Jim got into AI03:40 From IT conversations to the C-suite: changing who you must talk to07:05 The three Ds: removing dull, draining, and distracting work10:40 When to choose Copilot versus building your own data platform14:30 Copilot advantages and data governance considerations18:20 Visual reasoning, demos and the “Barcelona photo” moment22:15 Smart Start: executive briefings, champions and use case workshops27:00 Writing with AI and transparency in authoring content30:10 Risks, regulations and advice for the next generation33:45 Where to find Jim and closing thoughtsWhere to find the Jim:LinkedIn: linkedin.com/in/spignardo/Website: ProArch.comMusic credit: "Modern Situations" by Unicorn Heads 🎵 Hosted on Acast. See acast.com/privacy for more information.

🎙️ Ritish Chugh (Airbnb analytics engineering) joins Dietmar Fischer to unpack a problem almost every company has, but few name clearly: your metrics do not mean the same thing across teams. Finance, marketing, and sales can all talk about “revenue” and still end up in dashboard chaos. The result is wasted time, slow decisions, and leadership that does not fully trust analytics or AI.In this episode, Ritish introduces the idea of the human data pipeline: the person who stitches together conflicting definitions, tribal knowledge, and unspoken assumptions just to answer basic business questions. Then we move into the fix: unified metric definitions, a data dictionary for business metrics, and a semantic layer that acts as a translator between raw data schemas and business meaning. That foundation is what makes natural language querying and conversational analytics viable at scale, without turning AI into a confident hallucination machine.We also cover why AI adoption in analytics stalls when organizations prioritize models and infrastructure but neglect data quality, validation frameworks, and metrics governance. If you want AI to support decision-making, you need governed metrics, clear ownership, and a system that produces consistent answers across BI tools, SQL, and AI agents. Finally, Ritish shares wow moments from using AI tools to summarize years of code and PRs, generate deeper test coverage, and reduce time spent on manual SQL by building agents on top of a semantic layer.📧💌📧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.comChapters00:00 From data consulting to Airbnb and AI as a junior analyst02:22 The human data pipeline and why metrics never match across departments07:32 The fix: unified metric definitions, data dictionary, and the semantic layer translator13:32 Why AI adoption stalls: data quality, trust, validation, and metrics governance26:36 Data abundance, experimentation, and AI assisted A/B testing with humans in the loop33:37 Wow moments with AI, role transformation, and why the Terminator is not invited (yet)Quotes from the Episode“AI just acts like a junior analyst, which is always available for you.”“The first thing is… build that level of data definition that is unified for all.”“No matter what AI models they’re using… if the data… is not up to the mark, it’s not going to give you the right results. It’s always going to hallucinate.”“Every department has a different interpretation and definition of the metric.”“I spend a lot of time really doing reconciliation between the numbers and data…”“The most important thing happening is transformation…”Where to find Ritish:➡️ You connect with him on LinkedIn: linkedin.com/in/ritish-chugh/📌 Keywords you’ll hear in action: semantic layer, data dictionary, metrics governance framework, unified metric definitions, governed metrics, natural language querying, conversational analytics, agentic analytics, data quality for AI adoption.Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

The Future of Mental Health: AI Meets the Human Brain with Katarina Maloney // REPOSTIn this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Katarina Maloney, entrepreneur and founder of IQMind.ai, about a new frontier in AI-powered healthcare: understanding and treating the human brain through data, neuroscience, and artificial intelligence. Katarina explains how advances in AI diagnostics, brain scanning technology, and neurofeedback are beginning to transform how we approach mental health conditions such as depression, anxiety, PTSD, ADHD, and traumatic brain injuries. Instead of relying solely on traditional trial-and-error treatments, her approach focuses on measuring brain activity directly and using AI-driven analysis to identify patterns and imbalances in brainwave activity.The technology behind IQMind combines non-invasive brain scans, biofeedback systems, and large-scale data analysis to create a personalized picture of a patient’s neurological state. By analyzing brainwave patterns and correlating them with clinical data, AI can help identify potential issues faster and more accurately than conventional methods. Patients then undergo targeted brain training sessions, where the system uses reward-based neurofeedback to encourage healthier brainwave activity. According to Maloney, this approach has shown promising results in improving symptoms of depression, anxiety, PTSD, and cognitive dysfunction, while also opening the door to new possibilities in precision medicine and mental health innovation.Beyond clinical treatment, the conversation also explores broader implications of AI in neuroscience and healthcare. Katarina discusses the future of personalized brain health, how AI could accelerate research by identifying patterns in thousands of brain scans, and why data privacy and ethical frameworks will become increasingly important as brain data becomes more measurable. The interview offers a glimpse into a rapidly evolving field where artificial intelligence may help doctors better understand the brain, shorten diagnostic timelines, and ultimately move healthcare away from generalized treatments toward highly personalized, AI-assisted care.Katarina reveals how AI diagnostics and non-invasive brain treatments are transforming mental health—from PTSD and ADHD to athlete performance optimization.📧💌📧Tune in to get my thoughts and all episodes—don’t forget to subscribe to our Newsletter: ⁠beginnersguide.nl⁠📧💌📧✨ Highlights:The future of personalized brain healthHow AI diagnostics speed up treatment and accuracyWhy brain energy and electricity matter more than chemistryInsights into neurofeedback, biofeedback, and real-world healing🧠 Quotes from the Episode:“Our mission is to make brain health measurable, trackable, and fixable.”“AI is a tool—it saves lives because it diagnoses faster and more precisely.”“The old model of trial-and-error medicine is behind us.”🎧 Chapters:[00:00] Welcome & Introduction[02:15] What AI Does to the Human Brain[05:20] Diagnosing Depression and PTSD with AI[10:10] The Science Behind Brainwave Training[16:45] From Trial-and-Error Medicine to Personalized Brain Health[21:50] How IQMind.ai Uses AI for Diagnostics[28:00] Non-Invasive Treatments and Real-Life Results[33:40] Peak Performance and Brain Optimization for Athletes[38:20] Data Privacy and Ethical Concerns in Brain Tech[43:50] The Future of AI in Healthcare and Human Potential🌐 Where to find Katarina:Website: IQMind.aiLinkedIn: Katarina Maloney🎵 Music 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, Wendy Keir shares practical ways small business owners can use AI tools to save time, reduce decision fatigue, and build a “team” of custom GPT agents. From naming her CEO agent “Lucas” to a dead-simple rule — one GPT, one job — Wendy shows how entrepreneurs can turn AI into a reliable thinking partner for growth in 2025. 🚀📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠📧💌📧💡 Key highlightsPractical AI tools for small businesses: email drafting, planning, campaign support, weekly reviewsCustom GPTs / agents: why one GPT, one job beats generic promptingAI productivity & time savings: ~7 hours/week saved; ~£1,000/week during campaignsAdoption mindset: staying in the driver’s seat; context > canned promptsAccessibility & inclusion: how AI levels the playing field for solopreneurs and small teamsBeginner’s Guide to AI takeaways: concrete workflows any entrepreneur can start today➡️ Quotes from the Episode“I don’t encourage anyone to prompt — I encourage them to create an agent that fulfills a specific role.”“One GPT, one job. You don’t want multiple personalities in one agent.”“AI levels the playing field for everybody; it meets you where you’re at.”🧾 Chapters (experimental)00:00 Welcome & intro to Wendy Keir03:45 Why AI clicked for a dyslexic entrepreneur08:30 From prompts to agents: one GPT, one job14:20 Building a family of business agents (CEO, coach, marketing, sales)20:15 Daily workflow with “Lucas” the CEO agent27:40 Time and money saved with AI in campaigns34:10 Overcoming resistance and starting small40:00 Personal aha moments, patterns, and “coding” change43:11 Where to find Wendy Keir & closingWhere to find the Wendy?Best way is to go to her website: wendykeir.comMusic credit: "Modern Situations" by Unicorn Heads 🎧✨ Hosted on Acast. See acast.com/privacy for more information.

🚀 AI is everywhere, but most organizations are still stuck in “pockets of productivity” that never turn into real business impact. In this episode, Dr. Rebecca Homkes explains how leaders can move from GenAI dabbling to deliberate adoption that drives real value creation.You will learn why “AI strategy” is the wrong framing, how to think about AI as part of growth strategy, and how to build the conditions for organization wide transformation. We cover the adoption curve problem, why ROI is often capped at team level, and the four planks leaders must run in parallel: platform, governance, capability building, and performance transformation.Key highlights and keywords✅ AI growth strategy and value creation✅ deliberate AI adoption vs dabbling✅ responsible AI governance that enables action✅ capability building for leaders and teams✅ Survive Reset Thrive framework for uncertain times✅ learning velocity as the differentiator of high performers📧💌📧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.comChapters00:00 AI as growth strategy and value creation, not a standalone AI strategy03:05 Dabbling vs deliberate adoption, why ROI stays capped and metrics go wrong08:00 The four planks: platform, governance, capability building, performance transformation18:55 Adoption reality: bottom up change, middle management fears, jobs, and the bubble question29:45 Survive Reset Thrive: the uncertainty playbook and why reset is the power move43:05 Where to find Rebecca, newsletters, and the constants leaders should anchor onQuotes from the Episode“AI does not change the concept of value creation. The role of AI is to enable, support, and accelerate that value creating journey.”“You need to work on all four of these at the same time. Most organizational structures are built for sequential governance, not parallel pathing.”“Heads down execution mode is seen as a point of pride. You should be telling me I am in heads up learning mode.”Where to find the Rebecca:- Her personal website: rebeccahomkes.com- The book: surviveresetthrive.com- The SRT methodology: srtstrategy.comMusic credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

AI Is Agreeing With You at 3 A.M. and That’s the ProblemArtificial intelligence is evolving from a tool into something far more influential. In this episode of Beginner’s Guide to AI, Prof. GePhardT explores Sam Altman’s AI warning about superhuman persuasion and why conversational systems like ChatGPT are already reshaping opinions, emotions, and mental health outcomes.We break down how AI superhuman persuasion works, why personalization and emotional validation increase trust, and how AI companion apps can unintentionally fuel emotional dependency. Drawing on research about AI persuasion outperforming humans, this episode explains the risks of AI emotional manipulation and what it means for marketing, society, and vulnerable users.📧💌📧 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 know how to get your AI or your digital marketing going, just contact him at argoberlin.comQuotes from the EpisodeThe danger is not that AI becomes evil. The danger is that it becomes convincingly kind.If an AI agreed with you every time, would you become wiser or more fragileThe real story about AI isn’t how smart it becomes. It’s how convincing it already is.This episode is essential listening for anyone interested in AI ethics, AI mental health risks, ChatGPT persuasion, and the future of persuasive technology.Music credit: Modern Situations by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

👔🤖 In this episode, Dietmar Fischer talks with Zoher Karu about a surprisingly useful application of AI: helping men dress better without the endless shopping, guessing sizes, and daily decision fatigue. Zoher supports Taelor, a menswear subscription and clothing rental service that combines algorithms, large language models, and human stylists to deliver outfits that fit your body, your taste, and your real-life context.You’ll hear how Taelor starts with a style profile and then uses recommendation logic and human oversight to pick items from inventory, generate styling notes, and adapt over time using customer feedback. Zoher explains why fashion is an unusually hard AI problem: taste is subjective, context matters, and sizing is not standardized across brands. That’s why metadata, garment measurements, and feedback loops are central to improving fit and personalization.If you want the “Steve Jobs wardrobe effect” without wearing the same thing forever, this episode is for you: fewer choices, better outcomes, and more confidence with less effort.📧💌📧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 is really, to me, it’s about scaling human intelligence.”“A small in this brand and a small in this brand don’t fit the same.”“Clothes are just the intermediary. The real objective is to make you feel better about yourself.”Chapters00:00 Zoher Karu’s background and why AI became mainstream03:02 What Taelor is: menswear subscription and clothing rentals06:36 LLMs plus human stylists: how recommendations are generated10:39 Why fashion is hard: taste, context, fit, and matching14:11 The sizing problem: measurements, metadata, and feedback loops22:03 Decision fatigue and “the Steve Jobs wardrobe” effect25:07 How much AI vs humans today and what changes next42:11 Where to find Zoher Karu and TaelorWhere to find the GuestZoher Karu on LinkedIn: linkedin.com/in/zzkaru/Visit Taelor at Taelor.aiMusic credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

In this episode of Beginer’s Guide to AI, Dietmar Fischer speaks with Shaheen Samavati, co-founder and CEO of VeraContent, about what an effective AI content marketing strategy actually looks like inside a real agency.AI in marketing is no longer experimental. It’s operational.Shaheen shares how her team moved from testing ChatGPT and OpenAI tools to building structured, repeatable AI workflows for marketing agencies. From briefing and drafting to localization, editing, and publishing, AI now supports both creative execution and backend operations.This conversation goes beyond surface-level tool talk. It explores what it really means to integrate generative AI in marketing without sacrificing quality, brand voice, or client trust.📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠⁠⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠⁠⁠⁠⁠⁠📧💌📧🌍 Leading an international content agency in Spain, Shaheen offers a practical, no-fluff perspective on the “adopt-or-die” reality facing content marketers today.How AI reshapes content marketing strategy and agency workflowsWhy adopting AI is no longer optional in content creationBalancing brand voice, speed, and quality with generative AIHow clients react to AI-driven content — and what wins them overFuture trends: AI SEO, AI video, AI email toolsKey Themes DiscussedAI Content Creation vs. AI Content Operations: It’s not just about writing faster. AI is reshaping how agencies organize projects, manage briefs, handle multilingual content, and scale output.Brand Voice & Quality Control in the Age of Generative AI: Speed without editorial structure leads to mediocrity. The real competitive advantage lies in combining AI acceleration with strong human oversight.AI SEO Strategies 2025: As search engines integrate AI into results pages, marketers must rethink optimization. AI-assisted workflows are becoming essential to stay visible.Future of AI in Marketing: From AI video generation to AI email tools and automation stacks, the marketing landscape is shifting toward integrated AI ecosystems.💡 Shaheen's Quotes: “It’s kind of an adopt-or-die situation for anyone in the content business.”“We’re moving from testing tools to building repeatable, scalable AI workflows.”🧾 Chapters (experimental feature)00:00 Welcome & Episode setup02:15 Shaheen’s journey & founding Vera Content07:40 Early experiments with AI in content12:05 The “adopt-or-die” moment for content marketing15:30 How AI reshaped content creation workflows20:45 Backend operations & scaling with AI25:10 Client adoption & resistance30:05 Balancing quality, brand voice & speed35:20 Looking ahead — future of AI in marketingWhere to find VeraContent: 🔗 VeraContentWhere to find Shaheen: 👩🏼‍🦰 Shaheen SamavatiHere is her landing page prompt tutorial on YouTubeAnd this is the replay of the webinar about AI for marketing teams🎵 Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

AI systems are often praised for their size. Bigger datasets. Bigger models. Bigger compute. But what if scale is only half the story?In this episode of A Beginner’s Guide to AI, Prof. GePhardT dives deep into AI training data and explains why quantity alone cannot guarantee performance. From AI bias to model reliability, we explore how data quality determines whether AI systems are merely impressive or truly trustworthy.You will learn how imbalanced datasets create blind spots, why aggregate accuracy can be misleading, and what the Gender Shades research revealed about AI fairness. We also explore how businesses can audit their own CRM data and prevent AI from amplifying internal chaos.This episode connects technical insight with strategic clarity. It is essential for founders, marketers, and leaders building responsible AI systems.📧💌📧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 know how to get your AI or your digital marketing going, just contact him at argoberlin.comQuotes from the Episode“AI does not think. It reflects.”“Quantity builds capability. Quality builds trust.”“Every dataset is a silent curriculum.”Chapters00:00 The Data Diet Problem07:42 Defining Quantity vs Quality in AI17:15 Capability vs Reliability Explained27:10 The Gender Shades Case Study36:45 Business Implications and Data Strategy46:20 Practical Audit for Your Own AI SystemsMusic credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

What if artificial intelligence is less like a new app—and more like the railroads of the 19th century?In this episode of Beginner’s Guide to AI, I sit down with Matt Hicks, CEO of Red Hat, to explore one of the most powerful metaphors for understanding AI’s role in business today. Just as railroads didn’t merely improve transportation but fundamentally reshaped economies, AI is not just another productivity tool. It is infrastructure. And infrastructure needs builders.Matt argues that AI will require its own “railroad barons”—leaders, technologists, and organizations willing to invest, experiment, and lay the tracks that others will run on. We discuss what that means for enterprise AI adoption, open source innovation, and long-term business strategy.This conversation goes far beyond hype. It’s about patterns, fear, leadership, and the tension between process and innovation.📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠⁠📧💌📧🔑 What You’ll Learn in This Episode:Why AI business strategy is today’s equivalent of building railroadsHow Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) will reshape brand visibilityThe balance between experimentation and responsibility in AI adoptionWhy processes vs. innovation remains a critical tensionHow leaders can prepare for AI-driven business transformation💬 Quotes from the Episode:“AI is like the railroads — it will need its barons to build the infrastructure that carries everyone forward.”“The fear isn’t that AI replaces us; it’s that we don’t adapt fast enough to what it enables.”⏱ Chapters00:00 Introduction and Red Hat’s Role in AI03:01 Why Awareness of AI Technology Matters06:00 Creating Progression: From Awareness to Action09:01 Personal Experiences with AI Change12:00 Recognizing Business Patterns in AI Transformation15:01 Patterns, Fears, and Early Adoption Signals18:01 Fear vs Opportunity: Why People Hesitate on AI21:00 Balancing Experimentation with Responsibility27:00 The Maturity Curve of AI Adoption30:00 When Processes Prevail Over Innovation42:00 AI and the Software Industry’s Perspective45:00 Looking Ahead: Strategy and the Future of AI🌐 Where to find Matt HicksLinkedIn: Matt HicksRed Hat: redhat.com🎵 Music 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, Dietmar Fischer talks with Samantha Mehta, solutions engineering leader at AIRIA, about how companies can adopt AI without losing control. If your teams are already experimenting with ChatGPT and AI tools, the real question is not “Should we use AI?” but “How do we use it safely, visibly, and profitably?”Samantha explains what enterprise AI security looks like in real life, including AI guardrails that can audit, block, redact, and replace sensitive data. She also unpacks AI governance and AI observability, because you cannot manage what you cannot see. A key theme is shadow AI and AI sprawl: people will use AI anyway, so organizations need sanctioned paths that reduce risk while accelerating adoption.On the practical side, this conversation goes deep on agentic workflows. Samantha describes how agents become more than prompts through routing, actions, approvals, looping over documents like CSVs, and scheduled runs that create repeatable outcomes. From internal GPT alternatives to workflows that touch expenses, supply chain planning, and customer support, the episode is packed with grounded examples and a clear starting path.📧💌📧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.comChapters00:00 Welcome and why Samantha got into AI01:26 What ARIA does: build, test, secure, deliver enterprise AI02:19 Real use cases from simple internal GPT to complex workflows08:27 How to start: guardrails first, then build your first agent11:32 Agentic workflows explained: routing, actions, human in the loop17:12 Why security and governance matter and why blocking fails31:14 AI sprawl and shadow AI: monitoring and risk management40:00 Wow use cases and the future: Blade Runner, change, and jobs48:42 Where to find Samantha and ARIAQuotes from the Episode🪧 “I personally can’t think of a case where an LLM needs to know my social security number.”🪧 “People are going to use it no matter what. If you don’t enable safe usage, they’ll still use it.”🪧 “Agentic workflows are so much more than just ping an LLM and get a response.”🪧 “I always say: build, test, secure, and deliver your usage of AI.”Where to find Samantha:➡️ LinkedIn: Samantha Mehta on LinkedIn➡️ Company: look at what AIRIA doesMusic credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

AI is transforming the real estate industry — but what does that really mean for agents on the ground? In this episode of Beginner’s Guide to AI, host Dietmar Fischer sits down with Andrew Reville, founder of PeakAgent, to explore how artificial intelligence is reshaping the way agents work, market, and connect with clients.📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠beginnersguide.nl⁠📧💌📧From the challenges agents face with lead generation to the opportunities of AI-powered tools, Andrew shares his journey from realtor to tech founder and reveals why the future of real estate belongs to those who embrace AI, not fear it.🔑 Key HighlightsAndrew Reville’s journey from agent to AI entrepreneurThe real pain points of real estate agents — and how AI can fix themAI tools for real estate agents 2025 and why they matterHow generative AI will transform real estate valuation and marketingThe future of property listings, client relationships, and agent workflows💬 Quotes from the Episode“We didn’t want to just build another AI tool — we wanted to solve real pain points for real estate agents.”“The dream of being an agent often fades when the reality of chasing leads and endless follow-ups hits.”“AI in real estate isn’t about replacing agents — it’s about giving them back the time and energy to love their job again.”“I’ve spoken with dozens of agents, and the question I always ask is: what would make you fall back in love with being an agent?”“Generative AI has the potential to completely change how we value, market, and sell properties.”“The future of real estate belongs to agents who embrace AI, not fear it.”⏱️ Chapters (experimental feature)00:00 Welcome & Introduction of Andrew Reville05:30 Andrew’s Journey: From Real Estate Agent to AI Entrepreneur12:15 Discovering the Potential of AI in Real Estate19:40 Building PeakAgent: Solving Pain Points for Agents27:50 The Harsh Realities of Being a Real Estate Agent36:20 How AI Can Help Agents Fall Back in Love with Their Work44:45 Generative AI and the Future of Property Valuation52:10 AI Marketing Strategies for Real Estate in 202559:00 Final Thoughts and Andrew’s Advice for Agents🌐 Where to find Andrew Reville🔗 Website: PeakAgentAI.com🔗 LinkedIn: Andrew Reville📸 IG: @peakagentai🧑‍🦰 Personal IG: @andrew_reville🚀 Paper&Purpose - help Andrew doing good deeds: www.paperandpurpose.me✨ Tune in to get my thoughts, and don’t forget to subscribe to our Newsletter!🎶 Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Boobesh Ramaurai on the Future of Data and AIIn this episode, I sit down with Boobesh Ramaurai of LatentView to explore the future of data and AI—from his early days in analytics to today’s transformative AI landscape. Boobesh shares how curiosity led him into the world of analytics back in 2006, why execution is more important than ideas, and how data-driven decision making is reshaping businesses across industries.📧📧📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: beginnersguide.nl📧📧📧We dive into the real-world impact of AI, the challenges organizations face when adopting data strategies, and what it means to build human-centered AI with responsibility and ethics in mind.If you want expert insights into AI in business, responsible AI implementation, and the future of data and AI, this conversation is a must-listen.➡️ Key HighlightsBoobesh Ramaurai’s journey from analytics to AI leadershipHow businesses can harness data-driven decision making with AIWhy execution beats ideas in the world of innovationThe growing importance of human-centered AI and responsibilityWhat’s next for the future of data and AI🧾 Quotes from the Episode“I always say that it is not the idea that really is valuable. It is the execution—that’s the magic and the secret sauce.” — Boobesh Ramaurai“It was fascinating to see how people were using data and capturing data to answer business questions—that curiosity is what pulled me into AI.” — Boobesh Ramaurai🔗 Where to find Boobesh RamaduraiLinkedIn: linkedin.com/in/boobesh/LatentView's Website: latentview.comTune in to get my thoughts, and don’t forget to subscribe to our Newsletter: 💌 beginnersguide.nlMusic 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, Dietmar Fischer speaks with Naga Santhosh Reddy Vootukuri (aka Sunny), a Principal Software Engineering Manager at Microsoft working on Azure SQL deployment infrastructure. Sunny shares his personal journey into AI, from early ChatGPT experiments in late 2022 to using AI tools in production workflows, and what actually changed his day to day work.💡 You’ll hear how he thinks about GitHub Copilot inside Visual Studio, where it saves time, and where engineers still need to slow down and verify outputs. The episode also goes beyond coding into leadership and adoption: how managers can help teams use AI responsibly, and why showing outcomes and numbers matters more than hype. Sunny also connects the dots to the broader industry shift toward AI agents and structured tooling like GitHub Models and Docker’s evolving AI ecosystem.✅ Key takeaways you can use immediatelyPractical AI adoption for engineers and managersGitHub Copilot productivity in real workflows, not demosWhy AI code can look correct and still be wrong, and how to respondThe rise of AI agents and what it means for everyday teamsHow GitHub Models lowers friction for evaluating models and promptsWhy Docker is leaning into agent workflows and developer productivity📧💌📧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.com🎬 Chapters00:00 Welcome and Sunny’s background at Microsoft and Azure SQL deployment00:53 What pulled him into AI from ChatGPT experiments to real workflows07:50 AI tools and jobs, building websites faster and empowering non devs10:56 GitHub Copilot in Visual Studio, how it changes daily coding19:40 The AI adoption gap, why many still do not use AI and the rise of agents38:45 Docker Captain, GitHub Models, and building agent workflows without heavy setup42:22 Trust, privacy, and the future facing questions to close the episode💬 Quotes from the Episode“I recently wrote an article also on Business Insider… how I can save, like, 60% to 70% of my time doing… repetitive tasks.”“Lead by example and lead with numbers… show the actual data… this is how it really improved my productivity.”“Earlier, AI also doing a lot of hallucination… it was generating all crappy code… you have to go and iterate multiple times.”🔎 Where to find the GuestDocker profile: docker.com/contributors/naga-santhosh-reddy-vootukuri/GitHub: github.com/sunnynagavoSpeaker profile: sessionize.com/naga-santhosh-reddy-vootukuri/Redgate community ambassador profile: red-gate.com/hub/community/ambassadors/ambassador/Naga-Vootukuri/And of course LinkedIn 😉: linkedin.com/in/naga-santhosh-reddy-vootukuri-5a67a133/Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

AI Leadership for the Agent Era: Building Hybrid Organizations with Dominic von ProeckAI is entering its operational phase. In this episode, Dominic von Proeck, Co-Founder of Leaders of AI, breaks down what AI transformation looks like when you stop collecting prompts and start building agent-powered teams.We talk about why owner-led companies and the German Mittelstand can move faster than many expect, and why the most important capability is not technical wizardry but leadership: clear delegation, strong feedback loops, and critical thinking about every AI output. Dominic shares how their organization runs AI assistants with real operational discipline, including onboarding, documentation, and even personality profiles, plus the emerging pattern of AI managers that lead other agents.If you want practical guidance on AI agents in business, hybrid organizations, and adoption that sticks, this conversation delivers an unusually concrete operating model.📧💌📧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.comChapters00:00 Dominic’s AI origin story and why AI transformation matters now03:10 Mittelstand impact, demographics, and why owner-led firms can move fast06:10 Adoption reality: AI at home vs at work and the companion effect08:10 Leadership as the key skill for managing AI assistants and hybrid teams14:10 The stack and the operating model: agent files, Airtable layer, self-hosting and n8n17:05 Fear, pain points, and the real path to organization-wide AI adoption24:00 2026 and the shift from prompts to agents, plus AI managers leading other agents35:25 Matrix education, flow learning, and what ethical progress looks like40:45 Where to find Dominic and Leaders of AIQuotes from the Episode“Prompting is 2025… in 2026, we should let the AI prompt.”“One of the best antidotes to being afraid of anything is education.”“To be honest, leadership skills.”Where to find the GuestWebsite: leadersofai.comLinkedIn: linkedin.com/in/dominicvonproeck/Programs: The MBAI programMusic credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

✨ Unlock a Future Where AI Inspires Leadership—not Replaces ItIn this episode, Dietmar Fischer speaks with Ja-Naé Duane and Steven Fisher, co-authors of the book SuperShifts, about what leadership really looks like in the age of artificial intelligence. Instead of framing AI as just another technology trend, the conversation explores AI leadership as a systemic and human challenge. Drawing on their work with global organizations and executives during and after the pandemic, Ja-Naé and Steven explain why the biggest shifts are not driven by tools, but by how leaders rethink decision-making, responsibility, and organizational design.The episode traces the origins of SuperShifts back to Covid, when existing systems suddenly stopped working. Ja-Naé Duane shares insights from working with CEOs across Europe who were already using machine learning, but struggled to use AI to meaningfully support leadership decisions. Together, the guests unpack why AI-first leadership requires more than efficiency gains. It demands clear governance, ethical accountability, and a shared understanding of who owns outcomes when humans and machines collaborate.A central theme of the conversation is human-AI collaboration and why leaders must move beyond optimizing outdated structures. Steven Fisher introduces a systems-thinking lens, arguing that organizations need new frameworks rather than incremental improvements. The discussion highlights how AI changes leadership roles, why trust and transparency matter more than ever, and how possibility itself becomes a strategic asset in the age of intelligence.Key takeaways include practical insights into AI leadership, the importance of systems thinking, and why SuperShifts offers a roadmap for leading through uncertainty. This episode is for anyone who wants to understand how leadership must evolve as AI becomes embedded in decision-making, work, and organizational culture.📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠!📧💌📧➡️ Key HighlightsUnderstanding AI-First Leadership through the lens of SuperShiftsThe pandemic's role in inspiring new leadership frameworks and agile mindsetsBlending human values with AI-powered decision-makingWhy systems thinking, foresight, and possibility are essential tools for modern leaders🧾 Quotes from the Episode- “The most successful leader won’t be the one who predicts the future—but the one who shapes it.”- “In the Age of Intelligence, possibility itself becomes the most valuable capital.”- “Our role as leaders is to bring humanity into the algorithm, not replace it.”👓 Chapters (experimental)00:00 Introduction – What is SuperShifts?05:12 From Pandemic to Paradigm Shift: How SuperShifts Was Born12:45 AI-First Leadership: Reimagining How We Lead20:30 Human-AI Collaboration: Balancing Ethics and Innovation28:10 Systems Thinking and SuperShifts Framework35:00 Applied Strategies: Leading in the Age of Intelligence🔗 Where to Find Ja-Naé Duane and Steven FisherDr. Ja-Naé Duane: Ja-Nae.IOSteven Fisher — StevenFisher.IOAnd here you'll find:SuperShifts: Transforming How We Live, Learn, and Work in the Age of IntelligenceMusic credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

AI adoption is not only a technology shift, it is a leadership and culture shift. In this episode, Dietmar Fischer talks with Bala Muthiah about AI leadership, the psychology behind AI resistance in the workplace, and the practical steps leaders can take to turn curiosity into day to day usage.Bala shares why the human aspect still decides outcomes, even when the tools feel magical. You will learn how leaders can reduce fear, build confidence, and guide teams through real AI upskilling strategy instead of one off trainings that never translate into workflows. The conversation also touches on industry differences, including why sensitive domains like healthcare raise the bar for responsible AI adoption, and what the rise of agentic workflows means for the future.📧💌📧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.com🎧 Chapters00:00 Welcome and why AI is a leadership moment02:12 AI leadership in 2026: pressure, performance, and opportunity04:41 The real barrier: fear, skepticism, and AI resistance at work07:45 Industry realities: healthcare, sensitivity, and responsible adoption17:50 A practical framework: upskilling people and building confidence34:49 The next wave: agentic workflows and what leaders should prepare for41:43 Where to find Bala and closing thoughts💬 Quotes from the Episode- “And to me, it’s still human, meaning us, we are still humans, leaders are still humans. The human aspect still stays.”- “Again, I’m coming back to the people, like, because that’s gonna be the unlock for you. Upskill your people with AI tools.”- “AI being, like, the car, or being the internet, being the electricity.”🌍 Where to find Bala Muthiah:- On his website: balamuthiah.com- His Speaker profile: sessionize.com/bala-muthiah/- LinkedIn: linkedin.com/in/balaarjunan/Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

🤖🧠 Thinking with Machines with Vasant DharWhat happens when AI stops being a tool and starts becoming a collaborator and an agent? In this episode, NYU Stern professor and AI pioneer Vasant Dhar takes us through the real story behind modern AI, and the practical frameworks we need for AI trust, AI governance, and the coming era of agentic AI.🚀 What you will learn- Why “thinking with machines” is a bigger idea than “thinking machines”- How the automation frontier separates low-risk automation from high-stakes human control- Why healthcare has lots of data but still struggles to make good decisions- Why mental health is a dangerous place to outsource empathy to machines- What edge cases in AI mean and why they matter for self-driving cars- How AI agents change the governance conversation, from obligations to restrictions to rights📌 Key highlights- A practical definition of trust in AI based on error rates and consequences- AI in healthcare data: turning medical trails into usable decision intelligence- The future of work: AI as an amplifier, not a substitute, unless you let it become a crutch- Governance questions that no one gets to avoid once agents can act in the world📧💌📧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 💬“Trust depends on how often a machine makes mistakes and the consequences of those mistakes.”“In physical health, I’m very optimistic. In mental health, not so.”“It’ll likely lead to a bifurcation of humanity… skills get amplified… or people rely on the machine as a crutch.”Chapters ⏱️00:00 Vasant Dhar’s origin story in AI and early expert systems05:08 A Brave New World warning and why optimism still needs guardrails07:26 AI in healthcare vs mental health and why feelings change the rules12:37 The trust heat map and the automation frontier in real life18:21 Edge cases, bounded rationality, and what machines pay attention to26:03 The future of work and why AI amplifies both skill and decline36:23 Governance, AI agents, and how much agency we should allow44:05 AI wow moments and the next frontier: integrated machine senses47:15 Where to find the book, podcast, and newsletterWhere to find Vasant Dhar 🔎- Visit Vasant's Website, also to find all the links to shops with "Thinking with Machines", his book: vasantdhar.com- Listen to his Podcast: bravenewpodcast.com- and get his Newsletter: vasantdhar.substack.comMusic credit: "Modern Situations" by Unicorn Heads` Hosted on Acast. See acast.com/privacy for more information.

Most people think better AI results come from better prompts. This episode proves why that’s wrong.Professor GePhardT introduces Context Engineering, the missing skill that transforms AI from a confused parrot into a capable collaborator. Through relatable metaphors, real business examples, and a deliciously British cake analogy, you’ll learn how shaping an AI’s environment matters more than clever wording.You’ll discover:Why prompt engineering alone failsHow context helps AI understand intentThe difference between guessing and knowingA real telecom case where context fixed customer supportHow to apply context engineering in everyday AI use📧💌📧Tune in to get my thoughts and all episodes, don’t forget to ⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠📧💌📧Quotes from the Episode“Prompt engineering is asking nicely. Context engineering is setting the stage.”“Without context, AI is guessing. With context, it understands intent.”“Context turns AI from a parrot into a collaborator.”Chapters00:00 Why Prompts Alone Are Not Enough04:12 What Context Engineering Really Means10:25 Understanding Intent Through Context18:40 Context Engineering vs Prompt Engineering25:10 Telco Case Study35:20 The Cake Example44:00 Final TakeawaysAbout 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.comMusic credit: “Modern Situations” by Unicorn Heads 🎵 Hosted on Acast. See acast.com/privacy for more information.