A Beginner's Guide to AI

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

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.