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A Beginner's Guide to AI
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A Beginner's Guide to AI

Author: Dietmar Fischer

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"A Beginner's Guide to AI" makes the complex world of Artificial Intelligence accessible to all. Each episode asks someone working with AI about what they do and how AI can help you. Ideal for novices, tech enthusiasts, and the simply curious, this podcast transforms AI learning into an engaging, digestible journey. Join us as we take the first steps into AI 🚀

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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.
🤖🧠 AI is making strategy cheap. Adoption is still expensive.In this episode, Dietmar Fischer sits down with Bud Caddell (NOBL) to unpack what leaders miss when they roll out generative AI and expect instant results. Bud shares how his team thinks about AI change management, why “turning on Copilot” is not an adoption plan, and what happens to consulting when LLMs can produce “firm-grade” recommendations in seconds.You will also hear the story behind ConsultingSlop.com, a strategy generator that models the reasoning styles of major consulting firms and outputs polished advice instantly. What started as a parody quickly became a serious signal about commoditization, incentives, and the real differentiator: execution, trust, and organizational design.Key takeaways you can apply immediately:✅ How to approach Microsoft Copilot adoption strategy like a redesign effort, not a software toggle✅ Why AI literacy and training reduce fear, resistance, and “adoption theater”✅ What the agents wave means in practice, including platforms like Agentforce✅ How “vibe coding” changes prototyping speed and risk for teams📧💌📧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 this incredible wave that I think is gonna fundamentally change individual organizations, but the entire economy, society at large.”“We turned on Copilot, so why aren’t we more productive? … it’s a design process.”“My big prediction is that over the next 18 months, we’re gonna see a lot of backpedaling… and sunk cost fallacy.”Chapters00:00 Bud’s path from software to organizational change and why AI feels different04:20 ConsultingSlop.com, vibe coding, and when AI strategy gets uncomfortably believable06:30 Copilot mandates vs real adoption, why productivity math fails without redesign16:40 AI as a catalyst for deeper issues: brand story, conflict, and culture19:25 The next 18 months: investment traps, backpedaling, and what leaders should do38:00 Agents, Agentforce, and Bud’s personal AI toolkit plus wow moments and wrapWhere to find the GuestBud Caddell: https://budcaddell.com/NOBL: https://nobl.io/Consulting Slop: https://consultingslop.com/LinkedIn: linkedin.com/in/budcaddell/Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.
🚀 In this episode, Dietmar Fischer talks with Janet Barker-Evans about what happens when AI stops being a novelty and becomes part of a serious creative workflow.Janet breaks down how she uses custom GPTs for marketing as brainstorming partners and how synthetic personas can help teams validate campaigns faster, sometimes in a single day instead of waiting weeks for traditional research cycles.Our topics today include hands-on AI training, multi-model workflows (ChatGPT, Gemini, Claude, Copilot), and why AI fear often comes down to power and control.📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠📧💌📧About the Host: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🎯 What you will learn:How synthetic personas in market research and synthetic customers can accelerate concept testingHow custom GPTs for marketing can unlock better creative optionsHow to choose between tools like ChatGPT, Gemini, Claude, and Copilot for real business work🕒 Chapters00:00 Welcome and Janet’s AI origin story01:47 Custom GPTs as brainstorming partners for marketers05:05 Hands-on AI workshops: building confidence across ChatGPT, Gemini, Claude, Copilot15:23 Synthetic personas and rapid creative validation with “persona panels”20:00 Multi-model workflows: choosing the right tool and making outputs usable35:03 The wow moments and the fear factor: prototyping visuals, power, control, and what’s next💬 Quotes from the Episode“It’s like having a partner who’s not afraid to pitch a crazy idea.”“When we come up with a creative campaign, we will go test it against our synthetic persona panel.”“They’re all synthetic!”“Some of them will poke holes in our thinking, which helps us make it stronger.”“We can gut check it inside of a day.”“So, it’s about power, it’s about control…”🔎 Where to find the GuestJanet's website: janetbarkerevans.comAbelsonTayler's website: AbelsonTaylor GroupOr connect on LinkedIn with Janet: Janet Barker-EvansThanks for listening. If you enjoyed the episode, please follow the show and share it with someone who is trying to ship better work faster.Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.
Michael Sacca (Leadpages) on AI-powered landing pages, personalization, and the future of search 🚀In this conversation, Michael Sacca shares how Leadpages is weaving AI landing page optimization into real marketing workflows - from personalization that actually moves the needle to what Answer Engine Optimization (AEO) means for search and conversions.📧📧📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠!📧📧📧💡 HighlightsHow AI landing page optimization boosts conversion rates with smarter on-page decisions 🤖Practical ways to implement AI-driven personalization without overwhelming your stackWhy AEO (Answer Engine Optimization) matters as search shifts to assistants and LLMs 🔎Navigating privacy & data considerations when deploying AIThe future roadmap for AI inside SaaS marketing tools 🚀⚡Quotes from the Episode"Can AI be an analyzer of customer data, a designer, or even a generator of entire assets? That’s what we’re experimenting with—expanding from just a landing page builder into a conversion optimization platform, with AI at the heart of that story.” - Michael Sacca“If we can get you the answer faster, we can increase conversions.” - Michael Sacca“One exciting use case is syncing ad creative with landing page optimization. Imagine designing a page, having ads produced, and feeding both into a system that constantly optimizes them together. That’s where we’re heading.” - Michael Sacca🧾 Chapters00:00 Introduction – Dietmar Fischer welcomes Michael Sacca from Leadpages05:17 Making AI accessible for SMBs in landing page optimization10:28 Building an AI-first landing page builder15:37 The exciting shift in Martech and AI adoption20:59 Exploring personalization and customer experience challenges26:09 Conversational landing pages and chatbots in Beta31:19 The cusp of transformation: AI’s role in marketing workflows36:39 Lessons from 13 years of Leadpages and the future outlook41:45 Closing remarks and where to find Michael SaccaWhere to find Michael Sacca:🔗 Website: leadpages.com🧑‍🦰 LinkedIn: linkedin.com/in/michaelsacca🙅 X/Twitter: x.com/michaelsacca🎙️ "On the Record" Podcast: lp.leadpages.com/podcast/📧 Tune 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, host Dietmar Fischer sits down with Jeetu Patel, one of the most respected voices in enterprise technology, to explore leadership and innovation in the age of AI.From his early journey at Box to his executive leadership at Cisco, Jeetu shares a unique perspective on how leaders can adapt, inspire, and build AI-first organizations that thrive in times of rapid change.📧📧📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠!📧📧📧Whether you’re an executive, innovator, or simply curious about the future of leadership with AI, this episode will challenge your thinking and spark new ideas about the future of work.🔑 Episode HighlightsAI Leadership Strategies: How leaders can empower people, not replace them.Innovation in the Age of AI: Opportunities and challenges for executives.Building AI-First Organizations: Why starting today is critical for tomorrow.Future of Work: Leadership lessons from tech executives who’ve lived digital transformation.💬 Quotes from the Episode“Leadership in the age of AI isn’t about replacing people — it’s about empowering them to innovate faster and smarter.” — Jeetu Patel“If you’re not building your organization to be AI-first today, you’ll be playing catch-up tomorrow.” — Jeetu Patel🎬 Podcast Chapters (experimental feature)00:00 Introduction and Welcome with Jeetu Patel00:21 Why Jeetu Patel Chose AI02:56 Cisco, Infrastructure, and the AI Rush09:02 AI Education and Adoption at Scale16:18 How Jeetu Patel Personally Uses AI26:46 Leadership Lessons and Transformation28:12 Meta-Prompting and Asking Better Questions42:15 Innovation and Leadership in the Age of AI54:33 Personal Reflections and Closing Thoughts🌐 Where to find Jeetu PatelYou can find Jeetu on LinkedInAnd, you can find Cisco at, yes, Cisco.com 😉🎧 Tune in to get my thoughts, and don’t forget to subscribe to our Newsletter: beginnersguide.nl🎵 Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.
Europe has brilliant researchers, ambitious founders, and world-class industry. Yet the AI race is being dominated elsewhere. In this episode, Dietmar Fischer talks with Fabian Westerheide, founder of Rise of AI, about why Europe is struggling with AI sovereignty, infrastructure, and execution, and what entrepreneurs can do right now to stay competitive.Fabian explains how Rise of AI grew over a decade from early community meetups into a curated conference and ecosystem hub where Europe’s most relevant AI leaders meet. He also makes the case that Europe’s biggest strategic risk is dependency on American GPUs, hyperscalers, and cloud platforms, while policy, capital allocation, and digital administration move too slowly for exponential change.You will learn what a GDPR compliant AI stack can look like, why EU AI Act compliant implementation is becoming a competitive advantage, and why Europe’s research-to-startup transfer remains painfully inefficient. This is a practical and provocative conversation about AI infrastructure, venture capital incentives, European-first tech choices, and the mindset shift required in 2026: stop waiting, start building.📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠📧💌📧Chapters00:00 Welcome and why Fabian chose AI01:55 Rise of AI turns 10 years: from meetups to a curated conference03:19 Europe’s biggest AI challenge: dependency on US cloud and GPUs10:05 Optimists in a dystopian world: why Rise of AI exists11:22 European AI champions and the sovereignty problem16:45 Why Europe struggles to turn research into AI companies19:40 2026 outlook: stop waiting, take responsibility, use AI23:00 Where to find Fabian and Rise 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.comQuotes from the Episode“We are living the dystopia. But within this, I’m an optimist.”“The whole stack is running on American GPUs, it’s running on American hyperscalers.”“If you run a company, use AI, no excuses.”“I realized back then AI will change the world.”“You can’t put me in any box, but overall I’m dedicating 12 hours of a day for AI within Europe.”“Don’t play the capitalistic game anymore… figure out what you want to do meaningful with your life.”Where to find Fabian and the Rise of AI Conference:Fabian Westerheide: Website fabian-westerheide.deRise of AI: Official site riseof.aiRise of AI Ticket Shop: riseof.ai/ticket-shopLinkedIn: Fabian WesterheideMusic credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.
Hollywood loves a good AI apocalypse—but how likely is a real-life Skynet scenario? In today's episode of A Beginner's Guide to AI, Professor GePhardT takes you on an entertaining yet eye-opening journey into Artificial General Intelligence (AGI). From understanding why films like The Terminator shape our deepest AI anxieties, to real-world safety measures inspired by these sci-fi nightmares, this episode breaks down exactly how humanity can steer advanced AI towards a beneficial future—rather than a robotic uprising.Expect to hear why a smart kitchen assistant could unintentionally cause chaos, how fictional tales are influencing actual AI research, and what top thinkers like Elon Musk and Stephen Hawking have warned us about. It's a conversation packed with fascinating examples, practical tips, and an honest look at how we're preparing for AGI today.Tune in to get my thoughts, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠!Want to get in contact? Write me an email: podcast@argo.berlinThis podcast was generated with the help of ChatGPT, Mistral and Claude 3. We do fact check with human eyes, but there still might be hallucinations in the output. And, by the way, it's read by an AI voice.Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.
In this episode, Yvette Schmitter unpacks the uncomfortable truth about modern AI: how convenience turns citizens into data points. We go deep on AI privacy, data ethics, and the industry incentives that drive data brokers, invasive biometrics, and “consent theater” in Terms of Service. Yvette blends engineering chops with no-nonsense clarity to show what needs to change—and what you can do today.📧📧📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠!📧📧📧Key highlights:AI privacy explained in real-world terms—what you trade away when you click AcceptData brokers 101: how your info is collected, bundled, and resoldThe “action figure” experiment: a vivid story about bias and representation in AI imageryBiometrics and identity: faces, voice prints, and why “frictionless” can be riskyRegulatory theater vs. meaningful guardrails—and where pro-innovation actually fitsBanks, voice recognition, and moving money: the security-privacy tradeoffQuotes from the Episode“Pro-innovation. I love innovation. I’m anti-bullshit.”“Since we don’t buy votes, why would we buy people’s data?”Chapters00:00 Introductions and Setup03:27 The Consent Illusion & Data Brokers: Turning People into Data Points04:40 The “Action Figure” AI Fail & Biometrics and Identity12:59 Terms of Service – Read Before You Play19:59 Regulatory Theater and Real-World Harms24:03 Pro-Innovation vs Guardrails – Finding the Line45:59 Banks, Voice Recognition, and Moving Money56:49 Final Thoughts – Sensible Guardrails for AI StartupsWhere to find Yvette SchmitterYou can contact her via LinkedIn, or the Fusion Collective website 🚀post⁠ on being “Huang’d” by ChatGPT when she asked it to turn her into a “Cloud Jedi." Also a recent Substack ⁠article⁠ that takes it a step further. - EU AI Code of Conduct: 26 companies signed, META did not - Layoff data, the numbers:Microsoft laid off 19,175 people  IBM was refreshingly honest about replacing 200 HR employees with chatbots Intel cut 33,900 jobs, 20% of their workforce, while pivoting to AI services. - The Register: Attributed by Hood to 'go-to-market execution challenges'- Channelweb: "Microsoft CFO Amy Hood said that non-AI Azure sales saw 'go-to-market execution challenges' in the vendor's 'scale motion"- SiliconANGLE: "causing the Microsoft stock price to fall more than 4% in extended trading"- Yahoo Finance: "Microsoft shares tumbled as much as 5% in extended trading Wednesday" - Check out this graphic depicting tech companies with the largest layoffs in 2025 - Microsoft: Amy Hood's "Go-to-Market Execution Challenges" Quote:$22.6 Billion Capital ExpenditureGeekWire: "For the quarter, Microsoft reported capital expenditures of $22.6 billion, a new record high"Stock Drop & Market Reaction." ---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.
In this episode of Beginner’s Guide to AI, host Dietmar Fischer speaks with Michael Housman, AI leader, econometrician, and author of the upcoming book Future Proof. Together, they unpack how leaders can future-proof their businesses with AI and why the most important AI transformation doesn’t start with technology, but with people.You’ll learn why companies that hesitate risk falling behind, how even small AI wins can unlock massive productivity, and why AI literacy programs are becoming essential across organizations. Michael explains how AI can act as a strategic thought partner for executives, how to identify high-impact opportunities, and why slow-moving industries often face the biggest AI disruption ahead.From eliminating unconscious bias in hiring to redesigning workflows and supercharging marketing output, this episode is packed with practical examples and leadership insights based on real company transformations.📧💌📧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 learn how to grow your AI or digital marketing capabilities, just reach out to him at argoberlin.com💎 Quotes from the Episode“Think of AI not as a tool but as a collaborator and a thought partner.”“Technology is easy. People are hard. Adoption is always the biggest challenge.”“You can’t future-proof your business unless the C-suite uses AI themselves.”🧾 Chapters00:00 Welcome to the Episode02:10 Why Leaders Need to Future-Proof Their Businesses with AI07:55 How Companies Should Start with AI: Practical First Steps14:40 AI Literacy, Training, and Overcoming Organizational Resistance22:30 AI as a Thought Partner: New Leadership Models31:15 The Future of Work, Bias, and Smarter Decision-Making38:42 Where to Find Michael Housman and Learn MoreWhere to Find Michael HousmanWebsite: michaelhousman.comAIcelerator: ai-ccelerator.comLinkedIn: linkedin.com/in/michaelhousmanMusic 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, Professor GePhardT takes The Cluetrain Manifesto’s famous idea markets are conversations and stress tests it in the age of generative AI. In 1999, Cluetrain demanded that brands stop sounding like machines and start speaking with a human voice. Today, AI can generate that human sounding voice on demand, which creates a new problem: it becomes easy to sound authentic while becoming less trustworthy.You will learn why conversational marketing is not about posting more, replying faster, or writing prettier copy. It is about credibility in public. This episode breaks down the difference between tone and truth, why AI customer service chatbots can create brand risk when they guess, and how to use human in the loop design so your AI supports real accountability instead of manufacturing polite noise.We also unpack a real cautionary case: Moffatt v Air Canada. A website chatbot provided incorrect guidance about bereavement fares, the customer relied on it, and compensation was ordered. It is a sharp reminder that when AI speaks on your website, customers experience it as the company speaking.📧💌📧Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧💬 Quotes from the Episode“AI makes language cheap, and when language is cheap, trust becomes the scarce ingredient.”“Responsiveness can masquerade as empathy.”“When AI speaks in your name, its answers become part of your promises, not just part of your tone.”“You can talk beautifully about cake while still serving bad cake.”“A chatbot is not a neutral tool. It is a brand voice.”“In 1999 the challenge was speaking human. Now the challenge is acting human.” 🎧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 Why Cluetrain matters again in the AI era04:10 Markets are conversations and why the human voice cannot be faked10:05 AI makes language cheap and trust expensive18:30 The authenticity trap: tone without accountability27:40 Case study: Air Canada chatbot and the cost of confident wrong answers36:20 Practical framework: human in the loop and conversation design✅ Key topics and keywordsCluetrain Manifesto and AIMarkets are conversations AIConversational marketing AIAI brand voice authenticityAI trust and accountabilityChatbot hallucinations customer supportChatbot legal liabilityHuman in the loop chatbot designMusic credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.
How is artificial intelligence transforming the way we approach marketing? In this episode, we dive deep with Kasper Sierslev, founder of Zite, to uncover the real-world opportunities and challenges of AI in marketing.Discover how forward-thinking brands are leveraging AI tools to spark creativity, streamline campaigns, and stay ahead in a rapidly evolving digital landscape.📧💌📧Ready to take your business to the next level? Subscribe for more AI strategies, share your questions in the comments, and visit our website for free resources. Don’t miss exclusive content in our newsletter—sign up today: ⁠⁠⁠beginnersguide.nl⁠⁠⁠📧💌📧💡 Key Highlights:Kasper Sierslev shares his journey and unique perspective on embedding AI into marketing strategiesTop AI tools for marketers and how to use them for impactful resultsThe importance of a human-centric approach to AI in marketingInsights on the future of AI and how brands can stay aheadActionable advice for marketers looking to adopt AI today🧾 Quotes from the Episode:“It’s not super easy sitting on the other side doing creative work and just saying, ‘We made this great film, look how funny it is.’ That’s gut feeling, it’s opinions. For almost 20 years now, creativity and branding has lost a lot.” - Kasper Sierslev“I think it’s super easy to do something now, but we don’t really have the big AI tech companies here yet. Maybe that’s because of copyright laws or the lawsuits happening at the moment. Still, we can build on top of the bigger models and protect what we’re doing as it goes back into the loop.”Kasper Sierslev📂 Chapters (experimental feature):00:00 Introduction & Kasper Sierslev's Background04:00 AI Tools for Marketers08:00 Creativity, Branding & AI15:00 Human-Centric AI in Marketing25:00 Real-World AI Marketing Case Studies33:00 Challenges & Cultural Shifts in Advertising41:00 The Future of AI in Marketing50:00 Practical Advice for Marketers🔗 Where to find Kasper Sierslev:LinkedInZite Website, where you also find the In-house Barometer!---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.
Humayun Sheikh on the Agentic Web, Trust, and the Agentic EconomyHumayun Sheikh joins Dietmar Fischer to explain what happens when AI stops recommending and starts doing. We explore the Agentic Web, a new layer where personal AI agents and verified brand agents collaborate to complete tasks like booking travel, coordinating meetings, and shopping with trust built in.You will learn what makes a real AI agent, why autonomy matters, and how multi-agent systems unlock an agentic economy. We also tackle the marketer’s question: what happens to SEO when the buyer becomes an assistant agent choosing on your behalf? Humayun breaks down how identity, verification, and trusted lists can reduce scams and make agentic commerce safe and usable.📧💌📧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.comChapters00:00 Welcome and Humayun’s journey from gaming to DeepMind03:01 What is an AI agent: autonomy and decision-making08:20 The Agentic Web: discoverability, connectivity, trust and commerce rails23:47 Personal agents in practice: preferences, handles and onboarding in minutes29:53 Verified brand agents and trust: domains, identity and safe agentic buying48:12 Risks, AGI fears, corporations vs countries and what comes nextQuotes from the Episode“There has to be a hint of autonomy within an agent.”“We have provided the rails of discoverability, connectivity, communication, trust. And commerce.”“Your aggregator is your own agent. It holds your preferences. It doesn’t pass it to anybody.”“Anybody who has a website should have an agent, or will have an agent.”“I was the first investor in DeepMind.”“We will not have countries, we will have corporations.”Where to find Humayun SheikhFetch.ai - your personal AIASI1.ai - the LLMFollow Humayun on LinkedIn!Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.
The Rising Cost of Intelligence: What Expensive AI Means for the WorldArtificial intelligence is reshaping how we work, learn, and create. But as frontier AI models become more capable, their costs are rising faster than ever. This episode of A Beginner’s Guide to AI dives into the global AI divide, exploring how price, compute, infrastructure, and access are quietly determining who benefits from AI and who risks falling behind.Listeners will discover why advanced AI models cost so much to train and run, how high prices can concentrate innovation in wealthy institutions, and why access to strong models is becoming a new form of economic and educational inequality. Through vivid examples and clear explanations, Professor Gephardt guides listeners through the real-world consequences of expensive AI and what can still be done to ensure a more inclusive 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.comQuotes from the Episode:“When intelligence becomes expensive, opportunity becomes exclusive.”“A great model is useless if only a handful of people can afford to use it.”“If AI becomes a privilege, innovation shrinks to the size of the elite who control it.”Chapters00:00 The Hidden Price of Intelligence04:12 Why Cutting-Edge AI Is So Expensive12:47 How AI Costs Create a Global Divide21:30 Real-World Case Studies on AI Access32:18 Practical Ways to Narrow the AI Gap39:42 Final Thoughts and Key LessonsMusic credit: "Modern Situations" by Unicorn Heads 🎧✨ Hosted on Acast. See acast.com/privacy for more information.
Context rot is one of the most underestimated risks in artificial intelligence today. In this episode of A Beginner’s Guide to AI, we explore how AI systems trained on static data slowly drift away from reality while continuing to sound confident, helpful, and persuasive.You’ll learn why large language models struggle with time, why feeding more information into AI can backfire, and how outdated knowledge quietly sabotages decisions in marketing and business. This episode explains the difference between timeless principles and perishable insights, and why trusting AI without checking freshness can cost credibility and money.Key topics include context rot in AI, outdated training data, long context window limitations, AI decision-making risks, and practical strategies like retrieval-augmented generation and smarter context engineering.📧💌📧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“Fluency is not accuracy, even though our brains desperately want it to be.”“More context doesn’t make AI smarter, it often makes it confused.”“AI confidence is cheap. Verification is expensive.”Chapters00:00 Context Rot and the Illusion of Smart AI05:42 Why AI Knowledge Freezes in Time12:18 When More Context Makes AI Worse19:47 Business and Marketing Risks of Context Rot27:05 How to Reduce Context Rot in Practice34:40 What Humans Must Do Better Than AIMusic credit: "Modern Situations" by Unicorn Heads 🎧 Hosted on Acast. See acast.com/privacy for more information.
Machine learning is everywhere, yet rarely understood. In this episode of A Beginner’s Guide to AI, we strip away the hype and explain how machine learning actually works, why it’s so powerful, and where it quietly goes wrong.You’ll learn how machines are trained on data rather than rules, why predictions are not understanding, and how real-world systems can produce unfair outcomes even when they look accurate. A real healthcare case shows how a cost-based algorithm systematically underestimated medical need, revealing the hidden dangers of proxy metrics.This episode covers machine learning basics, ethical AI, algorithmic bias, fairness, and transparency in a way that is accessible to beginners and useful for professionals.📧💌📧Tune in to get my thoughts and all episodes, don’t forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧Quotes from the Episode“Machine learning gives you what you measure, not what you value.”“The algorithm didn’t invent bias. It learned it efficiently.”“A perfect prediction of the wrong thing is still failure.”Chapters00:00 Machine Learning Without the Myth04:12 How Machines Learn From Data10:45 Types of Machine Learning18:30 The Cake Example26:05 Healthcare Case Study36:40 Ethics, Bias, and Proxies45:50 Final TakeawaysAbout 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.Music credit: Modern Situations by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.
REPOST due to low podcast listener activity - if you listen now, you are the exception 😉Ever wondered how Netflix knows exactly what you'll binge next or how big brands like Delta Air Lines turn multimillion-dollar sponsorships into concrete sales?Welcome back to A Beginner's Guide to AI, where today we're uncovering the fascinating world of AI inference—the secret sauce behind machine-made predictions.--- --- ---A word from our Sponsor:Sensay creates AI-powered digital replicas to preserve and share individual and organizational knowledge, turning it into scalable, sustainable, and autonomous wisdom.Visit Sensay at ⁠⁠⁠⁠⁠⁠⁠Sensay.io⁠⁠⁠⁠⁠⁠⁠And listen to Dan, Sensay's CEO and founder, ⁠⁠⁠⁠⁠⁠⁠in this episode⁠⁠⁠⁠⁠⁠⁠!--- --- ---Professor Gephardt, with his usual charm and wit, breaks down precisely how AI learns from past data to tackle new, unseen scenarios, turning educated guesses into powerful, profitable insights.Expect engaging analogies—from fruit-loving robots to cake-tasting mysteries—and real-life case studies, like Delta’s remarkable $30 million Olympic success story powered by AI. Plus, practical tips on how to spot AI inference in your daily digital life and even how to experiment with your own AI models!Tune in to get my thoughts, and don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠!This podcast was generated with the help of ChatGPT and Mistral. We do fact-check with human eyes, but there still might be hallucinations in the output. And, by the way, it's read by an AI voice.Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.
REPOST DUE TO WRONG AUDIO TRACK. Changed it, but many may have missed the right episode.Is intelligence something we’re born with, or do we learn everything from scratch? That’s not just a question for philosophers - it’s at the core of artificial intelligence today.In this episode ofA Beginner’s Guide to AI, we explore the great debate between nativism and deep learning.Nativism suggests that some knowledge is built-in, like the way babies instinctively pick up language. Deep learning, on the other hand, argues that intelligence comes purely from experience - AI models don’t start with any understanding; they learn everything from massive amounts of data.We break down how this plays out in real AI systems, from AlphaZero teaching itself to play chess to ChatGPTGPT mimicking human language without actually understanding it. And, of course, we use cake to make it all crystal clear.Tune in to get my thoughts, and don’t forget tosubscribe to our Newsletter at beginnersguide.nlThis podcast was generated with the help of ChatGPT, Mistral, and Claude 3. We do fact-check with human eyes, but there still might be hallucinations in the output. And, by the way, it’s read by an AI voice.Music credit:"Modern Situations" by Unicorn Heads. Hosted on Acast. See acast.com/privacy for more information.
AI vs. Automation: Why Repetitive Marketing is FailingREPOST due to low podcast listener activity - if you listen now, you are the exception 😉Ever received the same email twice—word for word, from two different people? That’s not AI, that’s bad automation. And it happens way more often than it should.In this episode, we break down the key difference between automation and artificial intelligence—why one just follows rules while the other actually thinks. With a real-world case study straight from my inbox, we’ll expose how businesses are unknowingly damaging their credibility with mindless automation and what they could do differently with AI.If you’re running digital marketing, email campaigns, or even PR outreach, this is a must-listen. Stop the spam, start thinking smarter.Tune in to get my thoughts, and don’t forget to subscribe to our Newsletter!This podcast was generated with the help of ChatGPT, Mistral, and Claude 3. We do fact-check with human eyes, but there still might be hallucinations in the output. And, by the way, it's read by an AI voice.Music credit: "Modern Situations" by Unicorn Heads. Hosted on Acast. See acast.com/privacy for more information.
Ever wonder how Netflix knows your next binge-watch, or why your bank spots fraud before you do? In this lively episode of A Beginner’s Guide to AI, Professor GePhardT lifts the lid on predictive AI—the hidden tech wizard quietly shaping our daily lives.From forecasting retail trends at Target to critical healthcare interventions, predictive AI isn't just predicting the future; it's already shaping it. But there’s a catch: with great power comes the thorny challenge of bias and ethics.Join the fun as we untangle how predictive AI differs from generative AI, explore its surprising influence in everyday situations (cakes included!), and sharpen our own predictive skills through hands-on activities with Google Trends. Plus, a reality check from AI pioneer Pedro Domingos reminds us why understanding this tech matters—because computers might already run more than we'd like to admit.Tune in to get my thoughts and all the episodes: don't forget to ⁠subscribe to our Newsletter⁠ 💌Want to get in contact? Write me an email: podcast@argo.berlinThis podcast was generated with the help of ChatGPT, Mistral, and Claude 3. We do fact-check with human eyes, but there still might be hallucinations in the output. And, by the way, it's read by an AI voice from ElevenLabs.Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.
Artificial intelligence has become incredibly convincing. It talks smoothly, reacts instantly, and often feels surprisingly human. In this episode of A Beginner’s Guide to AI, Prof. GepHardT explores why that feeling can be misleading — and why it matters.Drawing on literature, psychology, and real-world AI design, the episode explains how modern AI systems simulate intelligence without understanding, why humans instinctively project emotions onto machines, and where ethical risks begin when appearance replaces clarity. This is an accessible, practical episode for anyone who wants to understand AI without getting lost in jargon or hype.📧💌📧Tune in to get my thoughts and all episodes, don’t forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧Chapters00:00 When AI Feels Alive04:12 The Olympia Effect and Human Projection10:05 What AI Actually Does and What It Doesn’t18:40 Why Humans Trust Machines26:30 Ethical Risks of Emotional AI34:10 How to Stay Clear-Headed Around AIQuotes from the Episode“AI doesn’t understand you — it performs understanding.”“The danger isn’t smart machines, it’s trusting fluent ones.”“When intelligence looks alive, that’s when it needs the most scrutiny.”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🎧 Music credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.
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Comments (2)

Amir Em

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Mar 15th
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