"A Beginner's Guide to AI" makes the complex world of Artificial Intelligence accessible to all. Each interview episode asks someone working with AI about what they do and how AI can help you. The explainer episodes take an important concept/idea and, yeah, explain it to you!
Ideal for novices, tech enthusiasts, and the simply curious, this podcast transforms AI learning into an engaging, digestible journey. Join us and learn everything you need to know on how to use AI in the best way 🚀
🎙️ About The Host, Dietmar Fischer
Dietmar is a AI enthusiast and digital marketer from Berlin. If you want to know how to get your AI or your digital marketing going, just contact him at argoberlin.com
AI Isn’t Moving Too Fast. It’s Too Noisy - Nikolas Badminton
Saison 16 · Épisode 15
lundi 19 octobre 2026 • Durée 55:43
🤖 Why AI Transformation Needs Intentionality, Not More Technology
AI transformation is not about putting AI everywhere. Futurist Nikolas Badminton argues that successful organizations are becoming much more intentional about where AI creates value and where humans remain essential.
In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Nikolas Badminton, Chief Futurist and Hope Engineer at Futurist.com, about moving beyond AI hype and building organizations that can actually handle technological change.
Nikolas argues that the world is not simply changing faster. It is getting noisier.
Behind the endless stream of AI models, agents and automation promises are the same difficult questions companies have faced for decades: people, processes, governance, data, culture and leadership.
So what changes when AI enters the picture?
We explore why going all in on AI can make employees work harder instead of less, why intentionality is becoming central to AI strategy, and why successful AI adoption is fundamentally a transformation project.
We also go beyond AI.
Nikolas introduces the idea behind his new book, The Hope Engineer’s Playbook: hope can become a practical energy for organizational change when leaders combine vision with pathways, agency and wisdom.
We discuss futures thinking, employee empowerment, sustainability, open-source AI, AI sovereignty and even science fiction as a serious strategic tool.
🎧 In this episode:
• Why AI feels faster and more chaotic than it really is
• Why leaders should stop trying to use AI everywhere
• The hidden organizational work behind AI transformation
• Why AI can increase employee workload
• Hope as an energy for change
• Why agency matters inside organizations
• Open-source AI and enterprise AI sovereignty
• Why sustainability and futures thinking belong in business strategy
• How science fiction helps executives experience possible futures
• Whether AI leads us toward Terminator, Matrix or something completely different
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💬 Quotes from the Episode“The world is changing faster than ever before. I actually think it's noisier than ever before.”“It's a transformation project. There's still people and processes and governance, there's data, and that's messy.”“I get hired for the things I used to get fired for.”
⏱️ Chapters
00:00 Meet Futurist and Hope Engineer Nikolas Badminton
01:26 Why AI Feels Faster Than It Really Is
04:33 From AI Hype to Intentional Transformation
09:16 Why Hope Is a Serious Leadership Tool
17:16 Futures Thinking and the Courage to Think Differently
25:10 How to Become a Hope Engineer
29:22 AI Sovereignty and the Case for Open Source
32:47 Sustainability, Science Fiction and Better Futures
AI Is Now the Business Standard. Are You Falling Behind? - DIETMARs OPINION
Saison 16 · Épisode 14
samedi 17 octobre 2026 • Durée 09:59
🤖 AI has moved beyond technical teams and innovation labs. At Berlin’s BIG BANG KI Festival, Dietmar Fischer found packed stages, long queues, and business professionals searching for practical ways to implement artificial intelligence.
In this solo episode of Beginner’s Guide to AI, Dietmar shares what he observed at the festival and what it tells us about AI adoption in the wider business world.
The dominant questions were practical. How can a company integrate AI into its CRM? How can it build useful AI agents? How can it turn individual tools into repeatable workflows? The audience was not limited to developers or AI specialists. It looked like the audience at any large business conference.
That shift matters. AI is no longer an unusual competitive advantage. It is becoming part of the expected business standard.
The festival also exposed the continuing gap between AI marketing and AI implementation. Many exhibitors used impressive language without clearly explaining what their products did. Interest in AI is high, but clear business value is still difficult to identify.
Dietmar also visits the robot arena, where humanoid machines dance and fight. The demonstration leads to a more serious question about how physical robots could change private security and other real-world services.
💡 In this episode:
What the BIG BANG KI Festival reveals about AI adoption
Why AI has entered mainstream business
What business professionals want from AI agents
Why CRM integration and AI workflows are becoming important
The gap between AI buzzwords and practical business value
What humanoid robots could mean for security
Why occasional AI use is no longer enough
How companies can move from AI tools to systematic implementation
The message is simple: companies must do more than use AI. They must learn to systematize it, connect it to real processes, and make it productive.
Quotes from the Episode“AI arrived in the business world, definitely arrived.”“It makes AI a standard. And if you don’t follow the standard, you are below standard and you fall behind.”“It’s not just using AI. You have to get to the next level to systematize AI, to use it to really be productive, to use agents and all those things.”ChaptersAbout Dietmar Fischer
Stop Doing the Work. Start Directing the AI - Solomon Thimothy
Saison 16 · Épisode 13
mardi 13 octobre 2026 • Durée 56:58
🤖 AI fluency is becoming a core business skill. But being AI fluent means much more than knowing how to prompt ChatGPT.
In this episode of Beginner's Guide to AI, Dietmar Fischer talks with entrepreneur and growth marketer Solomon Thimothy about the transition from using AI as a chatbot to using AI as part of the workforce.
Solomon describes how his teams use AI agents and coding tools to create software, automate workflows, prepare client work and increase capacity without simply adding more people.
One example captures the shift: a client had a design process that normally took about a week. After rebuilding the workflow around AI, multiple branded materials could be produced during a single call. According to Solomon, the client estimated that the new process saved him $18,000.
But this episode is not really about one tool.
It is about a different way of working.
Instead of employees doing every task themselves, Solomon argues that professionals increasingly need to direct AI systems that execute the work. That changes productivity, hiring, professional services, management and even the economics of running a company.
We discuss:
🤖 Why AI fluency matters beyond prompt engineering
⚙️ How AI agents change everyday knowledge work
📈 Why AI can increase capacity without immediately increasing headcount
🧠 Why employees need to learn to direct rather than simply execute
💼 What AI means for hiring and professional services
💻 How non-programmers can build working software with AI
⏱️ Why speed can be more valuable than pure cost reduction
💰 Why AI token costs are becoming a management problem
👤 About Dietmar Fischer💬 Quotes from the Episode“We now need to drive the thing, we don't need to do the thing.”“I don't think we're going to be taken over by AI. I think we already are.”“It's your talent, your experience, your past work.”⏱️ Chapters🔗 Where to Find Solomon Thimothy
Jevons’ AI Paradox: Why Cheaper Models Raise Energy Demand
Saison 16 · Épisode 12
dimanche 11 octobre 2026 • Durée 22:54
⚡ AI is getting cheaper, faster, and more efficient. So why are data centres preparing to use far more electricity?
In this episode of A Beginner’s Guide to AI, Professor GePhardT explores Jevons’ paradox and its uncomfortable lesson for artificial intelligence: using less energy per task does not guarantee that we use less energy overall.
Better chips, smaller models, efficient inference, and AI agents make AI more affordable. But lower cost also creates more demand. One AI task becomes ten. One assistant becomes an agent. One model call becomes a long automated workflow running quietly in the background.
We look at the AI rebound effect, AI energy consumption, data-centre electricity demand, sustainable AI, AI agents, and the infrastructure cost behind near-free inference. The episode also examines Google Gemini prompt efficiency alongside the larger growth in AI-focused data centres.
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👤 About Dietmar Fischer
Dietmar is a podcaster and digital marketer from Argo.berlin. If you want to get your AI or digital marketing going, contact him at argoberlin.com.
💬 Quotes from the Episode
“Each individual task may become cheaper. The total number of tasks can explode.”
“The efficient oven was not a failure. It did exactly what it was supposed to do.”
A Disturbing AI Story Big Tech Never Wants You to Hear, with Paul Hebert // REPOST
Saison 16 · Épisode 11
vendredi 9 octobre 2026 • Durée 53:33
🎙️In this episode of Beginner’s Guide to AI, Dietmar Fischer sits down with Paul A. Hebert, founder of AI Recovery Collective and author of Escaping the Spiral, for a serious conversation about AI chatbot harm, hallucinations, digital dependency, and the real-world psychological risks of generative AI.
Paul shares how an intense experience with ChatGPT pushed him into a dangerous spiral, what he learned about the limits of large language models, and why AI literacy may be one of the most important skills of this decade.
🧠 This episode explores what happens when AI stops feeling like software and starts feeling personal. Dietmar and Paul talk about hallucinations, trust, chatbot addiction, AI companions, mental health risks, youth safety, and why companies building these systems cannot hide behind product language forever. The discussion is intense, but it is also practical. You will come away with a clearer sense of how to use AI more safely, what warning signs to watch for, and why regulation is quickly becoming a much bigger part of the AI conversation.
OpenAI has publicly discussed why language models hallucinate, while lawmakers in multiple U.S. jurisdictions have pushed new restrictions on AI systems acting like therapists or medical professionals.
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👤 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
Why Your AI Content Feels Soulless - Diane Strand
Saison 16 · Épisode 10
mercredi 7 octobre 2026 • Durée 48:31
🤖 AI and creativity do not have to be opponents. Used well, artificial intelligence can help people work faster, develop ideas, and remove repetitive tasks. But it cannot replace the human vision, judgment, and emotional connection that make creative work meaningful.
In this episode of Beginner’s Guide to AI, host Dietmar Fischer speaks with executive producer, educator, author, and creative entrepreneur Diane Strand about what generative AI means for creative professionals, entrepreneurs, marketers, and business leaders.
Diane believes that AI should remain a tool with “the human in the middle.” Like a hammer, it can make a task easier, but someone must still decide what to build and how to build it.
The conversation examines where AI adds genuine value and where automation begins to weaken the result. Diane explains why fully AI-generated content often feels generic, why businesses still need people who understand other people, and why creative professionals must retain control over their ideas.
She also shares a practical example from the development of her book cover. AI helped her turn the themes, colors, and emotional tone of her book into visual concepts. A professional designer then used those concepts to create the final cover. This reduced a process that could have taken weeks to only a few days, without replacing the designer or Diane’s creative direction.
Why This Matters
AI is changing creative work, marketing, filmmaking, and entrepreneurship. It can help small teams produce more, allow independent entrepreneurs to start with fewer resources, and move employees away from repetitive tasks.
However, faster production does not automatically create better work. If AI supplies the ideas, personality, and final judgment, the result can lose its originality and emotional value.
Diane offers a clear warning: AI may not replace creative professionals, but professionals who know how to use AI may replace those who refuse to learn it.
Key TakeawaysAbout Dietmar FischerQuotes from the Episode“If you start relying on it to do your work, you're the first to be replaced.”“I don't think AI kills creativity. I think it forces us to be more creative.”“If you want a human to buy, you need to have a human initiating the marketing.”Where to Find Diane StrandClosing
Why Your Brain Needs to Go to the Gym in the Age of AI - DIETMARs OPINION
Saison 16 · Épisode 10
mardi 6 octobre 2026 • Durée 13:39
Dietmar Fischer explores cognitive offloading, critical thinking, and why learning must remain mentally demanding when AI can provide instant answers.
🧠 What happens when AI solves every problem before you have had time to think?
AI can make us faster and more productive. But if we use it to avoid every difficult mental task, we may also weaken the critical thinking, judgment, and problem-solving skills that make us valuable.
Inspired by the question of whether the classroom should function more like a gym, Dietmar Fischer examines why our brains need resistance, repetition, and deliberate exercise. Just as muscles become weaker without use, our intellectual abilities can suffer when we outsource too much of the thinking process.
The goal is not to compete with AI at everything. It is to recognize where AI performs better and where human abilities still matter. Creativity, empathy, strategic thinking, social intelligence, curiosity, and judgment remain essential. When we develop those abilities and use AI for the right tasks, humans and machines can become an effective team.
🎯 In this episode:
Why the classroom could become a gym for the brain
How AI can encourage cognitive offloading
Why easy answers do not always produce real learning
The difference between reaching a result and understanding it
Why intrinsic motivation matters in the age of AI
Which human skills will remain important at work
How to use AI without surrendering your ability to think
Why reading and difficult intellectual tasks still matter
AI should help us think better, not remove thinking from the process.
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Quotes from the EpisodeAbout Dietmar FischerChapters
Mate, Why Are You Talking to a Rubber Duck?! AI as a Thinking Partner
Saison 16 · Épisode 9
samedi 3 octobre 2026 • Durée 22:55
🦆 What if the most useful part of an AI conversation is something you say?
Rubber duck debugging began with programmers explaining their code to a plastic duck. In this episode of Beginner’s Guide to AI, discover how the same approach can help you use AI as a thinking partner for difficult emails, confusing projects and business decisions.
When you describe what you expected, what happened and where you got stuck, you may uncover the real problem. An AI assistant can add questions, summaries and alternative explanations. But it can also accept your assumptions, offer confident mistakes or keep you talking when it is time to act.
🧠 In this episode:
How rubber duck debugging with AI applies beyond programming.
Why explaining a problem can reveal missing details and unchecked assumptions.
How an AI thinking partner can help you prepare for decisions and difficult conversations.
What Harvard’s CS50 Duck shows about guiding people towards answers.
Where AI confirmation bias and excessive agreement can mislead you.
A short exercise to turn your conversation into a specific next step.
🎓 Our case study examines the CS50 Duck and the challenge of giving useful help without doing all the thinking for the learner. We discuss positive feedback, reported mistakes and why asking more questions is not always enough.
🍰 There is also a flat cake, a wrongly accused oven and a reminder that a fluent answer still needs checking.
For founders, marketers and business professionals, the practical question is simple: after talking to AI, can you explain the problem more clearly and take the next step yourself?
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AI at School: Why Students Still Need to Struggle - Jonathan Strecker
Saison 16 · Épisode 8
jeudi 1 octobre 2026 • Durée 51:35
🤖 AI in education can deliver answers and feedback almost instantly, but does faster performance always produce better learning?
Dr. Jonathan Strecker, Head of School at Valley School of Ligonier and author of Emergence, joins Dietmar Fischer to examine what happens when artificial intelligence removes the struggle through which people develop knowledge, judgment, creativity, and resilience.
Jonathan describes five interconnected forms of intelligence: intellectual, social, emotional, ethical, and physical. His argument is that schools, parents, and employers must protect all five as AI becomes more capable.
AI can be a powerful learning coach. A student can write a first draft and receive useful feedback within seconds instead of waiting days. But the same tool can complete the assignment and remove the mental effort that makes learning possible.
🧠 In this episode, you will discover:
Why productive struggle is essential for learning
How AI can support students without replacing their thinking
Why boredom can lead to imagination and metacognition
What cognitive offloading means for children and adults
Why responsible AI education is better than a simple ban
How the five intelligences provide a framework for human development
Why AI dependence may be more dangerous than an AI takeover
What business leaders can learn from the classroom
This discussion is relevant far beyond education. Professionals are also using AI to write, research, analyze, and make decisions. The important question is not only whether AI improves the output. It is whether the person remains capable of producing and judging that output.
🎧 Listen to learn how AI can strengthen human intelligence without quietly replacing it.
Do You Read Newsletters?
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About Dietmar FischerQuotes from the Episode“I'm not necessarily worried about AI itself. I'm worried about what it's replacing.”“You just can't skip the friction that is required to make yourself better.”“Boredom is one of the most important states we can let children be in.”ChaptersWhere to Find the Guest
Job Seekers: Your AI-Written Résumé Is Destroying Trust - Jeremy Schiefeling
Saison 16 · Épisode 7
mardi 29 septembre 2026 • Durée 48:42
Why AI Skills Alone Won’t Build an AI-Proof Career
🤖 An AI-proof career requires more than learning the newest tools. It requires knowing when to use AI, when to rely on human judgment, and how to demonstrate real value.
Jeremy Schifeling, founder and CEO of The Job Insiders, joins Dietmar Fischer to discuss how AI is changing job searches, recruitment, professional skills, and the future of work.
Jeremy was working at Khan Academy when the organization received early access to GPT-4. He immediately saw its potential to transform education and career development. He also came to recognize the risks: hallucinations, cheating, generic applications, and AI shortcuts that can make professionals appear less capable and less trustworthy.
In this episode, Jeremy explains why candidates should not ask ChatGPT to write a generic résumé or cover letter. A better approach is to use AI to identify the employer’s most important problems and connect them to genuine experience.
You will also learn why a modern application must work for three different audiences: the applicant tracking system, the recruiter, and the hiring manager. Algorithms need relevant language. Recruiters need clear stories. Hiring managers need evidence that you can solve a business problem.
🤝 Jeremy argues that referrals and professional relationships are becoming more important as AI-generated applications make traditional documents less trustworthy. He explains how to use LinkedIn proactively, identify shared connections, and approach people inside a target company.
The broader lesson is simple. AI literacy is becoming essential, but it is not sufficient. Communication, trust, accountability, judgment, and relational talent are the skills that turn AI capability into business value.
Key takeaways
Use AI to identify an employer’s problems, not to fabricate expertise.
Optimize your résumé for both algorithms and human readers.
Demonstrate AI skills through real projects and outcomes.
Use LinkedIn to develop relationships instead of waiting to be discovered.
Never Miss An Episode: Our NewsletterAbout Dietmar FischerQuotes from the Episode“The bottleneck is no longer technical talent, it is relational talent.”“Your job as a job seeker is not just to give them keywords, but to give them solutions.”“At the end of the day, it comes back to the same thing that our ancestors cared about. Can I trust you?”ChaptersWhere to Find Jeremy Schifeling
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If this conversation changed how you think about AI and creativity, share it with someone who is trying to find the right balance between automation and human judgment.
Subscribe to Beginner’s Guide to AI for more conversations about artificial intelligence, business, creativity, and the future of work. 🎧
💬 “The better we train our brain, the better we can face what’s coming.”
💬 “If we use AI for the things where AI is better and we develop our abilities where we are better, then we have a good team.”
💬 “The middleman is the brain in this case. Don’t cut it out. You need it there.”
Dietmar Fischer is the creator and host of Beginner’s Guide to AI and a digital marketer at Argo.berlin. If you want to get your AI project or digital marketing moving, contact him at argoberlin.com.
00:00 Can We Still Think in the Age of AI?
02:16 The Classroom as a Gym for the Brain
04:31 Human Strengths AI Cannot Replace
06:28 The Danger of Outsourcing Problem-Solving
09:40 Learning as Lifelong Brain Training
10:30 Reading, Storytelling and the Final Challenge
“You may discover that the most useful sentence in the conversation is one you wrote yourself.”
“It can also agree with your worst idea in beautifully organised paragraphs.”
“The conversation feels active. Whether you are making progress is a separate question.”
👤 About Dietmar Fischer
Dietmar Fischer is a podcaster and digital marketer from Argo.berlin. If you want to get started with AI or improve your digital marketing, contact him at argoberlin.com.
🎙️ AI transparency
Professor Gephardt is an AI character. The script was generated with AI, and the voice is synthetic. Check claims that matter to your decisions.
If this conversation changed how you think about AI and learning, subscribe, share the episode, and tell us which human skill you believe we must protect most.
Combine AI fluency with communication and judgment.
Delegate repetitive work to AI while retaining human accountability.
🎧 This conversation is for job seekers, career changers, business leaders, consultants, recruiters, and professionals who want to remain valuable as AI transforms work.
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