?? In this episode, Dietmar Fischer talks with Zoher Karu about a surprisingly useful application of AI: helping men dress better without the endless shopping, guessing sizes, and daily decision fatigue. Zoher supports Taelor, a menswear subscription and clothing rental service that combines algorithms, large language models, and human stylists to deliver outfits that fit your body, your taste, and your real-life context.

You?ll hear how Taelor starts with a style profile and then uses recommendation logic and human oversight to pick items from inventory, generate styling notes, and adapt over time using customer feedback. Zoher explains why fashion is an unusually hard AI problem: taste is subjective, context matters, and sizing is not standardized across brands. That?s why metadata, garment measurements, and feedback loops are central to improving fit and personalization.

If you want the ?Steve Jobs wardrobe effect? without wearing the same thing forever, this episode is for you: fewer choices, better outcomes, and more confidence with less effort.

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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 argoberlin.com

Quotes from the Episode

?AI is really, to me, it?s about scaling human intelligence.?

?A small in this brand and a small in this brand don?t fit the same.?

?Clothes are just the intermediary. The real objective is to make you feel better about yourself.?

Chapters

00:00 Zoher Karu?s background and why AI became mainstream

03:02 What Taelor is: menswear subscription and clothing rentals

06:36 LLMs plus human stylists: how recommendations are generated

10:39 Why fashion is hard: taste, context, fit, and matching

14:11 The sizing problem: measurements, metadata, and feedback loops

22:03 Decision fatigue and ?the Steve Jobs wardrobe? effect

25:07 How much AI vs humans today and what changes next

42:11 Where to find Zoher Karu and Taelor

Where to find the Guest

Zoher Karu on LinkedIn: linkedin.com/in/zzkaru/

Visit Taelor at Taelor.ai

Music credit: "Modern Situations" by Unicorn Heads

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In this episode of Beginer?s Guide to AI, Dietmar Fischer speaks with Shaheen Samavati, co-founder and CEO of VeraContent, about what an effective AI content marketing strategy actually looks like inside a real agency.

AI in marketing is no longer experimental. It?s operational.

Shaheen shares how her team moved from testing ChatGPT and OpenAI tools to building structured, repeatable AI workflows for marketing agencies. From briefing and drafting to localization, editing, and publishing, AI now supports both creative execution and backend operations.

This conversation goes beyond surface-level tool talk. It explores what it really means to integrate generative AI in marketing without sacrificing quality, brand voice, or client trust.

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? Leading an international content agency in Spain, Shaheen offers a practical, no-fluff perspective on the ?adopt-or-die? reality facing content marketers today.

How AI reshapes content marketing strategy and agency workflowsWhy adopting AI is no longer optional in content creationBalancing brand voice, speed, and quality with generative AIHow clients react to AI-driven content ? and what wins them overFuture trends: AI SEO, AI video, AI email tools

Key Themes Discussed

AI Content Creation vs. AI Content Operations: It?s not just about writing faster. AI is reshaping how agencies organize projects, manage briefs, handle multilingual content, and scale output.Brand Voice & Quality Control in the Age of Generative AI: Speed without editorial structure leads to mediocrity. The real competitive advantage lies in combining AI acceleration with strong human oversight.AI SEO Strategies 2025: As search engines integrate AI into results pages, marketers must rethink optimization. AI-assisted workflows are becoming essential to stay visible.Future of AI in Marketing: From AI video generation to AI email tools and automation stacks, the marketing landscape is shifting toward integrated AI ecosystems.

? Shaheen's Quotes:

?It?s kind of an adopt-or-die situation for anyone in the content business.??We?re moving from testing tools to building repeatable, scalable AI workflows.?

? Chapters (experimental feature)

00:00 Welcome & Episode setup

02:15 Shaheen?s journey & founding Vera Content

07:40 Early experiments with AI in content

12:05 The ?adopt-or-die? moment for content marketing

15:30 How AI reshaped content creation workflows

20:45 Backend operations & scaling with AI

25:10 Client adoption & resistance

30:05 Balancing quality, brand voice & speed

35:20 Looking ahead ? future of AI in marketing

Where to find VeraContent: ? VeraContent

Where to find Shaheen: ???? Shaheen Samavati

Here is her landing page prompt tutorial on YouTube

And this is the replay of the webinar about AI for marketing teams

? Music credit: "Modern Situations" by Unicorn Heads

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AI systems are often praised for their size. Bigger datasets. Bigger models. Bigger compute. But what if scale is only half the story?

In this episode of A Beginner?s Guide to AI, Prof. GePhardT dives deep into AI training data and explains why quantity alone cannot guarantee performance. From AI bias to model reliability, we explore how data quality determines whether AI systems are merely impressive or truly trustworthy.

You will learn how imbalanced datasets create blind spots, why aggregate accuracy can be misleading, and what the Gender Shades research revealed about AI fairness. We also explore how businesses can audit their own CRM data and prevent AI from amplifying internal chaos.

This episode connects technical insight with strategic clarity. It is essential for founders, marketers, and leaders building responsible AI systems.

???

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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 argoberlin.com

Quotes from the Episode?AI does not think. It reflects.??Quantity builds capability. Quality builds trust.??Every dataset is a silent curriculum.?Chapters

00:00 The Data Diet Problem

07:42 Defining Quantity vs Quality in AI

17:15 Capability vs Reliability Explained

27:10 The Gender Shades Case Study

36:45 Business Implications and Data Strategy

46:20 Practical Audit for Your Own AI Systems

Music credit: "Modern Situations" by Unicorn Heads

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What if artificial intelligence is less like a new app?and more like the railroads of the 19th century?

In this episode of Beginner?s Guide to AI, I sit down with Matt Hicks, CEO of Red Hat, to explore one of the most powerful metaphors for understanding AI?s role in business today. Just as railroads didn?t merely improve transportation but fundamentally reshaped economies, AI is not just another productivity tool. It is infrastructure. And infrastructure needs builders.

Matt argues that AI will require its own ?railroad barons??leaders, technologists, and organizations willing to invest, experiment, and lay the tracks that others will run on. We discuss what that means for enterprise AI adoption, open source innovation, and long-term business strategy.

This conversation goes far beyond hype. It?s about patterns, fear, leadership, and the tension between process and innovation.

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? What You?ll Learn in This Episode:

Why AI business strategy is today?s equivalent of building railroadsHow Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) will reshape brand visibilityThe balance between experimentation and responsibility in AI adoptionWhy processes vs. innovation remains a critical tensionHow leaders can prepare for AI-driven business transformation

? Quotes from the Episode:

?AI is like the railroads ? it will need its barons to build the infrastructure that carries everyone forward.??The fear isn?t that AI replaces us; it?s that we don?t adapt fast enough to what it enables.?

? Chapters

00:00 Introduction and Red Hat?s Role in AI

03:01 Why Awareness of AI Technology Matters

06:00 Creating Progression: From Awareness to Action

09:01 Personal Experiences with AI Change

12:00 Recognizing Business Patterns in AI Transformation

15:01 Patterns, Fears, and Early Adoption Signals

18:01 Fear vs Opportunity: Why People Hesitate on AI

21:00 Balancing Experimentation with Responsibility

27:00 The Maturity Curve of AI Adoption

30:00 When Processes Prevail Over Innovation

42:00 AI and the Software Industry?s Perspective

45:00 Looking Ahead: Strategy and the Future of AI

? Where to find Matt Hicks

LinkedIn: Matt HicksRed Hat: redhat.com

? Music credit: "Modern Situations" by Unicorn Heads

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?? In this episode of Beginner?s Guide to AI, Dietmar Fischer talks with Samantha Mehta, solutions engineering leader at AIRIA, about how companies can adopt AI without losing control. If your teams are already experimenting with ChatGPT and AI tools, the real question is not ?Should we use AI?? but ?How do we use it safely, visibly, and profitably??

Samantha explains what enterprise AI security looks like in real life, including AI guardrails that can audit, block, redact, and replace sensitive data. She also unpacks AI governance and AI observability, because you cannot manage what you cannot see. A key theme is shadow AI and AI sprawl: people will use AI anyway, so organizations need sanctioned paths that reduce risk while accelerating adoption.

On the practical side, this conversation goes deep on agentic workflows. Samantha describes how agents become more than prompts through routing, actions, approvals, looping over documents like CSVs, and scheduled runs that create repeatable outcomes. From internal GPT alternatives to workflows that touch expenses, supply chain planning, and customer support, the episode is packed with grounded examples and a clear starting path.

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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 argoberlin.com

Chapters

00:00 Welcome and why Samantha got into AI

01:26 What ARIA does: build, test, secure, deliver enterprise AI

02:19 Real use cases from simple internal GPT to complex workflows

08:27 How to start: guardrails first, then build your first agent

11:32 Agentic workflows explained: routing, actions, human in the loop

17:12 Why security and governance matter and why blocking fails

31:14 AI sprawl and shadow AI: monitoring and risk management

40:00 Wow use cases and the future: Blade Runner, change, and jobs

48:42 Where to find Samantha and ARIA

Quotes from the Episode

? ?I personally can?t think of a case where an LLM needs to know my social security number.?

? ?People are going to use it no matter what. If you don?t enable safe usage, they?ll still use it.?

? ?Agentic workflows are so much more than just ping an LLM and get a response.?

? ?I always say: build, test, secure, and deliver your usage of AI.?

Where to find Samantha:

?? LinkedIn: Samantha Mehta on LinkedIn

?? Company: look at what AIRIA does

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AI is transforming the real estate industry ? but what does that really mean for agents on the ground? In this episode of Beginner?s Guide to AI, host Dietmar Fischer sits down with Andrew Reville, founder of PeakAgent, to explore how artificial intelligence is reshaping the way agents work, market, and connect with clients.

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From the challenges agents face with lead generation to the opportunities of AI-powered tools, Andrew shares his journey from realtor to tech founder and reveals why the future of real estate belongs to those who embrace AI, not fear it.

? Key Highlights

Andrew Reville?s journey from agent to AI entrepreneur

The real pain points of real estate agents ? and how AI can fix them

AI tools for real estate agents 2025 and why they matter

How generative AI will transform real estate valuation and marketing

The future of property listings, client relationships, and agent workflows

? Quotes from the Episode

?We didn?t want to just build another AI tool ? we wanted to solve real pain points for real estate agents.?

?The dream of being an agent often fades when the reality of chasing leads and endless follow-ups hits.?

?AI in real estate isn?t about replacing agents ? it?s about giving them back the time and energy to love their job again.?

?I?ve spoken with dozens of agents, and the question I always ask is: what would make you fall back in love with being an agent??

?Generative AI has the potential to completely change how we value, market, and sell properties.?

?The future of real estate belongs to agents who embrace AI, not fear it.?

?? Chapters (experimental feature)

00:00 Welcome & Introduction of Andrew Reville
05:30 Andrew?s Journey: From Real Estate Agent to AI Entrepreneur
12:15 Discovering the Potential of AI in Real Estate
19:40 Building PeakAgent: Solving Pain Points for Agents
27:50 The Harsh Realities of Being a Real Estate Agent
36:20 How AI Can Help Agents Fall Back in Love with Their Work
44:45 Generative AI and the Future of Property Valuation
52:10 AI Marketing Strategies for Real Estate in 2025
59:00 Final Thoughts and Andrew?s Advice for Agents

? Where to find Andrew Reville

? Website: PeakAgentAI.com

? LinkedIn: Andrew Reville

? IG: @peakagentai

??? Personal IG: @andrew_reville

? Paper&Purpose - help Andrew doing good deeds: www.paperandpurpose.me

? Tune in to get my thoughts, and don?t forget to subscribe to our Newsletter!
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Boobesh Ramaurai on the Future of Data and AI

In this episode, I sit down with Boobesh Ramaurai of LatentView to explore the future of data and AI?from his early days in analytics to today?s transformative AI landscape. Boobesh shares how curiosity led him into the world of analytics back in 2006, why execution is more important than ideas, and how data-driven decision making is reshaping businesses across industries.

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We dive into the real-world impact of AI, the challenges organizations face when adopting data strategies, and what it means to build human-centered AI with responsibility and ethics in mind.

If you want expert insights into AI in business, responsible AI implementation, and the future of data and AI, this conversation is a must-listen.

?? Key Highlights

Boobesh Ramaurai?s journey from analytics to AI leadershipHow businesses can harness data-driven decision making with AIWhy execution beats ideas in the world of innovationThe growing importance of human-centered AI and responsibilityWhat?s next for the future of data and AI

? Quotes from the Episode

?I always say that it is not the idea that really is valuable. It is the execution?that?s the magic and the secret sauce.? ? Boobesh Ramaurai

?It was fascinating to see how people were using data and capturing data to answer business questions?that curiosity is what pulled me into AI.? ? Boobesh Ramaurai

? Where to find Boobesh Ramadurai

LinkedIn: linkedin.com/in/boobesh/LatentView's Website: latentview.com

Tune in to get my thoughts, and don?t forget to subscribe to our Newsletter: ? beginnersguide.nl

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? In this episode of Beginner?s Guide to AI, Dietmar Fischer speaks with Naga Santhosh Reddy Vootukuri (aka Sunny), a Principal Software Engineering Manager at Microsoft working on Azure SQL deployment infrastructure. Sunny shares his personal journey into AI, from early ChatGPT experiments in late 2022 to using AI tools in production workflows, and what actually changed his day to day work.

? You?ll hear how he thinks about GitHub Copilot inside Visual Studio, where it saves time, and where engineers still need to slow down and verify outputs. The episode also goes beyond coding into leadership and adoption: how managers can help teams use AI responsibly, and why showing outcomes and numbers matters more than hype. Sunny also connects the dots to the broader industry shift toward AI agents and structured tooling like GitHub Models and Docker?s evolving AI ecosystem.

? Key takeaways you can use immediately

Practical AI adoption for engineers and managersGitHub Copilot productivity in real workflows, not demosWhy AI code can look correct and still be wrong, and how to respondThe rise of AI agents and what it means for everyday teamsHow GitHub Models lowers friction for evaluating models and promptsWhy Docker is leaning into agent workflows and developer productivity

???

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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 argoberlin.com

? Chapters

00:00 Welcome and Sunny?s background at Microsoft and Azure SQL deployment

00:53 What pulled him into AI from ChatGPT experiments to real workflows

07:50 AI tools and jobs, building websites faster and empowering non devs

10:56 GitHub Copilot in Visual Studio, how it changes daily coding

19:40 The AI adoption gap, why many still do not use AI and the rise of agents

38:45 Docker Captain, GitHub Models, and building agent workflows without heavy setup

42:22 Trust, privacy, and the future facing questions to close the episode

? Quotes from the Episode

?I recently wrote an article also on Business Insider? how I can save, like, 60% to 70% of my time doing? repetitive tasks.??Lead by example and lead with numbers? show the actual data? this is how it really improved my productivity.??Earlier, AI also doing a lot of hallucination? it was generating all crappy code? you have to go and iterate multiple times.?

? Where to find the Guest

Docker profile: docker.com/contributors/naga-santhosh-reddy-vootukuri/GitHub: github.com/sunnynagavoSpeaker profile: sessionize.com/naga-santhosh-reddy-vootukuri/Redgate community ambassador profile: red-gate.com/hub/community/ambassadors/ambassador/Naga-Vootukuri/And of course LinkedIn ?: linkedin.com/in/naga-santhosh-reddy-vootukuri-5a67a133/

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AI Leadership for the Agent Era: Building Hybrid Organizations with Dominic von Proeck

AI is entering its operational phase. In this episode, Dominic von Proeck, Co-Founder of Leaders of AI, breaks down what AI transformation looks like when you stop collecting prompts and start building agent-powered teams.

We talk about why owner-led companies and the German Mittelstand can move faster than many expect, and why the most important capability is not technical wizardry but leadership: clear delegation, strong feedback loops, and critical thinking about every AI output.

Dominic shares how their organization runs AI assistants with real operational discipline, including onboarding, documentation, and even personality profiles, plus the emerging pattern of AI managers that lead other agents.

If you want practical guidance on AI agents in business, hybrid organizations, and adoption that sticks, this conversation delivers an unusually concrete operating model.

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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 argoberlin.com

Chapters

00:00 Dominic?s AI origin story and why AI transformation matters now

03:10 Mittelstand impact, demographics, and why owner-led firms can move fast

06:10 Adoption reality: AI at home vs at work and the companion effect

08:10 Leadership as the key skill for managing AI assistants and hybrid teams

14:10 The stack and the operating model: agent files, Airtable layer, self-hosting and n8n

17:05 Fear, pain points, and the real path to organization-wide AI adoption

24:00 2026 and the shift from prompts to agents, plus AI managers leading other agents

35:25 Matrix education, flow learning, and what ethical progress looks like

40:45 Where to find Dominic and Leaders of AI

Quotes from the Episode?Prompting is 2025? in 2026, we should let the AI prompt.??One of the best antidotes to being afraid of anything is education.??To be honest, leadership skills.?
Where to find the GuestWebsite: leadersofai.comLinkedIn: linkedin.com/in/dominicvonproeck/Programs: The MBAI program

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? Unlock a Future Where AI Inspires Leadership?not Replaces It

In this episode, Dietmar Fischer speaks with Ja-Naé Duane and Steven Fisher, co-authors of the book SuperShifts, about what leadership really looks like in the age of artificial intelligence. Instead of framing AI as just another technology trend, the conversation explores AI leadership as a systemic and human challenge. Drawing on their work with global organizations and executives during and after the pandemic, Ja-Naé and Steven explain why the biggest shifts are not driven by tools, but by how leaders rethink decision-making, responsibility, and organizational design.

The episode traces the origins of SuperShifts back to Covid, when existing systems suddenly stopped working. Ja-Naé Duane shares insights from working with CEOs across Europe who were already using machine learning, but struggled to use AI to meaningfully support leadership decisions. Together, the guests unpack why AI-first leadership requires more than efficiency gains. It demands clear governance, ethical accountability, and a shared understanding of who owns outcomes when humans and machines collaborate.

A central theme of the conversation is human-AI collaboration and why leaders must move beyond optimizing outdated structures. Steven Fisher introduces a systems-thinking lens, arguing that organizations need new frameworks rather than incremental improvements. The discussion highlights how AI changes leadership roles, why trust and transparency matter more than ever, and how possibility itself becomes a strategic asset in the age of intelligence.

Key takeaways include practical insights into AI leadership, the importance of systems thinking, and why SuperShifts offers a roadmap for leading through uncertainty. This episode is for anyone who wants to understand how leadership must evolve as AI becomes embedded in decision-making, work, and organizational culture.

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?? Key Highlights

Understanding AI-First Leadership through the lens of SuperShiftsThe pandemic's role in inspiring new leadership frameworks and agile mindsetsBlending human values with AI-powered decision-makingWhy systems thinking, foresight, and possibility are essential tools for modern leaders

? Quotes from the Episode

- ?The most successful leader won?t be the one who predicts the future?but the one who shapes it.?

- ?In the Age of Intelligence, possibility itself becomes the most valuable capital.?

- ?Our role as leaders is to bring humanity into the algorithm, not replace it.?

? Chapters (experimental)

00:00 Introduction ? What is SuperShifts?

05:12 From Pandemic to Paradigm Shift: How SuperShifts Was Born

12:45 AI-First Leadership: Reimagining How We Lead

20:30 Human-AI Collaboration: Balancing Ethics and Innovation

28:10 Systems Thinking and SuperShifts Framework

35:00 Applied Strategies: Leading in the Age of Intelligence

? Where to Find Ja-Naé Duane and Steven Fisher

Dr. Ja-Naé Duane: Ja-Nae.IOSteven Fisher ? StevenFisher.IO

And here you'll find:

SuperShifts: Transforming How We Live, Learn, and Work in the Age of Intelligence

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AI adoption is not only a technology shift, it is a leadership and culture shift. In this episode, Dietmar Fischer talks with Bala Muthiah about AI leadership, the psychology behind AI resistance in the workplace, and the practical steps leaders can take to turn curiosity into day to day usage.

Bala shares why the human aspect still decides outcomes, even when the tools feel magical. You will learn how leaders can reduce fear, build confidence, and guide teams through real AI upskilling strategy instead of one off trainings that never translate into workflows. The conversation also touches on industry differences, including why sensitive domains like healthcare raise the bar for responsible AI adoption, and what the rise of agentic workflows means for the future.

???

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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 argoberlin.com

? Chapters

00:00 Welcome and why AI is a leadership moment

02:12 AI leadership in 2026: pressure, performance, and opportunity

04:41 The real barrier: fear, skepticism, and AI resistance at work

07:45 Industry realities: healthcare, sensitivity, and responsible adoption

17:50 A practical framework: upskilling people and building confidence

34:49 The next wave: agentic workflows and what leaders should prepare for

41:43 Where to find Bala and closing thoughts

? Quotes from the Episode

- ?And to me, it?s still human, meaning us, we are still humans, leaders are still humans. The human aspect still stays.?

- ?Again, I?m coming back to the people, like, because that?s gonna be the unlock for you. Upskill your people with AI tools.?

- ?AI being, like, the car, or being the internet, being the electricity.?

? Where to find Bala Muthiah:

- On his website: balamuthiah.com

- His Speaker profile: sessionize.com/bala-muthiah/

- LinkedIn: linkedin.com/in/balaarjunan/

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?? Thinking with Machines with Vasant Dhar

What happens when AI stops being a tool and starts becoming a collaborator and an agent? In this episode, NYU Stern professor and AI pioneer Vasant Dhar takes us through the real story behind modern AI, and the practical frameworks we need for AI trust, AI governance, and the coming era of agentic AI.

? What you will learn

- Why ?thinking with machines? is a bigger idea than ?thinking machines?

- How the automation frontier separates low-risk automation from high-stakes human control

- Why healthcare has lots of data but still struggles to make good decisions

- Why mental health is a dangerous place to outsource empathy to machines

- What edge cases in AI mean and why they matter for self-driving cars

- How AI agents change the governance conversation, from obligations to restrictions to rights

? Key highlights

- A practical definition of trust in AI based on error rates and consequences

- AI in healthcare data: turning medical trails into usable decision intelligence

- The future of work: AI as an amplifier, not a substitute, unless you let it become a crutch

- Governance questions that no one gets to avoid once agents can act in the world

???

Tune in to get my thoughts and all episodes, don't forget to ?????????????????????????????????????????????????????subscribe to our Newsletter?????????????????????????????????????????????????????: ????beginnersguide.nl????

???

About Dietmar Fischer:

Dietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or your digital marketing going, just contact him at argoberlin.com

Quotes from the Episode ?

?Trust depends on how often a machine makes mistakes and the consequences of those mistakes.?

?In physical health, I?m very optimistic. In mental health, not so.?

?It?ll likely lead to a bifurcation of humanity? skills get amplified? or people rely on the machine as a crutch.?

Chapters ??

00:00 Vasant Dhar?s origin story in AI and early expert systems

05:08 A Brave New World warning and why optimism still needs guardrails

07:26 AI in healthcare vs mental health and why feelings change the rules

12:37 The trust heat map and the automation frontier in real life

18:21 Edge cases, bounded rationality, and what machines pay attention to

26:03 The future of work and why AI amplifies both skill and decline

36:23 Governance, AI agents, and how much agency we should allow

44:05 AI wow moments and the next frontier: integrated machine senses

47:15 Where to find the book, podcast, and newsletter

Where to find Vasant Dhar ?

- Visit Vasant's Website, also to find all the links to shops with "Thinking with Machines", his book: vasantdhar.com

- Listen to his Podcast: bravenewpodcast.com

- and get his Newsletter: vasantdhar.substack.com

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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

???

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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.?

Chapters

00:00 Why Prompts Alone Are Not Enough

04:12 What Context Engineering Really Means

10:25 Understanding Intent Through Context

18:40 Context Engineering vs Prompt Engineering

25:10 Telco Case Study

35:20 The Cake Example

44:00 Final Takeaways

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

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?? 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

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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 argoberlin.com

Quotes 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.?

Chapters

00:00 Bud?s path from software to organizational change and why AI feels different

04:20 ConsultingSlop.com, vibe coding, and when AI strategy gets uncomfortably believable

06:30 Copilot mandates vs real adoption, why productivity math fails without redesign

16:40 AI as a catalyst for deeper issues: brand story, conflict, and culture

19:25 The next 18 months: investment traps, backpedaling, and what leaders should do

38:00 Agents, Agentforce, and Bud?s personal AI toolkit plus wow moments and wrap

Where to find the GuestBud Caddell: https://budcaddell.com/NOBL: https://nobl.io/Consulting Slop: https://consultingslop.com/LinkedIn: linkedin.com/in/budcaddell/

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? 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.

???

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???

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

? Chapters

00:00 Welcome and Janet?s AI origin story

01:47 Custom GPTs as brainstorming partners for marketers

05:05 Hands-on AI workshops: building confidence across ChatGPT, Gemini, Claude, Copilot

15:23 Synthetic personas and rapid creative validation with ?persona panels?

20:00 Multi-model workflows: choosing the right tool and making outputs usable

35:03 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 Guest

Janet's website: janetbarkerevans.comAbelsonTayler's website: AbelsonTaylor GroupOr connect on LinkedIn with Janet: Janet Barker-Evans

Thanks for listening. If you enjoyed the episode, please follow the show and share it with someone who is trying to ship better work faster.

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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.

???

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? Highlights

How 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

? Chapters

00:00 Introduction ? Dietmar Fischer welcomes Michael Sacca from Leadpages

05:17 Making AI accessible for SMBs in landing page optimization

10:28 Building an AI-first landing page builder

15:37 The exciting shift in Martech and AI adoption

20:59 Exploring personalization and customer experience challenges

26:09 Conversational landing pages and chatbots in Beta

31:19 The cusp of transformation: AI?s role in marketing workflows

36:39 Lessons from 13 years of Leadpages and the future outlook

41:45 Closing remarks and where to find Michael Sacca

Where 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.nl

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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.

???

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???

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 Highlights

AI 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 Patel

00:21 Why Jeetu Patel Chose AI

02:56 Cisco, Infrastructure, and the AI Rush

09:02 AI Education and Adoption at Scale

16:18 How Jeetu Patel Personally Uses AI

26:46 Leadership Lessons and Transformation

28:12 Meta-Prompting and Asking Better Questions

42:15 Innovation and Leadership in the Age of AI

54:33 Personal Reflections and Closing Thoughts

? Where to find Jeetu Patel

You can find Jeetu on LinkedIn

And, 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

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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.

???

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???

Chapters

00:00 Welcome and why Fabian chose AI

01:55 Rise of AI turns 10 years: from meetups to a curated conference

03:19 Europe?s biggest AI challenge: dependency on US cloud and GPUs

10:05 Optimists in a dystopian world: why Rise of AI exists

11:22 European AI champions and the sovereignty problem

16:45 Why Europe struggles to turn research into AI companies

19:40 2026 outlook: stop waiting, take responsibility, use AI

23:00 Where to find Fabian and Rise of AI

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?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 Westerheide

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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: [email protected]

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.

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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.

???

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???

Key highlights:

AI privacy explained in real-world terms?what you trade away when you click Accept

Data brokers 101: how your info is collected, bundled, and resold

The ?action figure? experiment: a vivid story about bias and representation in AI imagery

Biometrics and identity: faces, voice prints, and why ?frictionless? can be risky

Regulatory theater vs. meaningful guardrails?and where pro-innovation actually fits

Banks, voice recognition, and moving money: the security-privacy tradeoff

Quotes 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??

Chapters
00:00 Introductions and Setup
03:27 The Consent Illusion & Data Brokers: Turning People into Data Points
04:40 The ?Action Figure? AI Fail & Biometrics and Identity
12:59 Terms of Service ? Read Before You Play
19:59 Regulatory Theater and Real-World Harms
24:03 Pro-Innovation vs Guardrails ? Finding the Line
45:59 Banks, Voice Recognition, and Moving Money
56:49 Final Thoughts ? Sensible Guardrails for AI Startups

Where to find Yvette Schmitter
You 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!

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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.

???

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???

? 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.?

? Chapters

00:00 Welcome to the Episode

02:10 Why Leaders Need to Future-Proof Their Businesses with AI

07:55 How Companies Should Start with AI: Practical First Steps

14:40 AI Literacy, Training, and Overcoming Organizational Resistance

22:30 AI as a Thought Partner: New Leadership Models

31:15 The Future of Work, Bias, and Smarter Decision-Making

38:42 Where to Find Michael Housman and Learn More

Where to Find Michael Housman

Website: michaelhousman.comAIcelerator: ai-ccelerator.comLinkedIn: linkedin.com/in/michaelhousman

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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.

???

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???

? 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

? Chapters

00:00 Why Cluetrain matters again in the AI era

04:10 Markets are conversations and why the human voice cannot be faked

10:05 AI makes language cheap and trust expensive

18:30 The authenticity trap: tone without accountability

27:40 Case study: Air Canada chatbot and the cost of confident wrong answers

36:20 Practical framework: human in the loop and conversation design

? Key topics and keywords

Cluetrain Manifesto and AIMarkets are conversations AIConversational marketing AIAI brand voice authenticityAI trust and accountabilityChatbot hallucinations customer supportChatbot legal liabilityHuman in the loop chatbot design

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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 Background

04:00 AI Tools for Marketers

08:00 Creativity, Branding & AI

15:00 Human-Centric AI in Marketing

25:00 Real-World AI Marketing Case Studies

33:00 Challenges & Cultural Shifts in Advertising

41:00 The Future of AI in Marketing

50:00 Practical Advice for Marketers

? Where to find Kasper Sierslev:

LinkedInZite Website, where you also find the In-house Barometer!

---

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Humayun Sheikh on the Agentic Web, Trust, and the Agentic Economy

Humayun 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.

???

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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 argoberlin.com

Chapters

00:00 Welcome and Humayun?s journey from gaming to DeepMind

03:01 What is an AI agent: autonomy and decision-making

08:20 The Agentic Web: discoverability, connectivity, trust and commerce rails

23:47 Personal agents in practice: preferences, handles and onboarding in minutes

29:53 Verified brand agents and trust: domains, identity and safe agentic buying

48:12 Risks, AGI fears, corporations vs countries and what comes next

Quotes 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 Sheikh

Fetch.ai - your personal AIASI1.ai - the LLMFollow Humayun on LinkedIn!

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The Rising Cost of Intelligence: What Expensive AI Means for the World

Artificial 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.com

Quotes 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.?

Chapters

00:00 The Hidden Price of Intelligence

04:12 Why Cutting-Edge AI Is So Expensive

12:47 How AI Costs Create a Global Divide

21:30 Real-World Case Studies on AI Access

32:18 Practical Ways to Narrow the AI Gap

39:42 Final Thoughts and Key Lessons

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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.

???

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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 argoberlin.com

Quotes 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.?

Chapters

00:00 Context Rot and the Illusion of Smart AI

05:42 Why AI Knowledge Freezes in Time

12:18 When More Context Makes AI Worse

19:47 Business and Marketing Risks of Context Rot

27:05 How to Reduce Context Rot in Practice

34:40 What Humans Must Do Better Than AI

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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.

???

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???

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.?

Chapters

00:00 Machine Learning Without the Myth

04:12 How Machines Learn From Data

10:45 Types of Machine Learning

18:30 The Cake Example

26:05 Healthcare Case Study

36:40 Ethics, Bias, and Proxies

45:50 Final Takeaways

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.

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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.io???????

And listen to Dan, Sensay's CEO and founder, ???????in this episode???????!

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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.nl

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.

AI vs. Automation: Why Repetitive Marketing is Failing

REPOST 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: [email protected]

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 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.

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???

Chapters00:00 When AI Feels Alive
04:12 The Olympia Effect and Human Projection
10:05 What AI Actually Does and What It Doesn?t
18:40 Why Humans Trust Machines
26:30 Ethical Risks of Emotional AI
34:10 How to Stay Clear-Headed Around AI

Quotes 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 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

? Music credit: ?Modern Situations? by Unicorn Heads

Hosted on Acast. See acast.com/privacy for more information.

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.

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???

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.?

Chapters
00:00 Welcome & How Sam Got Into AI
03:21 What Are AI Agents? Definitions and Early Insights
07:14 Real Enterprise Use Cases of AI Agents
12:05 Job Satisfaction, Productivity, and Human-AI Collaboration
17:20 Generalists, Specialists & the Future of Work
22:30 Risks, Transparency & Avoiding an Oppressive AI Future
28:45 How Companies Should Start with Agentic AI
33:20 AI in Education and Changing Learning Environments
39:00 Sam?s Personal Use of AI ? What Works and What Doesn?t
41:20 Terminator vs Matrix? AI Futures
42:41 Where to Find Sam and the MIT Sloan Study

Where to Find the Sam Ransbotham
site at Boston College

Or you find him on LinkedIn
The study of MIT Sloan lies here

And, 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.com

Music credit: ?Modern Situations? by Unicorn Heads ?

Hosted on Acast. See acast.com/privacy for more information.

In this episode of Beginner?s Guide to AI, 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.

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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 elevate your AI strategy or your digital marketing, feel free to reach out anytime at Argoberlin.com

Quotes 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.?

Chapters

00:00 Welcome and Introduction

02:45 Alex Kihm?s Background: Engineering, Legal Tech and Early AI Work

10:32 The Problem with RAG, Training, Fine-Tuning and Hallucinations

18:55 The Birth of POMA AI and Solving the Chunking Problem

32:40 How POMA AI Rebuilds Document Structure and Enables True Enterprise Search

45:50 AI Safety, Manipulation Bots and The Future of AI in Business

52:10 Where to Find Alex Kihm and Closing Thoughts

Where to Find the Dr. Alex Kihm

All you need to know about chunking strategies, you'll find here: poma-ai.comContact Alex on LinkedIn!

Music credit: "Modern Situations" by Unicorn Heads

Hosted on Acast. See acast.com/privacy for more information.

Artificial intelligence breakthroughs might appear magical from the outside, but underneath lies a predictable and surprisingly elegant structure.

This episode of A Beginner?s Guide to AI takes listeners on a clear and engaging journey into the three scaling laws of AI, exploring how model size, dataset size, and compute power work together to shape the intelligence of modern systems.

Through practical explanations, entertaining analogies, and detailed real-world case studies, this episode demystifies the rules that drive every meaningful AI advancement.

Listeners will learn why bigger models often perform better, how data becomes the lifeblood of learning, and why compute power is the critical engine behind every training run.

The episode includes a memorable cake analogy, a breakdown of how scaling laws led to the rise of state-of-the-art large language models, and practical tips for evaluating AI tools using these principles.

This deep yet accessible explanation is designed for beginners, creators, and curious minds who want to understand what truly makes AI work.

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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 doesn?t just grow; it scales, and scaling changes everything.?
?Compute isn?t the cherry on top; it is the oven that makes the entire AI cake possible.?
?Scaling laws show us that AI progress isn?t magic; it?s engineered.?

Chapters

00:00 Introduction to AI Scaling
03:24 The Three Scaling Laws Explained
11:02 The Cake Analogy for AI Models
17:40 Case Study: How Scaling Transformed Large Language Models
23:58 Practical Tips for Understanding and Applying Scaling Laws
28:45 Final Recap and Key Takeaways

Music credit: "Modern Situations" by Unicorn Heads

Hosted on Acast. See acast.com/privacy for more information.

? Matt Weaver, Solutions Engineering Leader at OpenAI, takes us inside the launch of GPT-5, the rise of AI agents, and how these tools are transforming industries.

From practical business adoption tips to exploring advanced features like Deep Research and Custom GPTs, this episode is packed with actionable insights.

? Tune in to get my thoughts, tips and tricks and all the episode in your mailbox: beginnersguide.nl

? What you?ll learn in this episode:

How GPT-5 chooses the right reasoning model automatically for better answersWhy AI literacy is the foundation for business adoptionIndustry examples from banking (BBVA) to travel (Virgin Atlantic)How AI agents like Deep Research work ? and why they?re a game changerCreating your own Custom GPTs without codingAddressing AI objections: security, hallucinations, and cost concerns

Quotes from the Episode:

? ?AI is such a transformative technology ? now is the time to reimagine your processes, not just bolt it onto old ones.? ? Matt Weaver

? ?Your first AGI moment changes how you see every problem ? you start thinking, ?How can ChatGPT help me with this??? ? Matt Weaver

? Chapters (experimental):

00:00 Welcome & Introduction to Matt Weaver

01:18 Matt?s Journey into AI and Joining OpenAI

03:58 GPT-5 Launch ? What?s New and Why It Matters

08:28 How Businesses Should Start with ChatGPT

10:45 AI Adoption Strategies & Avoiding Common Mistakes

12:14 Industry Examples ? Banking, Travel, and Professional Services

14:06 Deep Research: AI Agents Explained

18:06 Study Mode & AI in Education

19:56 Overcoming Objections: Security, Hallucinations & Costs

24:06 ROI of ChatGPT in Business

28:22 The ?AGI Moment? & Personal Uses of ChatGPT

32:03 The Future of AI: Agents, Coding, and New Businesses

35:48 Custom GPTs ? Building Your Own AI Apps

39:06 AI Safety & Optimism for the Future

41:16 Where to Find Matt Weaver & Closing

Want to know more?

? ChatGPT is now also at Chat.com

? OpenAI's learning resources are at: academy.openai.com

? Music credit: "Modern Situations" by Unicorn Heads

Hosted on Acast. See acast.com/privacy for more information.

Ever wished you could clone yourself to get more done? Julian Goldie actually did it ? and built a content empire out of it. In this episode of A Beginner?s Guide to AI, host Dietmar Fischer talks with Julian about how he uses AI to create five videos a day, automate workflows, and still keep a personal, human touch that builds real trust with his audience.

Julian reveals how he turned his initial fear of AI into a full-scale growth engine for his business, transforming his SEO agency into a modern AI-powered content studio. He shares the systems, tools, and mindset that helped him automate marketing, scale his team, and reach millions ? all while avoiding the ?AI slop? that floods the internet.

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Tune in to get my thoughts and all episodes ? don?t forget to ??????????????????????????????????????????????????????????subscribe to our Newsletter?????????????????????????????????????????????????????: ????beginnersguide.nl????
???

? Key Highlights

How Julian scaled from one YouTube channel to nine using AI

The tools behind his workflow: Descript, Claude, and HeyGen

Why 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 empathy

Why 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.?

? Chapters

00:00 Julian?s AI Origin Story
How 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 Day
Julian explains his full workflow, the role of AI avatars, repurposing, and why human connection still matters.

14:40 AI Tools That Power the System
A 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 Loop
How AI supports decision-making, reflection, communication, and empowers team members instead of replacing them.

30:44 The Future of AI Content & Final Thoughts
Quality 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.agency

AI Profit Boardroom: aiprofitboardroom.com

YouTube: @JulianGoldie

Twitter/X: @JulianGoldieSEO

And Julian's Website: juliangoldie.com

? About Dietmar Fischer

Dietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or digital marketing going, just reach out at argoberlin.com ?

? Music credit: ?Modern Situations? by Unicorn Heads

Hosted on Acast. See acast.com/privacy for more information.

Step into the future of artificial intelligence with Fred Jordan as he introduces ?Biocomputing??the next evolutionary leap for AI.

In this episode, Fred unpacks how biocomputing uses nature?s own design principles to build more adaptive, resilient, and intelligent systems.

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Tune in to get my thoughts, and don?t forget to ?subscribe to our Newsletter?!

???

Highlights from the episode:

What ?Biocomputing? is, and why it matters for the future of AI

How biocomputing fundamentally differs from traditional approaches

Fred Jordan?s personal journey and vision for next-generation intelligence

Real-world examples and the untapped potential of biocomputing

Quotes from the Episode:

?Biocomputing is about harnessing the principles of life itself to create intelligence that adapts and evolves, just like nature intended.?

?We?re not just building smarter machines; with biocomputing, we?re taking inspiration from biology to leap forward in how AI thinks and grows.?

Chapters (experimental):
00:00 Introduction and Fred Jordan?s Background
04:15 What Is Biocomputing? The Big Idea
15:30 Biocomputing vs. Traditional AI: Key Differences
28:50 Real-World Applications and the Future of Biocomputing
41:10 Closing Thoughts and Next Steps

Where to find Fred Jordan and FinalSpark:

Discord: discord.com/invite/edPetHUYtx

Website: finalspark.com

Apply to join: finalspark.com/neuroplatform/

Music credit: "Modern Situations" by Unicorn Heads

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?? He Taught AI How to Have Manners ? Meet David Petrou of Continua AI

What 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 Newsletter

Tune 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 Episode

Why Social AI is the next big evolution beyond traditional chatbots

How Continua trains AI to understand timing, tone, context, and social cues

Why David believes text messaging with AI will reach a billion users

The engineering challenge behind teaching AI ?manners? and ?machine etiquette?

How AI group chat agents improve communication, planning, and collaboration

The real use cases: debugging code, planning trips, updating documents, running games, and summarizing information

How Continua?s multi-model architecture orchestrates LLMs, fine-tunes, and intent classifiers

Why Social AI is surprisingly safe ? and why today?s fears don?t match the technical reality

The leadership perspective: how to integrate AI thoughtfully without overwhelming teams

Where Social AI is heading next: meetings, real-time participation, contextual computing, and agentic actions like shopping

This 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.?

?? Chapters

00:00 David Petrou?s Origin Story & Early Fascination with AI
04:51 Why Social AI Matters: From APIs to Human-Aware Group Agents
09:12 Teaching AI Social Etiquette: When to Talk, Listen, or Stay Quiet
16:11 Inside Continuum: Multi-Model Architecture, Fine-Tuning & Real Use Cases
24:05 Social AI in the Real World: Planning Trips, Debugging, Collaboration & Automation
35:01 The Future of Social AI: Meetings, Agentic Actions, Leadership & Ethical Considerations

??? 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

? Where to Find the Guest: David Petrou

Website: continua.aiLinkedIn: David PetrouInstagram: David Petrou

? Closing Credits

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 mindset

Why organizations waste time on ?AI use-case lists?

How generative AI distorted expectations across industries

How to build a culture of curiosity rather than control

Why middle management often resists AI transformation

The four elements of Louisa?s Leadership Anatomy framework

How Louisa uses three AIs as strategic thought partners

What AI literacy really means for modern organizations

How 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 Loran
00:37 How curiosity led Louisa from Moët Hennessy to AI and Google
02:21 Early digital transformation and the roots of AI in logistics
04:46 Why strategy comes before tools ? the real AI leadership lesson
07:15 The global ?AI panic? and how leaders wasted 18 months on use-case lists
09:42 Rediscovering critical thinking in the AI era
11:56 Learning to lead through uncertainty and data discovery
14:33 Building a culture of curiosity instead of control
17:28 The leadership challenge: unlearning the habits of success
20:14 Lessons from Google ? when inefficiency is actually innovation
23:01 How AI puts pressure on leaders and middle management
25:47 The anatomy of leadership: eyes, lungs, arms, and spine
29:42 Using three AIs as thought partners while writing a book
33:11 What AI literacy really means in organizations
36:18 Education, ethics, and the future of learning with AI
39:22 The European AI mindset vs. U.S. drive
42:15 Final insights: leading with clarity, courage, and curiosity
43:37 Where to find Louisa Loran and her book

Where to find the Guest:
Website: LouisaLoran.com
LinkedIn: Louisa Loran
Book: Leadership Anatomy in Motion (wherever you buy your books)

About Dietmar Fischer:
Dietmar is a podcaster and AI marketer based in Berlin. If you want to get your AI or digital marketing moving, visit Argo.berlin.

Music credit: ?Modern Situations? by Unicorn Heads

Hosted on Acast. See acast.com/privacy for more information.

? AI-Created Books: Chance or Threat?
In this eye-opening episode of A Beginner?s Guide to AI, Professor GePhardT unpacks the fascinating, chaotic and sometimes alarming rise of AI-generated books. From Amazon?s restrictions on AI content to the ethics of machine-written storytelling, this episode dives deep into the future of publishing and what it means for readers, writers and creators.

We explore how AI-written books are made, why platforms are overwhelmed and how readers can distinguish human creativity from machine-made text. You?ll hear surprising real-world cases, including the Clarkesworld shutdown and the now-infamous ?82% AI-written? herbal remedy category on Amazon.

? What you?ll learn:

How AI book generation actually works

Why AI is both a creative partner and a creative threat

The risks of misinformation in AI-written books

How to spot an AI-generated book

Why platforms like Amazon are tightening their rules

The future of authorship in an AI-saturated world

???
Tune in to get my thoughts and all episodes ? don't forget to subscribe to our Newsletter: beginnersguide.nl
???

Quotes from the Episode

?A book is more than content; it?s a relationship between the mind that wrote it and the mind that reads it.?

?AI doesn?t dream, doubt or desire ? it just predicts what comes next.?

?AI can help creativity bloom, but it can also bury real voices under mountains of machine-written noise.?

?? About Dietmar Fischer
Dietmar is a podcaster and AI marketer from Berlin. If you want to kickstart your AI or digital marketing journey, he?s your guy!

You can find him at Argoberlin.com

? Music credit: ?Modern Situations? by Unicorn Heads

Hosted on Acast. See acast.com/privacy for more information.

// This is a repost of a great episode - and why, you ask yourself, did he not publish a new episode? Because you are nearly the only one listening to my podcast on the Thanksgiving weekend ?

The Terminator films have profoundly shaped how society thinks about artificial intelligence. This episode analyzes concepts like artificial general intelligence through the lens of Skynet, the malevolent AI in the movies.

We explore real-world AI safety research inspired by cautionary sci-fi narratives. The episode prompts a thoughtful examination of how we can develop advanced AI that enhances humanity rather than destroying it.

With ethical, responsible innovation, we can steer the future toward an AI-enabled world that benefits all.

???

Tune in to get my thoughts and all episodes, don?t forget to ?subscribe to our Newsletter?.

???

About Dietmar Fischer

Host of Beginner?s Guide to AI. Economist and digital marketer helping teams turn AI from hype into workflows.Training, talks, and courses with thousands of participants. ??

Go to ?argoberlin.com ?to see how we can help you!

This podcast was generated with the help of artificial intelligence. We do fact check with human eyes, but there might still be hallucinations in the output.

Music credit: "Modern Situations by Unicorn Heads"

Hosted on Acast. See acast.com/privacy for more information.

In this episode of A Beginner?s Guide to AI, host Dietmar Fischer talks with Roman Chernin from Nebius, about how AI democratization is reshaping the enterprise world.

Roman reveals what it really takes to move from prototype LLMs to reliable, scalable AI platforms - and why most companies don?t need to train their own models to harness AI?s potential.

???

Tune in to get my thoughts and all episodes - don?t forget to subscribe to our Newsletter: ?beginnersguide.nl?

???

From his early years at Yandex, where machine learning quietly powered maps and search, to helping Nebius build global AI infrastructure, Roman?s story is a blueprint for how cloud platforms can make AI accessible to everyone.

He explains how Nebius Token Factory enables businesses to deploy AI applications fast, how to navigate the minefield of compliance and cost, and why real success in AI comes from better collaboration and iteration ? not from ?being a genius.?

? Key Highlights

What 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.?

? Chapters

00:00 Introduction - Welcoming Roman Chernin to the show
00:28 Why AI? Roman?s early journey and Yandex years
01:24 What Nebius does: Building AI infrastructure for builders
03:02 The challenge of scaling AI infrastructure 10× per year
05:06 From utility computing to full-stack AI platforms
07:15 Why developer experience matters for AI growth
09:45 How enterprises move from OpenAI to open-source models
12:10 Compliance, data sovereignty, and enterprise security
14:55 Cost, latency, and optimization challenges in AI scaling
16:50 Which industries are adopting AI fastest
18:40 Democratizing AI for mid-sized businesses
19:35 Nebius Token Factory: Enabling custom AI APIs
22:14 Open-source vs closed models - the real trade-offs
26:03 The U.S. vs. European AI market and regulation
31:20 How governments can drive AI demand (not just infrastructure)
33:58 How AI changes leadership, creativity, and collaboration
37:40 Why iteration beats genius - and how AI accelerates it
38:56 Roman?s personal ?wow moment? with AI video generation
40:55 The real risks of AI - and how fast society must adapt
43:35 Final thoughts and where to find Nebius and Roman

Where to Find Roman Chernin and Nebius

Nebius WebsiteNebius Token FactoryRoman Chernin on LinkedIn

Music Credit: ?Modern Situations? by Unicorn Heads

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Human-Centered AI at Work with Monica Marquez: A Practical Adoption Playbook

If you?re still treating AI like a shiny gadget, this episode will be a polite intervention.Monica Marquez (Flipwork) shows how to build a human-centered AI adoption playbook that actually sticks.We dig into AI as a partner, not a tool; psychological safety for teams; and the one-workflow-per-month rule that turns experimentation into measurable AI ROI.You?ll learn how to avoid work slop, build agentic workflows, and translate machine output into authentic intelligence that reflects your expertise. ?

What you?ll learn

Shift identity first: ?I experiment with AI daily.?Redesign workflows before adding tools.Create psychological safety so teams can try, fail, and improve.Kill work slop and layer your context for quality.Build agentic workflows that scale judgment and consistency.Track time saved and quality gains to prove ROI.

??? Tune in to get my thoughts and all episodes, don?t forget to subscribe to our Newsletter.???

Quotes from the Episode

?The real danger isn?t killer robots. It?s disengaged humans.??Don?t ship work slop. Turn artificial intelligence into your authentic intelligence.??Redesign your workflow first, then layer AI. Otherwise you just automate the old mess.??Stop treating AI like a tool. Treat it like a partner.??Adoption starts with identity: I experiment with AI every day.??Use AI for five-dollar tasks so you can solve five-thousand-dollar problems.?

Chapters

00:00 Welcome, who is Monica Marquez and what is Flipwork

02:59 AI as a partner, not a tool

05:34 Practical example: recruiting, prompts, and human judgment

07:02 Generational beliefs, ?artificial intern,? and mindset shifts

11:24 From effort to impact: redefining success with AI

12:46 Redesigning workflows before layering AI

14:44 Psychological safety and daily experiments

16:55 Leaders model usage, run side-by-side experiments

18:37 Avoiding ?work slop? and building authentic intelligence

21:44 Doing more of your ?zone of genius? with AI

24:39 The one-workflow-per-month rule

29:25 Industry adoption patterns, lessons from Blockbuster vs Netflix

33:12 Personal AI use cases and voice-based workflows

36:32 Matrix, Terminator, and Monica?s real fear: disengaged humans

37:58 Where to find Monica and Flipwork

Where to find Monica Marquez

Her Agency: FlipworkMonica?s site: themonicamarquez.comNewsletter: Ay Ay Ay, AI

About Dietmar Fischer

Host of Beginner?s Guide to AI. Economist and digital marketer helping teams turn AI from hype into workflows.Training, talks, and courses with thousands of participants. ??

Go to argoberlin.com to see how we can help you!

Music credit: ?Modern Situations? by Unicorn Heads ?

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AI?s Biggest Secret: It?s Addicted to Being Average

Large Language Models are masters of fluency but victims of probability. In this episode, Professor GePhardT unpacks why averaging?inside embeddings, attention mechanisms, and token probabilities?quietly drains AI of originality. Through humour, insight, and one brilliant case study from the University of Tübingen, we explore how ?safe? AI outputs create the illusion of intelligence while smothering creativity.

From mathematical foundations to philosophical implications, this episode challenges listeners to rethink what ?intelligence? really means ? and to look for brilliance not in the middle, but at the edges.

? Key Takeaways:

Why LLMs default to safe, predictable outputs

How averaging erases nuance in AI

Real-world evidence of AI?s blind spots in reasoning

Techniques to push models beyond the middle ground

???
Tune in to get my thoughts and all episodes ? and don?t forget to subscribe to our Newsletter: beginnersguide.nl
???

? Quotes from the Episode:

?AI doesn?t need to be smarter. It needs to be braver.?

?The tragedy of the average is that it sounds right but feels wrong.?

?A bold sentence is an act of rebellion against probability.?

Where to find Professor Gephardt:
? We help you figure out your AI game: argoberlin.com

Music credit: ?Modern Situations? by Unicorn Heads ?

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AI tools for business coaching are transforming how leaders and professionals unlock performance and personal growth.

In this episode of Beginner?s Guide to AI, Lisa Turner of CETfreedom joins Dietmar Fischer to share real-world strategies and 40+ actionable AI tools that help coaches, entrepreneurs, and business leaders boost results.

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Ready to take your business to the next level? Subscribe for more AI strategies, share your questions in the comments, and visit our website for free resources. Don?t miss exclusive content in our newsletter?sign up today: beginnersguide.nl

???

Learn how practical AI can revolutionize business processes, streamline leadership, and enhance productivity.

Whether you want to overcome procrastination, empower your team, or drive personal development, this episode delivers proven approaches and expert insights.

? Key takeaways:
? Learn top AI tools for business coaching
? Discover AI techniques to beat imposter syndrome
? Explore AI strategies for leadership development
? Find practical uses for AI in personal growth
? See real examples of AI-ified coaching processes

? Chapters (experimental):
00:00 ? Welcome & Guest Introduction
02:30 ? Why AI? Lisa?s Journey from Engineering to Coaching
07:10 ? First Steps with AI: Overcoming Skepticism
12:00 ? Building 40+ AI Tools for Coaches
18:45 ? Busting Procrastination & Limiting Beliefs with AI
24:20 ? Empowering Leadership & Journaling via AI
30:00 ? The ?Doctor Who? Mindset for Innovation
35:15 ? Trends: How Coaches Use AI in 202540:05 ? Final Insights & Where to Find Lisa

? Quotes:
? "I found a way to AI-ify personal growth and leadership tools for real business results."

? "If you want to grow fast, you have to experiment boldly with new technology."

? Where to find Lisa Turner:

Go to Lisa's website and get a free book (a real one!) at: www.cetfreedom.com

? Or follow Lisa on social media:
TikTok: www.tiktok.com/@cetfreedom
Instagram: www.instagram.com/cetfreedom
Facebook: www.facebook.com/cetfreedom
LinkedIn: www.linkedin.com/company/cetfreedom

---

? Music credit: "Modern Situations" by Unicorn Heads

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Are you GenX and curious about AI, but not sure where to start? In this episode, Greg Steele breaks down how Generation X can confidently embrace artificial intelligence?no tech background required!

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Tune in to get my thoughts and all episodes in your mailbox, don't forget to ???subscribe to our Newsletter???!

???

Join us as Greg shares his own AI journey, debunks common myths about technology adoption after 40, and explains why now is the perfect time for GenX professionals to upskill. Whether you?re looking to stay relevant at work, explore new career paths, or just understand the buzz around AI, this episode delivers clear guidance and practical tips.

Key Highlights:

Why AI matters for GenX and people over 40

Overcoming technology barriers and digital fear

Essential AI skills for midlife professionals

Greg Steele?s step-by-step approach to mastering AI

Real-world stories of GenX success with AI tools

Quotes from the Episode:

?AI isn?t just for digital natives. GenX has a lifetime of experience?and that?s an asset in the age of artificial intelligence.?

?You don?t need to be a coder to thrive with AI. Curiosity and willingness to learn matter most.?

Chapters (experimental feature):
00:00 Introduction and Greg Steele?s AI Journey
04:55 Why GenX Needs to Understand AI Now
12:30 Overcoming AI Myths and Barriers for GenX
21:00 Practical AI Skills for People Over 40
29:15 Greg Steele?s Tips for Embracing AI with Confidence
34:40 Closing Thoughts and Key Takeaways

Get Gregs Book Gen X, Y? - I had a big laugh listening to it ?

- On Amazon

- On YouTube, read by himself!

Look how his CustomGPT on Wildlife Photography can help you ?

I actually tried it with the bee and wasp photos I took on my balcony - and I can tell you: I'll have to do better ?

Music credit: "Modern Situations" by Unicorn Heads

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Fast Minds, Slow Machines: Daniel Kahneman?s Lessons for AI

What if your brain and your AI assistant shared the same wiring? Professor GePhardT from Argo.berlin breaks down Daniel Kahneman?s legendary Thinking, Fast and Slow - showing how humans and machines both juggle instinct and logic, and why understanding that makes you a better marketer.

From System 1?s snap decisions to System 2?s strategic reasoning, discover how AI models mimic our two-speed thinking - and where they still fall short. With insights from real-world marketing case studies, this episode explains how to balance speed with depth in AI-driven creativity and strategy.

???

Tune in to get my thoughts and all episodes - and don?t forget to subscribe to our Newsletter: beginnersguide.nl

???

? Highlights:

Daniel Kahneman?s ?Thinking, Fast and Slow? through the lens of AIFast vs. Slow AI - what marketers should knowHow cognitive bias sneaks into algorithmsReal-world applications in campaign design and data analysisActionable tips to apply slow thinking to AI tools

? Quotes from the Episode

?AI?s biggest flaw isn?t that it?s too fast; it?s that it thinks speed equals truth.?

?Machines now have their own version of instinct and reflection - we built our own cognitive twin.?

?Real intelligence is knowing when to slow down.?

? 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!

? Music Credit: ?Modern Situations? by Unicorn Heads ?

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Discover How Startups Are Winning with AI: An Interview with Peter Swimm

Are you ready to stop working harder and start working smarter? In this episode, we sit down with Peter Swimm, a tech veteran with over 20 years of startup experience, to uncover how small teams can leverage AI to punch above their weight. Peter shares candid stories about being ?mistaken for an AI,? reveals why startups adapt to new tech faster, and offers his brutally honest advice for trailblazers looking to innovate with artificial intelligence.

???

Tune in to get my thoughts and all new episodes in your mailboxk: don?t forget to subscribe to our Newsletter!

???

? Episode Highlights:

- AI for startups: Why small teams win big

- Peter Swimm?s journey from community management to AI evangelist

- The power of working smarter, not harder?with automation and productivity tools

- Real talk: Risks of being a pioneer and best practices for safe AI adoption

- Actionable steps for founders and teams to get started with AI

- Fireflies AI and other top tools for productivity

? Quotes from the Episode:

"I've been accused of being AI because I'm everywhere?chats, emails, tutorials. That's how you use technology as a competitive advantage."

"Pioneers get scalped, but someone has to go first. If you want real innovation, you have to be willing to take the risk."

?? Chapters:

00:00 Meet Peter Swimm: 20 Years in Tech & Startups

03:12 Why Startups Move Faster with AI

09:35 Working Smarter, Not Harder?Automating the Rote, Focusing on Innovation

17:22 The Real Risks: Pioneers, Best Practices, and Lessons for AI Trailblazers

25:05 Action Steps: Peter?s Playbook for Making AI Work for Your Team

Where to find Peter Swimm, connect to him and see, what Toilville has to offer :

??? He is on LinkedIn

? And this is his Website

Music credit: "Modern Situations" by Unicorn Heads

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In this episode of A Beginner?s Guide to AI, Dietmar Fischer talks with Alex Levin, the Co-Founder and CEO of Regal.io, about how Voice AI is bringing real human conversation back to customer service.

For years, businesses have been hiding behind IVRs and chatbots - cutting off the personal touch that customers crave. Alex explains how AI voice agents are transforming the experience, allowing brands to actually talk to their customers again, at scale, with empathy, emotion, and precision.

We dive into what?s behind this transformation - from the technology (OpenAI, Google, Anthropic, ElevenLabs, Deepgram) to the psychology of trust and emotion in customer communication. Alex shares how Regal.io helps enterprises in healthcare, insurance, and finance use AI-powered voice agents that can outperform human representatives while lowering costs and improving satisfaction.

From replacing call center frustration with warm, natural conversations to the rise of empathetic AI agents, this episode explores what happens when voice meets intelligence.

???
Tune in to get my thoughts and all episodes ? and don?t forget to subscribe to our Newsletter: beginnersguide.nl
???

Quotes from the Episode

?If a customer wants to talk to you, you?re lucky - and if they want to do it by voice, you should let them.?

?The personalization possible with AI agents is more human than humans.?

?Everyone told me voice was dead - they were wrong.?

CHAPTERS

00:00 Introduction - Why Voice AI Is Making a Comeback

00:54 Alex Levin?s Journey from Startups to Voice AI

03:42 ?Voice Isn?t Dead? - The Moment That Sparked Regal.io

06:25 How Voice AI Actually Works Behind the Scenes

08:47 Using AI Agents to Talk to Customers at Scale

10:58 Data, Scripts, and What Makes a ?Good? AI Conversation

13:33 Legal Hurdles and Privacy in Voice AI

15:50 Why Healthcare and Insurance Are Early Adopters

18:26 How Customers React When They Realize It?s an AI

21:12 Real Use Cases - From Banks to Everyday Services

24:19 Human in the Loop: When AI Hands Over to People

26:55 Can Small Businesses Afford Voice AI Yet?

28:48 The AI Startup Boom and Smarter Investment Strategies

32:20 Leadership in the Age of AI - New Skills, New Metrics

35:12 Why Young Professionals Must Learn AI Tools Now

37:45 How Alex Personally Uses AI (and Where It Saves Time)

39:24 The ?Terminator Question? - Should We Be Worried?

42:08 Closing Reflections and Where to Find Regal.io

Where to Find Alex Levin

? Website: www.regal.io
?? LinkedIn: Alex Levin

? About Dietmar Fischer:
Dietmar is a podcaster, AI marketer, and economist from Berlin.
If you want to get your AI or your digital marketing going - just contact us at Argoberlin.com!

? Music credit: ?Modern Situations? by Unicorn Heads

Hosted on Acast. See acast.com/privacy for more information.