A Beginner's Guide to AI

✨ 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A central theme of the conversation is human-AI collaboration and why leaders must move beyond optimizing outdated structures.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 SuperShifts
The pandemic's role in inspiring new leadership frameworks and agile mindsets
Blending human values with AI-powered decision-making
Why 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.IO
Steven Fisher — StevenFisher.IO

And here you'll find:
SuperShifts: Transforming How We Live, Learn, and Work in the Age of Intelligence

Music credit: "Modern Situations" by Unicorn Heads
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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/

Music credit: "Modern Situations" by Unicorn Heads
Hosted on Acast. See acast.com/privacy for more information.

🤖🧠 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

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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 💬

“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

Music credit: "Modern Situations" by Unicorn Heads`
Hosted on Acast. See acast.com/privacy for more information.

Most people think better AI results come from better prompts. This episode proves why that’s wrong.
Professor GePhardT introduces Context Engineering, the missing skill that transforms AI from a confused parrot into a capable collaborator. Through relatable metaphors, real business examples, and a deliciously British cake analogy, you’ll learn how shaping an AI’s environment matters more than clever wording.

You’ll discover:
Why prompt engineering alone fails
How context helps AI understand intent
The difference between guessing and knowing
A real telecom case where context fixed customer support
How 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

Music credit: “Modern Situations” by Unicorn Heads 🎵
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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 Guest
Bud Caddell: https://budcaddell.com/
NOBL: https://nobl.io/
Consulting Slop: https://consultingslop.com/
LinkedIn: linkedin.com/in/budcaddell/

Music credit: "Modern Situations" by Unicorn Heads
Hosted on Acast. See acast.com/privacy for more information.