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Episodes

    The 180-second skill that makes AI actually work

    In 180 seconds, learn the ONE leadership skill that will future-proof your career in the next 18 months.

    OpenAI is planning something huge: AI systems will soon be capable of doing the work of their own top researchers.

    But most organizations are missing the real shift – not AI doing work, but leaders learning how to direct AI.

    If you’ve ever watched AI produce an impressive answer…

     …only to discover a fundamental mistake underneath it, you’re not alone.

    AI doesn’t fail because it’s weak.

    It fails because we ask it to solve problems that are too big, too vague, or too intertwined.

    The leaders who thrive won’t be the ones who use AI.

    They’ll be the ones who design the work – breaking complex challenges into clear, auditable steps so AI can actually deliver reliable results.

    This video breaks down:

    1. Why AI breaks under ambiguity

    2. How to “design the work” like you would for an intern

    3. The exact method for decomposing any complex task

    4. A live demo showing how a 3-step prompt beats a fancy 1-shot prompt

    5. Why this is becoming the most important leadership skill in modern business

    If you’re a business leader, this isn’t just about productivity. It’s about staying competitive, reducing risk, and leading teams (human + AI) through complexity.

    AI will automate more of the doing. Leaders who can direct AI will own the future.

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    OpenAI’s march to crazy 2027 predictions

    The future of AI isn’t science fiction anymore – it’s arriving faster than most companies can absorb.

    In this video, we break down a series of eye-opening comments from Sam Altman and Jakob Pachocki about autonomous AI researchers, AI-driven scientific discovery, and even the idea of data centers that can find your future spouse.

    More importantly, we explore what these advancements really mean for businesses:

    1. Will AI actually replace large portions of the workforce?

    2. How soon will AI begin delivering original research and breakthrough innovations?

    3. And why are many companies still struggling to adopt tools that have existed since 2022?

    We also compare these real-world developments to the provocative – and controversial – AI2027 paper, which predicts a future of fully automated AI-led institutions, government systems run by AI, and a workforce displaced by hyper-productive AI agents.

    Are we heading toward a Westworld-style future run by an omniscient AI “ball”?

    Or will adoption bottlenecks, corporate inertia, and real-world operational friction delay these predictions by decades?

    If you’re a business leader trying to understand which AI narratives are hype – and which may reshape your competitive landscape sooner than you think – this video is for you.

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    5 AI Truths & Lies

    Will AI kill meetings – or just the pointless ones?

    In this episode, we hear from Phil Lakin, Head of Enterprise Innovation at Zapier – who separates fact from fiction on five of AI myths shaping today’s workplaces. We cover:

    00:00 Intro

    00:37 Will AI kill meetings?

    01:59 Is your boss the real AI bottleneck?

    04:20 Is learning prompting pointless?

    05:50 Is AI success measured in time saved?

    07:06 Does AI make bad employees worse?

    Phil brings his firsthand experience working with C-suite leaders on enterprise AI transformation – sharing stories, hard truths, and practical frameworks that every manager and innovator needs to hear.

    Watch this if you want to:

    • Understand how AI is changing workplace culture

    • Avoid common executive AI adoption mistakes

    • Learn how to measure real ROI from automation

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    ChatGPT vs Expert Strategist: Can he save your job (from AI)?

    What if you pitted a world-class strategist against frontier AI – and asked them to redesign the future of white-collar work?

    In this episode, I bring together Sangeet Paul Choudary (advisor to 40+ Fortune 500 CEOs; author of Reshuffle) and ChatGPT to answer a single question: How do we protect – and even upgrade – our jobs in an AI economy?

    This is not another “AI tips” video. It’s a practical conversation for C-suites, R&D, strategy, innovation, and operations leaders who must make decisions amid uncertainty: talent strategy, org design, where to automate, and where human advantage compounds. Along the way we cover system-level shifts (workflows → orgs → markets), why “learn the tools” is necessary but not sufficient, and a simple rule leaders can use to spot the next high-value roles before they appear.

    A surprise industry judge listens in and declares a winner at the end.

    What you’ll learn (fast)

    * A 1-rule playbook for surfacing new high-value work

    * Where near-term value pools will emerge

    * How to future-proof talent

    * A leadership lens for budgeting

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    Steve Jobs Predicted THIS AI Use Case in 1983

    What if you could ask Aristotle for business advice – or get Steve Jobs’ take on your next proposal?

    In this video, we explore three powerful ways AI is already transforming how companies work:

    1. Talking to great thinkers – Steve Jobs imagined this in 1983. Today, you can use AI to channel the wisdom of historical or famous figures to stress-test your ideas.

    2. Fixing messy documents – From contracts to supplier forms, AI can scan, flag, and clean up errors before your team even opens the file. Stacey Popham, VP of R&D at Conagra, describes this pain point.

    3. Scaling into AI agents – Beyond single assistants, we show how multiple AI agents can run research, reconciliation, and reporting in parallel – hinting at the future of zero-person firms. Prof Mohan Sawhney from the Kellogg School of Management paints this future.

    While fun-filled, these are practical, field-tested use cases we’ve seen work inside in every size of company.

    By the end, you’ll see how to apply these methods to your own documents, processes, and workflows – and maybe even hear Aristotle weigh in on your next idea.

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    This is How We’ll All Work Soon

    What happens when AI can do in 3 hours what used to take your entire team 3 weeks?

    In this episode, Dino Gane-Palmer puts AI to the test. With a flight to catch and just hours on the clock, he applies a 5-step AI workflow to build a website feature that would normally require designers, developers, and endless meetings.

    Alongside Raghav Toshniwal (a founder who’s been building with AI for years), Dino explores how leaders can:

    • Compress weeks of work into hours
    • Navigate the differences between ChatGPT, Claude, and Gemini in real-world use cases
    • Think of AI not as a “helper” but as an end-to-end builder
    • Avoid the biggest traps in adopting AI at scale

    This isn’t just about websites. It’s a preview of how law, finance, R&D, and every desk job will transform. Business leaders who understand this shift will be the ones sipping cocktails while their competition scrambles.

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    How To Make AI People Want

    Why do so many enterprise AI roll-outs sputter? 

    More often than not, it comes down to one painfully obvious gap: the solution doesn’t tackle a problem employees actually feel. People already juggle endless priorities, and the “old way,” while clunky, is often good enough. If your AI doesn’t remove a real headache, no amount of prompt-engineering magic will spark adoption. 

    In this fast-paced session Dino Gane-Palmer (CEO, Auxee & PreScouter) maps a classic consumer-product playbook onto AI, revealing a 4-part formula he learned from food-innovation leader Stacey Popham (VP R&D, Conagra; Crystal Light alum). You’ll see exactly how the drink-mix that conquered grocery aisles mirrors the way winning AI tools must. 

    Learn what Crystal Light can teach us about AI adoption. 

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    Open AI’s 5 Stages of Artificial Intelligence

    What happens when artificial intelligence stops helping businesses and starts being the business itself?

    In this eye-opening deep-dive, PreScouter & Auxee CEO Dino Gane-Palmer unpacks the “sentient enterprise” vision first sketched by Prof. Mohan Sawhney and shows how OpenAI’s 5-level roadmap is turning that vision into reality. Also, discover the hidden “missing piece” that explains why so many companies stall at pilots and learn why appropriate autonomy (not total automation) will win.

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