Will AI take your job? It’s one of the most urgent questions of our time — and it touches all of us, no matter our industry, age, or experience. In this special three-part series of Decoded by Mo, I bring the opinions of some of the most influential voices in AI to an imaginery dinner table to debate what happens to work, identity, and humanity in the age of machines.

In Part 1 — Minds vs. Muscle, we explore why this moment feels different from past technological revolutions. From the wheel and the printing press, to the Luddites and the internet, every wave of innovation has disrupted jobs — but it always replaced muscle. AI, for the first time, replaces mind. That changes everything.

I reflect on how our bodies and brains are designed to survive — pruning away what we don’t use. Just like muscles weaken and languages fade when left idle, we risk losing the very muscles of our minds if we outsource too much to AI.

At the dinner table sits Mo Gawdat, the former Chief Business Officer of Google X, who doesn’t hedge his words: AI will take all jobs. Not some, not most — all. He describes AI as a child raised by the internet, learning at hyperspeed from both the best and worst of humanity. He calls the belief in “new jobs” a comforting myth — “100% crap,” in his words. Even CEOs, he argues, may not be safe.

And yet, Mo also points to what will remain: the deeply human. Care, empathy, love, presence. He ties the future of jobs to a deeper question of meaning, consumption, and spirituality: if machines do all the work, what will define us then?

I also bring in a fresh perspective from Gen Z — my niece — who believes AI should be banned in schools because it’s making students lazy. Her refusal to use AI for assignments contrasts with classmates who embrace it to free time for sports, friends, and hobbies. Both views raise the same concern: if we stop using our minds, we risk losing them.

This episode is about fear, warnings, and the possibility that jobs as we know them may end. In the next part, we’ll hear the opposite view — Peter Diamandis’ optimism that AI will create abundance, not collapse — alongside the cautious skepticism of Geoffrey Hinton, the godfather of AI.

So join me at the dinner table. The bread is broken, the music is playing, and the debate begins.

In Episode 1, we explored the big picture of AI and national sovereignty. But before moving forward, I wanted to hit pause and create something different: a pit stop episode, a crash course, a decoder. Welcome to Episode 1.5 — AI 101, explained without the jargon.

In this episode, I take you on a guided journey through the essentials of AI — how it works, why it matters, and what you really need to know to have smart conversations about it. Whether you’re completely new to the field or already working with AI tools, you’ll find this episode both accessible and insightful.

We’ll rewind the tape back to the origins of AI in 1956, through ELIZA the therapist chatbot of the 1960s, to the “AI winter” of the 1980s, the deep learning breakthrough of 2012, and the explosive rise of GPT models. We’ll explore how AI evolved from niche research into the technology wave that’s reshaping business, politics, and society.

From there, we decode the acronyms and buzzwords:

• LLMs (Large Language Models): autocomplete on rocket fuel.

• SLMs (Small Language Models): efficient pocket-sized cousins.

• Platforms vs. Models: the brain versus the body.

• Parameters & Tokens: what’s inside the AI “brain” and how memory works.

• Foundation Models: the raw clay that gets shaped into doctors, lawyers, and poets.

• Training vs. Inference vs. Fine-Tuning: how models learn and specialize.

  We’ll then dive into the hardware story — what GPUs actually are, why they’re essential for AI, and why they’ve become the new oil of the digital age. You’ll hear why Nvidia’s H100 chips cost more than cars, why entire nations are scrambling to secure them, and why supply bottlenecks make GPUs the most strategic commodity on the planet.

  And because AI is moving beyond words, we’ll explore multimodal AI — models that don’t just process text, but also images, audio, and video. Imagine talking to an AI that can see your world, hear your voice, and respond in real time — that’s where we’re headed.

  By the end of this episode, you won’t just recognize the buzzwords — you’ll own them. You’ll understand what they mean, how they connect, and why they matter. You’ll be able to spot hype from reality, and you’ll be able to explain AI concepts to anyone — whether it’s your boss, your team, or your family at dinner.

  This is AI decoded — made simple, engaging, and practical.

  So, if you’ve ever thought: “I wish someone could explain AI to me in plain English, without dumbing it down, but also without drowning me in jargon”… that’s exactly what Episode 1.5 delivers.

AI is transforming industries faster than any technology in history — but who really controls it? In this first episode of Decoded by Mo, we go beyond the headlines to explore why the winners in the AI era will be those who control the “rails”: the data, the compute power, and the platforms.

We look back at history — from the printing press to the internet — to see the patterns of change, dive into real-world AI success stories, and break down why countries are racing to build sovereign AI for security, economic strength, cultural preservation, and control over the narrative.

From political suspensions like Grok’s on X, to the coming wave of AI agents and job shifts, this episode sets the stage for the series: no jargon, no fluff, just practical insights for anyone curious about AI or leading with it.