How will the future unfold? What is the impact of AI and other exponential technologies on business & society? Join Azeem Azhar, founder of Exponential View, on his quest to demistify the era of exponential change.
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Azeem Azhar's Exponential View, a podcast by Azeem Azhar - Stats, Episodes and Rankings - My Podcast Data
Why AI isn’t showing up on your bottom line
Episode 41
Thursday, June 4, 2026 • Duration 19:17
Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I’ve been studying AI and exponential technologies at the frontier for over ten years.
Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic.
To keep up with the Exponential transition, subscribe to this channel or to my newsletter:
https://www.exponentialview.co/
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More than three years after ChatGPT's release, only 27% of executives say AI has met their ROI expectations. The history of factory electrification explains why — most companies are at the light-bulb stage, adding Copilot licenses rather than reconceptualizing their businesses around AI. In this episode I map the three stages of AI adoption, and show what it actually takes to move from chatbots to the autonomous company — the only stage where the moat becomes real.
I covered:
(01:40) Ford's electricity playbook: why AI adoption needs a complete rethink
(03:51) The congestion problem: why AI gains stall
(05:45) Chatbot to autonomous company: your three-stage roadmap
(06:40) Why individual productivity gains won't build a moat — and what will
(10:17) Which companies are getting AI transformation right
(14:12) My 2029 AI adoption forecast — and how to stay ahead
Production and research: Baba Films, Chantal Smith, Marija Gavrilov.
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AI, writing and artisanal media – inside Exponential View with Greg and Azeem
Episode 40
Thursday, April 16, 2026 • Duration 28:18
Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I’ve been studying AI and exponential technologies at the frontier for over ten years.
Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic.
To keep up with the Exponential transition, subscribe to this channel or to my newsletter:
Greg Williams has joined EV as Executive Editor — two years in the search. He was editor-in-chief of WIRED UK, recognized as Editor of the Year (Technology) three times, and is a five-time novelist. Introducing him to our community in this week’s episode became an opportunity to redefine what EV is: why we make maps instead of stories, and where I think AI is taking institutional media.
Karpathy’s autoresearch could make scientists of us all
Episode 39
Wednesday, April 1, 2026 • Duration 21:02
Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I’ve been studying AI and exponential technologies at the frontier for over ten years.
Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic.
Published in early March 2026, Andrej Karpathy's autoresearch AI tool makes autonomous scientific experimentation cheap and easy — but it was designed to solve machine learning problems. I wanted to see if I could apply its loop architecture to my own work: refining my worldview, testing arguments, solving business problems. In this video, I share how I adapted Karpathy’s autoresearch loops for problems that aren't easy to quantify, how to avoid the local minima trap, and the broader impact of these kinds of methods. I covered:
(02:11) The Karpathy Loop: what is it and how does it work
(07:54) Extending the loop into business and thinking
(09:46) The local minima trap
(12:20) The escape harness: getting beyond “good enough”
(16:05) What I’ve learned after 30 days
(18:47) The loop economy: from doing to judging
Production by EPIIPLUS1.
Production and research: Baba Films, Chantal Smith, Marija Gavrilov.
What NVIDIA’s bet on OpenClaw means for the future of AI and your token budget
Episode 38
Wednesday, March 25, 2026 • Duration 36:35
Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I’ve been studying AI and exponential technologies at the frontier for over ten years.
Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic.
To keep up with the Exponential transition, subscribe to this channel or to my newsletter:
Last week Jensen Huang shared the numbers from NVIDIA’s order book: AI compute demand has grown a millionfold in two years. Much GTC coverage focused on chips, robots, data centers in space, but I think Jensen revealed something far more important in his keynote: “the inference inflection has arrived,” and this is about to transform how all companies should manage their budgets. The inference era is already the operating assumption of the world’s most valuable company.
In this week’s podcast, I cover:
(1:20) NVIDIA's $1 trillion order book
(1:56) OpenClaw: our era's web browser
(7:54) Training vs Inference: how AI is changing
(12:50) Pre-fill vs. decode: the technical split
(18:06) The Harness: why OpenClaw changes everything
(18:59) The engine is useless without a car
(22:21) From 100M to 870M tokens per day
(24:29) Meet my agent R Mini Arnold's team
(26:16) AI focus group simulations at $10–50 a run
(29:36) Jensen's self-interest (and why he's still right)
(33:07) AI governance: token budgets don't belong with IT
Why I changed my mind about Apple and AI
Episode 37
Wednesday, March 18, 2026 • Duration 21:00
Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I've been studying AI and exponential technologies at the frontier for over ten years.
Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic.
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Apple may have stumbled into one of the most defensible positions in AI. This was not on my radar – just two months ago, I was describing a credibility crisis at the company; they appeared wrong-footed on the most important technology of our times and an acquisition was their only plausible way out.
In this episode I work through what I and many other commentators missed – and what road lies ahead for Apple. I cover:
(01:16) Why I was wrong about Apple
(02:40) What's behind the Mac Mini shortage
(04:07) China goes OpenClaw crazy
(06:28) Perplexity builds on a Mac Mini
(07:12) The edge case for Apple
(09:05) Apple Moat 1: hardware
(11:31) Apple Moat 2: privacy
(15:47) The K problem: when good enough beats genius
How to think well with AI: signals, quietness, and the argument engine
Episode 36
Friday, March 13, 2026 • Duration 32:56
Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I've been studying AI and exponential technologies at the frontier for over ten years.
Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic.
To keep up with the Exponential transition, subscribe to this channel or to my newsletter: https://www.exponentialview.co/
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AI has become so embedded in how I work that I can no longer cleanly separate it from my thinking. That raises a question I find genuinely unsettling: is intensive AI use making me a sharper thinker, or quietly doing the opposite? In this episode I pull back the curtain on my full research and writing process — the custom tools, the friction points, and the places where I'm still not sure I've got it right. For Ezra Klein, having AI summarize material is a disaster for original thought. But my AI systems are designed to protect the cognitive work that has to stay human, while they handle everything else. Knowing where to draw that line turns out to be the hardest and most important question.
I covered:
00:00 - Is AI worsening our thinking?
02:35 - Ezra Klein on AI and the death of original thought
04:02 - Cognitive offloading vs cognitive surrender
09:20 - Signal detection at scale
11:06 - Why I use several AI personas to scan for different insights
13:37 - AI tells me what NOT to think about
16:25 - The value of quietness
19:07 - Small notebooks, small ideas
20:01 - Writing reveals what you don't yet know
23:24 - The golden thread
Showing you my AI chief of staff (OpenClaw practical guide)
Episode 35
Thursday, March 5, 2026 • Duration 41:43
Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I've been studying AI and exponential technologies at the frontier for over ten years.
Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic.
To keep up with the Exponential transition, subscribe to this channel or to my newsletter: https://www.exponentialview.co/
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Meet R Mini Arnold - my OpenClaw chief of staff, which manages the equivalent of a ten-person team from a Mac mini in my garden studio. While I slept, that AI team debugged its own code at 3am, researched a trending Substack essay using five parallel investigators, and wrote a 4,600-word script for this very episode in 40 minutes. The gap between people who've started building this way and those who haven't is widening every week.
I covered:
00:51 Introducing my OpenClaw agent “R Mini Arnold”
03:59 What my AI chief of staff actually does
07:58 The hardware and software stack
10:38 A morning brief before you wake up
12:05 Overnight agents: research and code
15:00 How I communicate with my agent
18:56 Example 1: the sovereign wealth fund
22:41 Example 2: how this video was written
26:34 What it costs
29:22 The soul.md personality spec
32:39 Am I losing the judgment muscle?
35:46 Individuals vs. Fortune 500s
38:25 What to try this week
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Are we in charge of our AI tools or are they in charge of us?
Episode 34
Wednesday, February 25, 2026 • Duration 52:24
Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I've been studying AI and exponential technologies at the frontier for over ten years.
Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic.
To keep up with the Exponential transition, subscribe to this channel or to my newsletter: https://www.exponentialview.co/
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This is the first episode of AI Vistas, a new series where I bring together people I trust and respect to tackle a major question collectively.
Today’s question: are we in charge of our AI tools, or are they in charge of us?
Joining me are Nita Farahany, distinguished professor of law and philosophy at Duke University and a leading thinker on cognitive liberty and mental privacy; Eric Topol, founder of the Scripps Research Translational Institute and one of the world's most cited medical researchers; and Rohit Krishnan, engineer, former hedge fund manager, and AI builder. Moderating the conversation is Nick Thompson, CEO of The Atlantic.
We covered:
(01:33) Introducing AI Vistas
(03:51) The AI agent that made a financial decision mid-drive
(05:48) What does it mean to act autonomously anymore?
(08:42) Why AI harms are rarer than you'd expect
(10:24) When AI outperforms doctors – and why that's complicated
(15:20) Constituent competence: the skill you must never offload
(18:50) De-skilling is already happening
(31:20) What can schools do better?
(42:50) AI slop and "hollow-ware"
Entering the trillion-agent economy (ft. Rohit Krishnan)
Episode 12
Thursday, February 19, 2026 • Duration 52:43
Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I've been studying AI and exponential technologies at the frontier for over ten years.
Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic.
To keep up with the Exponential transition, subscribe to this channel or to my newsletter: https://www.exponentialview.co/
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In this episode, I sit down with my friend Rohit Krishnan - writer of the Substack newsletter Strange Loop Canon - for a hands-on conversation about what it actually looks like to build with AI agents today. Between us we're burning through tens of billions of tokens a month - I hit nearly 100 million in a single day this week - and we share what we're each running on our own machines.
We dig into the quirks and surprising power of tools like OpenClaw, Claude Code, and Cowork, debate why AI remains stubbornly bad at good writing, and zoom out to ask what a world of trillions of agents might actually look like — and what economic infrastructure it will need.
We covered:
(03:15) What's on your screen right now?
(04:30) OpenClaw
(06:27) Rohit’s agent, Morpheus
(11:06) Azeem's agent, R. Mini Arnold
(19:25) The analyst is now a machine
(22:36) 100 million tokens in a day: the new normal
(24:44) Building tools to improve AI writing: Horace and Broca
(32:19) Why writing is the hardest eval for LLMs
(39:18) Towards a trillion agents
(42:09) The agentic economy: coordination, identity, and exchange
Inside the economics of OpenAI (exclusive research)
Episode 100
Friday, February 13, 2026 • Duration 49:46
Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I've been studying AI and exponential technologies at the frontier for over ten years. Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic.
To keep up with the Exponential transition, subscribe to this channel or to my newsletter: https://www.exponentialview.co/
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In this episode, I'm joined by Jaime Sevilla, founder of Epoch AI; Hannah Petrovic from my team at Exponential View; and financial journalist Matt Robinson from AI Street. Together we investigate a fundamental question: do the economics of AI companies actually work?
We analysed OpenAI's financials from public data to examine whether their revenues can sustain the staggering R&D costs of frontier models.
The findings reveal a picture far more precarious than many assume; we also explore where the real infrastructure bottlenecks lie, why compute demand will dwarf energy constraints, and what the rise of long-running agentic workloads means for the entire industry.
Read the study here: https://www.exponentialview.co/p/inside-openais-unit-economics-epoch-exponentialview
We covered:
(00:00) Do the economics of frontier AI actually work?
(02:48) Piecing together OpenAI's finances from public data
(05:24) GPT-5's "rapidly depreciating asset" problem
(13:25) Why OpenAI is flirting with ads
(17:31) If you were Sam Altman, what would you do differently?
(22:54) Energy vs. GPUs; where the real infrastructure bottleneck lies
(29:15) What surging compute demand actually looks like
(33:12) The most surprising finding from the research
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