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

Read my essay "Why AI isn't showing up on your bottom line" on Substack: https://www.exponentialview.co/p/why-ai-isnt-showing-up-on-your-bottom-line
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Where to find me:

Exponential View newsletter: https://www.exponentialview.co/

Website: https://www.azeemazhar.com/

LinkedIn: https://www.linkedin.com/in/azeem/

Twitter/X: https://x.com/azeem

Production by EPIIPLUS1.

Production and research: Baba Films, Chantal Smith, Marija Gavrilov.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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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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

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Where to find me:

Exponential View newsletter: https://www.exponentialview.co/
Website: https://www.azeemazhar.com/
LinkedIn: https://www.linkedin.com/in/azeem/
Twitter/X: https://x.com/azeem

Production by EPIIPLUS1.
Production and research: Baba Films, Chantal Smith, Marija Gavrilov.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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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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

(35:07) From training economy to inference economy


Read my essay "Magnitudes of Intelligence" on Substack: https://www.exponentialview.co/p/the-hundred-million-token-day
Access the solar supercyle model here: https://www.exponentialview.co/p/solar-supercycle

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Where to find me:

Exponential View newsletter: https://www.exponentialview.co/

Website: https://www.azeemazhar.com/

LinkedIn: https://www.linkedin.com/in/azeem/

Twitter/X: https://x.com/azeem

Production by EPIIPLUS1.

Production and research: Baba Films, Chantal Smith, Marija Gavrilov.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.