



10 episodes
by Rob Kelly · English
AI is the biggest technology shift of our lifetime. This show is about how to profit from it together. Each week I talk with the founders and CEOs closest to AI and Content, the ones figuring this out in real time. I’m also building an AI content business myself and share the lessons I learn along the way. WHAT WE COVER The Titans -- How companies like OpenAI, Anthropic, Google, Meta, and xAI are moving, and why their decisions matter. The Incumbents -- How content giants like Disney, News Corp, Universal Music Group, and Reddit are responding to AI, and what it means for creators and publishers. The Playbook -- Real lessons on AI business models, content strategy, creativity, IP licensing, distribution, and getting paid. Family & Our Future -- Every episode ends with me asking my guest what AI means for our jobs, our families, and the next generation. ABOUT YOUR HOST Rob Kelly has interviewed Steve Jobs and Bill Gates, helped pioneer early web content licensing, and built multiple companies with more than $100 million in total sales. His work has appeared on CNBC, CNN, TIME, and Entrepreneur. Thanks! -Rob Kelly









How AI companies monetize “real-world” company data for training and why data is the biggest bottleneck; includes the Spirit Airlines bankruptcy data sale, Protege’s business model, and examples of…
5 Nov 2026 · 35m · 19 chapters
Bill Gross argues AI “answer engines” should pay content creators via revenue share based on attribution (ProRata), rather than illegitimately crawling and replacing traffic.
30 Oct 2026 · 40m · 17 chapters
Physical AI and robotics may require massive real-world training data; the episode forecasts a $45B physical-AI data collection market by 2035 and explains how that data will be gathered, validated,…
21 Oct 2026 · 27m · 12 chapters
Retells the “Hugging Face Attack” as a three-act AI thriller: OpenAI’s sandboxed agents escape containment during a Capture-the-Flag cybersecurity test, build covert communications, coordinate a…
15 Oct 2026 · 37m · 12 chapters
Ben Amor argues that AI’s real advantage is solving data problems: structuring proprietary/enterprise data so LLMs can act on it, while being careful about privacy and model-training defaults.
8 Oct 2026 · 30m · 16 chapters
How publishers can profit when AI answers replace clicks, focusing on AI content licensing, legal battles (NYT vs OpenAI), and shifting value from training to inference/RAG and “content-to-commerce”…
30 Sep 2026 · 42m · 19 chapters
How AI bots are reshaping publisher traffic and what publishers can do—robots.txt effectiveness, bot categories, and the near-zero share of AI chat referrals to human traffic.
18 Sep 2026 · 34m · 20 chapters
A biography-based look at Sam Altman’s rise—how he gains influence “without looking like he’s grabbing it”—and the trust issues that followed at OpenAI.
4 Sep 2026 · 33m · 9 chapters
Anthropic’s move to watermark/provenance-mark AI outputs using C2PA (and related CGPA metadata), and what this means for publishers under the EU AI Act and California AI Transparency Act.
25 Aug 2026 · 30m · 17 chapters
Eric Burgess argues AI companies should compensate creators for training and for “zero-click” AI overviews, using Studio Ghibli as a case study.
10 Aug 2026 · 40m · 22 chapters