Podcasts · Super Data Science: ML & AI Podcast with Jon Krohn
1001: How AI Erased My Career Moat, an Episode #1001 Special: Jon Krohn interviewed by Kirill Eremenko
· 1 h 56 min
Episode 1001: How AI Erased My Career Moat, an Episode #1001 Special: Jon Krohn interviewed by Kirill Eremenko
For this episode #1001 special, the tables are turned: SuperDataScience founder Kirill Eremenko takes the host’s chair and Jon Krohn is the guest. They trace Jon Krohn’s path from an Oxford neuroscience PhD to a New York hedge fund to founding the AI consulting firm Y Carrot, why he regrets leaving academia and how tools like Claude Code erased his hard-won technical moat and why that makes skilled engineers more valuable than ever. Along the way: whether AI is a bubble, Jevons paradox and the data-center boom, the RICE framework for choosing AI projects, the single biggest reason AI projects fail and how a well-built AI agent could give anyone “Christopher Nolan–like” focus.
Additional materials: https://www.superdatascience.com/1001
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In this episode you will learn:
• • (03:42) From an Oxford neuroscience PhD to AI consulting • • (17:25) Defining AGI and why consciousness isn’t required • • (30:39) Are we in an AI bubble? Why we benefit either way • • (46:32) Jevons paradox: why cheaper AI means more data centers • • (01:08:31) The RICE framework for prioritizing AI projects • • (01:15:08) The number-one reason AI projects fail in production • • (01:31:50) AI, attention, and protecting your wellbeing
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