#AIcareers #AgenticAI #AIconsulting For this episode #1001 special, the tables are turned: SuperDataScience founder Kirill Eremenko takes the host’s chair and @JonKrohnLearns 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. This episode is brought to you by: • Cisco: https://outshift.cisco.com • Acceldata: https://www.acceldata.io Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: • (00:00:00) Introduction • (00:03:42) From an Oxford neuroscience PhD to AI consulting • (00:17:25) Defining AGI and why consciousness isn’t required • (00:30:39) Are we in an AI bubble? Why we benefit either way • (00:46:32) 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 Additional materials: https://www.superdatascience.com/1001