998: In Case You Missed It in May 2026
In this month’s episode of ICYMI, Jon Krohn explores how AI agents are simultaneously creating new risks and unlocking powerful new ways of working with data. Hear from Anneka Gupta, Cal Al-Dhubaib, Trevor Manz, Jazmia Henry, Jeremy Mumford, and Jacob Miller, discussing why the old cybersecurity playbook breaks down in the age of Claude Mythos, how the notebook became an AI agent’s working memory, what it really takes to build a foundation model from scratch, and why failing slowly is the most expensive mistake an AI team can make.
Additional materials: www.superdatascience.com/998
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
(00:40) Why Claude Mythos Changes Everything About Cybersecurity
(08:11) Why Your Notebook Should Be Your Agent’s Working Memory
(13:19) What It Actually Takes to Build a Foundation Model From Scratch
(20:46) Failing Slowly Is the Most Expensive AI Mistake
995: End-to-End Foundation Models for the Energy Industry, with Jazmia Henry
Jazmia Henry joins Jon Krohn to break down what it actually takes to build end-to-end foundation models for the energy industry. From wrangling decades of handwritten oil-and-gas documents into usable training data, to bespoke tokenizers, reinforcement learning, and inference at scale, Jazmia walks through every stage of the stack. Along the way she explains why reinforcement learning models are "bursty," what reward hacking is and how her Grounded Continuous Evaluation framework fixes it, and revisits the 2023 NeurIPS paper that argued, to widespread skepticism at the time, that scaling bad data degrades model performance.
Additional materials: https://www.superdatascience.com/995
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
(10:06) The User Agnosticism Tenet
(20:02) The Zillow Offers parable
(23:25) Why workflows should come before agents
(29:57) Why data engineering is the bedrock of AI
(52:41) Why velocity is the only durable moat