988: In Case You Missed It in April 2026
In this month’s episode of In Case You Missed It, Jon Krohn talks to guests about memory and education, and how artificial intelligence is continuing to help lower the barriers to access. Hear from Matt Glickman, Traci Walker-Griffith, Richmond Alake, and Linda Haviv, discussing the foundations of AI agent memory, how engineers can develop at scale, and why they believe AI could be your child’s perfect tutor in the classroom.
Additional materials: www.superdatascience.com/988
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
985: The Four Types of Memory Every AI Agent Needs, with Richmond Alake
Oracle’s Director of AI Developer Experience Richmond Alake returns to the show to talk to Jon Krohn about agent memory; the network of systems, models, databases and LLMs that enable AI agents to learn and adapt over time. Listen to the episode to hear about Richmond’s “100 Days of Agent Memory” initiative, retrieval-augmented generation’s (RAG) limitations with AI agents, the layers of the AI agent stack, and what makes the Oracle AI database so useful to developers.
Additional materials: www.superdatascience.com/985
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
(03:15) What agent memory is and why it’s important
(28:28) RAG’s limitations for AI agents
(35:19) What matters in the AI agent stack beyond memory
(41:34) Why memory was undervalued in the AI agent stack
871: NoSQL Is Ideal for AI Applications, with MongoDB’s Richmond Alake
Agentic AI, AI success strategies, and why flexibility will be so important to keep up with the AI market: Jon Krohn talks to Richmond Alake about the NoSQL database MongoDB, including why it’s a great addition to your toolkit for developing (agentic) AI applications, with a look under the hood at its native vector database. Richmond also talks about why he expects multi-agent AI architectures to go mainstream in 2025.
Additional materials: www.superdatascience.com/871
This episode is brought to you by the Dell AI Factory with NVIDIA and by ODSC, the Open Data Science Conference.
Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.
In this episode you will learn:
(04:10) How Richmond became a Staff Developer Advocate
(07:40) How NoSQL database differs from a relational database
(16:50) The advantages of working with the cloud-based MongoDB Atlas
(32:26) Richmond’s predictions for agentic AI
(40:38) How to create an effective AI strategy
685: Tools for Building Real-Time Machine Learning Applications, with Richmond Alake
Richmond Alake, a Machine Learning Architect at Slalom Build, sits down with Jon to share real-time ML insights, tools and career experiences for a high-energy and high impact episode. From his work at Slalom Build to his two AI startups, discover the software choices, ML tools, and front-end development techniques used by a leader in the field.
This episode is brought to you by Posit, the open-source data science company, by AWS Inferentia, and by WithFeeling.ai, the company bringing humanity into AI. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.
In this episode you will learn:
• What is a Machine Learning Architect? [03:09]
• Richmond's startups [12:07]
• Why Richmond started a podcast [29:51]
• Richmond's new course on feature stores [38:05]
• Why Richmond produces data science content [43:25]
• Why All Data Scientists Should Write [51:30]
Additional materials: www.superdatascience.com/685