Mapping human memory to agents

Richmond Alake is Director of AI Developer Experience at Oracle and one of the most concrete voices on agent memory right now. His AI Engineer World's Fair talk on architecting agent memory crossed 100,000 views, he built the open-source MemoRIS library, and he co-created a course with Andrew Ng.

In this conversation, Richmond walks through memory engineering as a distinct discipline from prompt engineering and context engineering, demos a memory-aware financial services agent that runs vector, graph, spatial, and relational search in a single query, and explains the principle that separates production-grade memory systems from prototypes: don't delete, forget. If you're building agents that need to remember anything across sessions, this is the episode.

We cover:
- Why memory engineering deserves its own name, separate from prompt and context engineering
- The two failure modes Richmond sees most: wrong mental model and deleting instead of forgetting
- Four human memory types mapped to agent architecture: working, episodic, semantic, and procedural
- Demo: AFSA, a memory-aware financial services agent with converged search across data types
- How the Generative Agents paper's decay formula (relevance + recency + importance) enables controlled forgetting
- Where context engineering ends and memory engineering begins 
- Why files work for prototypes but databases win in production

Chapters:
(0:00) Memory is the last battleground in AI
(0:28) Meet Richmond Alake, Oracle's AI DevEx lead
(2:23) Why memory engineering is its own discipline
(7:57) The failure modes nobody talks about
(12:49) Demo: a memory-aware financial services agent
(18:30) Segmenting context windows by memory type
(19:22) Four human memory types mapped to agent architecture
(23:51) Procedural memory in production systems
(27:11) Don't delete, forget: implementing controlled decay (33:32) Sponsor: Galileo
(35:46) Where context engineering ends and memory engineering begins
(38:50) Is agent memory fundamentally a database problem?
(44:13) Files vs. databases: what production actually needs
(51:09) Picking your lane in the AI noise
(55:44) Richmond's courses with Andrew Ng, O'Reilly classes, and where to follow

Connect with Richmond Alake: LinkedIn: https://www.linkedin.com/in/richmondalake/
Check out his Youtube: https://www.youtube.com/@richmond_a
O'Reilly courses: https://www.oreilly.com/live-events/ai-memory-management-in-agentic-systems/0642572179274/
Diagrams from the episode: https://imgur.com/a/mMtcAtk

Connect with Conor:
Newsletter: https://newsletter.chainofthought.show/
Twitter/X: https://x.com/ConorBronsdon
LinkedIn: https://www.linkedin.com/in/conorbronsdon/
YouTube: https://www.youtube.com/@ConorBronsdon

More episodes: https://chainofthought.show

Thanks to Galileo — download their free 165-page guide to mastering multi-agent systems at http://www.galileo.ai/mastering-multi-agent-systems