Really enjoyed this deep dive—especially point #4 around memory.
One thing I’ve seen trip up a lot of teams is assuming “LLMs with longer context windows = solved memory.” But real product-grade memory usually needs more than recall—it needs scope (per user/project/session), persistence (across sessions), and control (TTL, deletion, audit).
We’ve been working on this exact problem with Recallio: a scoped memory API you can drop into any AI app without building custom vector infra or brittle RAG pipelines. It’s early but proving useful for teams who want their app to “remember” without overengineering.
Would love to jam more on the difference between memory as UX glue vs memory as pure retrieval infra—feels like that line is getting blurrier every month.
What a simplification!!
Great post, thank you for sharing! I appreciate you including the ethical aspects! 😊
I'm glad you find this useful Karo 😍
Really enjoyed this deep dive—especially point #4 around memory.
One thing I’ve seen trip up a lot of teams is assuming “LLMs with longer context windows = solved memory.” But real product-grade memory usually needs more than recall—it needs scope (per user/project/session), persistence (across sessions), and control (TTL, deletion, audit).
We’ve been working on this exact problem with Recallio: a scoped memory API you can drop into any AI app without building custom vector infra or brittle RAG pipelines. It’s early but proving useful for teams who want their app to “remember” without overengineering.
Would love to jam more on the difference between memory as UX glue vs memory as pure retrieval infra—feels like that line is getting blurrier every month.
Great Post!