Most "agent memory" today is one thing wearing three hats: a vector database.You embed the past, you retrieve the nearest neighbor, you paste it into the prompt. It works until it doesn't, and when it doesn't, you can't tell whether the agent forgot a fact, forgot an experience, or never learned the skill.
The human brain does not do this. It keeps three separate systems. I built an agent that does the same, and measured what it buys you.
The problem
I gave a language model a database it had never seen (Northwind) and asked it to write SQL. Cold, with no help, a strong model gets it right about a quarter of the time. Not because it can't write SQL, but because it doesn't know the schema, doesn't remember what worked last time, and has no sense of how to approach a question of a given shape. Those are three different kinds of not-knowing, and a single vector store treats them as one.
The brain analogy
