The memory framing is right, but the real gap isn't recall, it's the missing feedback loop tying actions to outcomes. Even with perfect retrieval these agents don't update from a decision that lost money last week; they re-derive from context every step, so the same mistake is always one dropped detail away. And having built retrieval-backed agents, that's where "bolt a database on the side" breaks: similarity search returns the closest chunk, rarely the contextually-right one. Deciding what to write to memory and when to surface it is the actual product, harder than the retrieval itself.

Anybody ever tell you that you write like an LLM?