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In many cases, agentic memory is being reduced to a vector database with embeddings and retrieval. That’s not agentic memory. That’s just storage + search.
Real agentic memory is about: - What an agent should remember vs forget - How memory changes over time (decay, reinforcement, consolidation) - When memory should be read implicitly vs explicitly - How memory influences planning, tool choice, and behavior - How to handle conflicting, stale, or context-dependent memories
A vector DB can be part of the system, but it’s not the system.
Until agents can reliably reason about their own memory and not just retrieve chunks. We’re still in early innings.
Curious what others think: - What does "solving agentic memory" actually mean? - Is this even a single problem, or a bundle of unsolved ones?
