creativemind_7

One of the biggest limitations with AI agents right now is memory. Most systems rely on stuffing conversation history into a prompt window, which doesn’t scale well and gets expensive fast.

Treating memory as its own layer (semantic recall, entity relationships, temporal context) seems like a much more realistic direction if we want agents that can actually work on long-running projects.

Curious how Remembra handles conflicting memories or bad data over time. Memory quality might end up being just as important as model quality.