Most AI agents forget critical context within days. Support bots repeat questions. Research loses threads.
Bigger tokens = higher costs, slower responses. Agents still miss buried details. Memory isn't just capacity.
OpenAI Memory, LangMem (semantic/procedural/episodic), MemGPT (swappable tiers), Mem0 (graph-enhanced).
10 extended conversations, ~600 dialogues each, 26K tokens avg. Real production scenarios, not toys.
Mem0 leads overall. Best balance across tasks. Graph variant delivers superior temporal reasoning.
Fast but misses multi-hop details. Best for basic preference tracking. Simple plug-and-play adoption.
Support → OpenAI. Complex research → Mem0 graph. Docs → MemGPT. LangGraph teams → LangMem.
Memory persistence = attack vectors. Poisoning agent memory affects all future interactions. Namespace scoping critical.
No system auto-solves what to remember vs forget. Effective = automatic extraction + manual curation.
Winners make memory invisible to developers while providing predictable performance at scale.