agentic memory

**RAG is not memory. Let me explain why.** After 2 years building AI memory systems, I keep seeing the same mistake: teams treat RAG as a memory solution. It's not. It's a single cognitive process — retrieve, rank, return. Human memory is a dozen interacting processes running in parallel. What RAG misses: **Episodic context.** We remember events tied to emotions, consequences, and causal chains. RAG retrieves chunks with no understanding of *when* something happened or *why* it mattered. **Time.** Not timestamps — directed acyclic graphs of events with causal relationships between them. This is a fundamentally different data structure than a vector index. **Forgetting.** Our memory is optimized to forget. What survives is shaped by recall frequency, emotional weight, and task relevance. RAG has no decay, no prioritization, no attention mechanism. **Task orientation.** Agent memory isn't conversational memory. Agents need to follow plans, respect constraints, apply rules, and expl