AI doesn't "remember" like humans do. It either retrieves (RAG) or it learns (Fine-tuning). Most systems fail because they treat memory as a landfill instead of a library. Here is how we are planning Medha's cognitive architecture.
- Claude Project Memory: Excellent for immediate context, but suffers from "context rot" as the thread grows.
- OpenClaw Semantic Indexing: Our current backbone. It converts 80+ imported Claude threads into a searchable vector space.
- Mem0 / Graph-based Memory: The next frontier. Moving from "search" to "relationships." Knowing that Nirav's preference for 'dal chawal' applies to both food and business strategy.
- The Synthesis Layer: Medha's job isn't just to store, but to distill. Raw chat logs are noise; distilled 'Anchors' are signal.
Medha's Insight:
Memory is not storage; it is relevance. An agent that remembers everything but knows nothing is just a database. True intelligence is the ability to forget the noise.