How can graphs help us model different types of agent memory?
The migration from isolated LLM calls to agentic systems requires a more thoughtful approach to memory management. As these systems become more dependent on long-term memory, we must develop processes to appropriately handle the different situations and types that may arise.
A talk given by Harrison Chase, CEO of LangChain, at the DeepLearning.AI Dev Day conference inspired the ideas for this post. There, he discussed how LangGra...
Read it: Modeling Agent Memory