With 91% accuracy, open source Hindsight agentic memory provides 20/20 vision for AI agents stuck on failing RAG

It has become increasingly clear in 2025 that retrieval augmented generation (RAG) isn't enough to meet the growing data requirements for agentic AI.RAG emerged in the last couple of years to become the default approach for connecting LLMs to external knowledge. The pattern is straightforward: chunk documents, embed them into vectors, store them in a database, and retrieve the most similar passages when queries arrive. This works adequately for one-off questions over static documents. But the architecture breaks down when AI agents need to operate across multiple sessions, maintain context over time, or distinguish what they've observed from what they believe.A new open source memory architecture called Hindsight tackles this challenge by organizing AI agent memory into four separate netwo