Vector databases are almost always talked about in the context of RAG. Store your documents, embed them, retrieve the relevant chunks at inference time. That's the default pattern and it works — until it doesn't.
Source: [Dev.to](https://dev.to/gerimate/i-built-a-python-agent-that-uses-a-vector-db-as-memory-not-retrieval-135e)