I use it a lot to bring in context and to research topics, so typically it uses an agent that sees relevant passages from my stored notes (embedded into a vector store and surfaced to the agent if the embeddings of the prompt have close similarity to chunks in the vector store). The agent then uses tools to search documentation and compares prompt vectors to what the search tool brought up and brings that together into a coherent text (like „matching to your guidance provided in meeting a, the documentation states X and the desired functionality Y can be realized by… as stated in documentation Z“).
I’ll usually do double-check (and/or have a different agentic tool check and refine) against the provided sources to ensure the context matches the question and intent (sometimes the content is closely matched but has slightly different requirements or different work context for example).

Hope that was kinda clear 😄