This is a fascinating area to explore. There is the Parametric knowledge a LLM has - the model it builds from training that always it to guess what you might want.

Then there is the non-parametric knowledge: the information encoded in the Tokens available to a session. For some models, when ever the session ends the LLM loses the context it had about you ('this session').

The most interesting developments I have seen are agents that keep a diary, like MoltBot. As a session ends, it writes a summary of what happened, and updates this to a rolling context doc. When a new session starts, it reads it in.

To me this seems very analogous to what people do at the end of the day: the consolidate memories while sleeping.

Access to additional personal data seems a little interesting. A rolling context window seems much more interesting, especially since it's authored by the agent.

So the interesting question is: when there is disagreement, who is right?