How do you design memory systems for long-running AI agents?

The concept sounds interesting. I wonder how the implementation would look like. 1. Which part of the agent decides what to keep and what to through away aka forget/ignore? Programmed agent application logic or an LLM - the brain? 2. How is the persistence part implemented? A database as container is still pretty abstract. What database type, specific product recommendations? How is the serialization done? 3. Based on what criteria would the agent decide what persistent data records are important for the current session and context? These are real implementation aspects I would be interested in. Can we discuss them here? Do you have references to open source examples or relevant articles? Cheers, Michael