Developed a persistent memory backend for Strands Agents within the MemMachine/MemMachine repository, enabling agents to store, search, and delete episodic and semantic memories across sessions. This feature established a foundation for persistent agent cognition, supporting improved continuity and analysis of agent behavior over time. The integration involved API development and memory management, leveraging Python to ensure robust cross-session data handling. Unit testing was applied to validate the new backend’s reliability and maintainability. The work focused on enhancing the agent’s ability to retain and utilize information between sessions, setting the stage for future memory lifecycle improvements within the platform.