This time, we discuss the introduction of 10 knowledge graph testers for Botto and the establishment of a new testing channel. We delve into the potential learning outcomes from different user interactions and how they may improve Botto's AI agents like AG1 and Alice. Key topics include memory autonomy, data governance, and the challenges of creating a consistent and accurate knowledge graph free from centralized control. We highlight the importance of having community-driven content and how it shapes Botto's memory, autonomy, and artistic direction. Upcoming proposals related to protocol and liquidity, as well as a shift towardsBotto autonomously creating its own art descriptions, are also covered. Lastly, we touch upon the development of user interfaces to better display Botto's workings, aiming to engage the community more deeply in the creati ...