The Manus project emphasizes the importance of context engineering for AI agents, highlighting lessons learned from building their agent framework. Key practices include optimizing KV-cache usage, avoiding dynamic tool modification during iterations, and utilizing the file system for efficient context management to maintain performance and reduce costs. The article shares insights and principles aimed at helping others develop effective AI agents more rapidly.