Context Engineering for AI Agents - Lessons from Building Manus - AI Agent上下文工程实践经验与核心策略

Context Engineering for AI Agents: Lessons from Building Manus 

Key Logic 

Yichao 'Peak' Ji, a builder of the Manus project, shared their practical experience and lessons learned in Context Engineering for AI Agents. They emphasized that in the rapidly iterating field of AI, relying on in-context learning and effective context management (rather than training models from scratch) is crucial for rapid product development and decoupling from underlying model technologies. They detailed how sophisticated context design can enhance an agent's performance, efficiency, robustness, and adaptability through six core principles, including optimizing KV-cache, intelligent tool management, using the file system as external memory, actively guiding attention, retaining error information to facilitate learning, and avoiding excessive few-shot techniques.