Context Engineering for AI Agents with LangChain and Manus

This podcast features Lance Martin from LangChain and Peak, the co-founder of Manus, discussing context engineering in AI agents. Lance introduces the concept, highlighting the challenges of managing growing context in autonomous agents and common strategies like context offloading, reduction, retrieval, and isolation. Peak then shares insights from Manus, emphasizing context reduction techniques such as compaction and summarization, different approaches to context isolation, and a layered action space for context offloading. The discussion transitions into a Q&A session, where they address questions about using shell tools, indexing, long-term memory, model selection, summarization prompting, agent-agent communication, planning, guardrailing, and evaluation strategies, providing practical insights and recommendations for managing context in AI agents.