Article

Context Engineering for Agents

LangChain · langchain.com

The write, select, compress, isolate framework every team now uses.

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It answers 2 questions

  1. Prompt engineering, RAG, or fine-tuning: which one does my product actually need?
  2. How do I give my agent the right context and memory so it stops forgetting?

Read with it

  1. The canonical guide: curation beats clever prompting for agents. anthropic.com Guide Effective context engineering for AI agents Anthropic
  2. Why context, not model size, unlocks agents that work for hours. sequoiacap.com Podcast Context Engineering Long-Horizon Agents | Harrison Chase Sequoia Training Data (Harrison Chase)
  3. Battle scars from a real production agent, including the KV-cache economics. manus.im Article Context Engineering for AI Agents: Lessons from Building Manus Yichao 'Peak' Ji (Manus)
  4. The post that coined the framing, with the LLM-as-CPU analogy. rlancemartin.github.io Article Context Engineering for Agents (original essay) Lance Martin
  5. An expert's teardown of how Manus applies the theory in production. rlancemartin.github.io Article Context Engineering in Manus Lance Martin
  6. The full conversation, including memory across sessions. latent.space Podcast Context Engineering for Agents | Lance Martin, LangChain Latent Space (Lance Martin)
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