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Context Engineering

Concepts

  • Context Engineering - Context engineering is the art and science of filling the context window with just the right information at each step of an agent's trajectory
  • Anthropic Context Engineering - Anthropic has published two major pieces on context engineering: a detailed post on their multi-agent research system, and a broader guide on effective context engineering for AI agents
  • Key Challenges in Context Management - As AI agents handle longer tasks and accumulate tool call feedback, the context window becomes a critical bottleneck
  • Context Graph - A Context Graph (CG) is a knowledge structure that extends traditional triple-based Knowledge Graphs (KGs) by attaching rich contextual metadata — temporal validity, geographic location, provenance...
  • Cognition / Devin: Context Engineering Principles - Walden Yan (Cognition, builders of Devin) published "Don't Build Multi-Agents" as a challenge to the prevailing trend of multi-agent architectures
  • The Efficiency Frontier: Cost-Performance Optimization in LLM Context Management - As LLMs increasingly rely on long-context processing, expanding context windows introduces substantial computational and financial costs
  • LangGraph Context Engineering - Lance Martin (LangChain) has been one of the most active voices synthesizing context engineering patterns across the industry
  • Manus Context Engineering - Manus is an autonomous AI agent built by a team led by Yichao 'Peak' Ji
  • Common Strategies for Context Management - Context engineering is the art and science of filling the context window with just the right information at each step of an agent's trajectory