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Context Engineering

We have several parts in context:

  • System prompt
  • User Prompt
  • Dialogue history
  • Memory
  • Relavent information from other sources
  • Tool use
  • Reasoning

What is context engineering

Prompt Engineering is about how to write instructions. Context Engineering is broader - it covers strategies for curating and maintaining the optimal set of tokens during inference, including everything that lands in context window beyond just the system prompt: tools, MCP servers, Skills, external data, message history and so on.

System prompt

Claude's system prompt: link

Context Retrieval

  • Just in time context strategies
    • Rather than pre-loading all relevant data up front, agents maintain lightweight identifiers(file paths, stored queries, web links) and dynamically load data into context at runtime using tools.

Long-Horizon Tasks: Three techniques

  • Compaction
    • It takes a conversation nearing the context window limit, summarizes it, and reinitializes a new context window with the summary.
    • The art lies in selecting what to keep vs. discard, overly aggressive compaction can lose subtle but critical context. Anthropic recommends starting by maximizing recall.
  • Structured Note-Taking
    • It involves the agent regularly writing notes persisted to memory outside the context window, which get pulled back in later.
  • Sub-Agent Architectures
    • Rather than one agent maintaining state across an entire project, specialized sub-agents handle focus tasks with clean context windows. The main agent coordinates with a high-level plan while sub-agents perform deep technical work. Each sub-agent may use tens of thousands of tokens in its exploration but returns only a condensed summary of 1,000–2,000 tokens to the lead agent — achieving a clear separation of concerns.