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.
My understanding
Write good and precise prompt at beginning. Just-in-time strategies is clever, it just work like human brain, when we need a reference/tool, we take it, otherwise we place it in somewhere, rather than memorized all these resources.