Foundation Concepts / Core Definitions

Context Engineering

Intermediate [3/5]
Knowledge management Context design

Definition

Context engineering is the discipline of designing and managing the information systems that provide LLMs with the context they need for reliable task completion. While prompt engineering focuses on crafting individual instructions, context engineering takes a broader systems view.

It encompasses everything from knowledge base design to retrieval strategies, memory management, and the orchestration of multiple information sources to build effective AI applications.

Key Concepts

  • Context window management: Strategically deciding what information fits within the model's token limits
  • Information retrieval: Fetching relevant data from external sources like databases, documents, or APIs
  • Context prioritization: Ranking and filtering information by relevance to maximize signal-to-noise ratio
  • Memory systems: Implementing short-term and long-term memory for maintaining state across interactions
  • Dynamic context: Adjusting context based on the specific task, user, or conversation state

Examples

RAG System
Document-Augmented Assistant
User Query: "What's our refund policy?" Context Engineering Process: 1. Convert query to embedding 2. Search vector database for relevant docs 3. Retrieve top 3 policy documents 4. Rank by relevance score 5. Inject into prompt as context 6. Generate grounded response
A retrieval-augmented generation system that fetches relevant documents to answer queries.
Multi-Source Context
Customer Support Bot
Context Sources: - Customer profile (from CRM) - Recent order history (from database) - Previous conversation summary (from memory) - Product documentation (from knowledge base) - Current policies (from config) All combined into a coherent context window.
Orchestrating multiple data sources to provide comprehensive context for a support interaction.

Interactive Exercise

✎
Design a Context Strategy

You're building a coding assistant. What context sources would you include?

List at least 4 types of context that would help the assistant provide better code suggestions.

Pro Tips
  • Start with the most relevant context and add more only if needed
  • Monitor context window usage to avoid truncation
  • Use summarization for older or less critical context
  • Consider context caching for frequently used information

Related Terms

Context Window RAG Prompt Engineering Chunking Knowledge Base