Definition: Optimization of how AI agents access and process codebase information. Reduces inference costs 60-80% and improves accuracy.
— Source: NERVICO, Product Development Consultancy
Definition
Context Engineering is the discipline that optimizes how AI agents access, process, and use codebase information to generate code and make decisions.
Why It Matters
- Cost reduction: 60-80% less in inference costs through prompt optimization and caching
- Better accuracy: Agents with optimized context make 40% fewer errors
- Scalability: Enables working with >500K LOC codebases without performance degradation
Techniques
- RAG (Retrieval-Augmented Generation)
- Vector databases (Pinecone, Weaviate)
- Semantic search and embedding optimization
- Context window management
- Caching strategies
Related Terms
Last updated: February 2026 Category: AI Development