7 context engineering techniques for production
Seven context engineering techniques used in production AI systems, with implementation patterns and research on when each one works.
Definition
Context Engineering: The practice of deliberately designing, structuring, and managing the information provided to AI models to improve output quality and relevance.
Seven context engineering techniques used in production AI systems, with implementation patterns and research on when each one works.
ETH Zurich found AI-generated context files hurt agent performance by 3%. The problem is structure, not volume. Here's what the research says.
New research analyzed 3,282 MCP bug reports. The patterns reveal a context delivery problem, not a protocol problem. Here's what the research shows.
A context window is the total text an AI model can process at once. Learn how they work, why size isn't everything, and what actually affects performance.
88% of organizations report AI agent security incidents. The root cause is a context engineering failure: agents get all-or-nothing access instead of scoped context.
GPT-5.2 hallucinate at 10.8%, o3-pro at 23.3%. The fix has less to do with better models and more to do with better context engineering.
Prompt engineering is a dead end. Context engineering is the discipline replacing it. Here's what it is, why it matters, and how to apply it.