context engineering
Context engineering is the systematic design and optimization of all the information given to a model at inference time so it can respond reliably. This includes prompts, retrieved documents or memory, tool outputs, metadata, policies, and session state.
Unlike prompt engineering, which focuses on creating instructions, context engineering manages the full payload that occupies the model’s context window.
Typical parts include retrieval and selection of content, chunking and ranking, schema-based formatting, grounding and citations, session history, and integration of tool and API outputs.
Related Resources
Tutorial
Context Engineering for Python Codebases
Learn how context engineering shapes what your AI coding agent sees on every turn, and use four practical strategies to keep your Python projects on track.
