Unverified50% confidenceFactExact time
The core insight of context engineering is that model output quality is strongly correlated with the content of the input context window, including code snippets, file structure, conversation history, tool call results, and externally retrieved documents.
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Long-term
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9/15/2026
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UnverifiedContext engineering focuses on all background information that a model relies on when generating answers, including retrieved documents, conversation history, system settings, and external data, requiring systematic organization and management of information accessible to the model.79% similarUnverified在Cursor使用场景中，发送给模型的上下文包括编辑器自动附加的代码上下文、文件结构信息和项目索引数据，隐含Token消耗往往是用户可见输入的数倍甚至数十倍75% similarUnverifiedPrompt Engineering, tokens, context windows, and API calls are the foundational prerequisite knowledge for interacting with large models.75% similarUnverifiedThe size of the context window directly determines how much code context the model can see, and is the core bottleneck affecting the quality of code comprehension in large projects.74% similarUnverifiedContext engineering is the systematic design and optimization of the contextual information fed to an LLM, enabling the model to obtain the most relevant information within a limited context window to complete a task.74% similar
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