Context engineering is a broader approach than prompt engineering, focusing on all inputs an AI sees before generating a response.
Context includes system instructions, user prompts, conversation history, long-term memory, retrieved data, available tools, and structured output formats.
The success of AI agents depends more on the quality of the provided context than on the underlying model.
Context engineering builds dynamic systems that gather and format the right information and tools at the right time.
Presenting context in concise, structured forms prevents missing details and improves AI performance.
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